ICORES 2019 Abstracts

Area 1 - Methodologies and Technologies
Full Papers Short Papers
Area 2 - Applications
Full Papers Short Papers

Area 1 - Methodologies and Technologies

Full Papers
Paper Nr: 8
Title:

Algorithms for Reorganizing Branches within Enterprise Network
Authors:

Milan Dordevic and Hiba Tabbara
Abstract: The problem of reorganizing branches in an enterprise network is based on a weighted graph problem formulation. The suboptimal solution to this problem is obtained by applying a two-phase algorithm. The first is to decompose the graph into different sections in such a way that those sections are equally balanced. The second phase is to find a service centre for each section. In this paper, we propose an improvement of a hybrid genetic algorithm for decomposing the graph into different sections. We also propose new algorithms for finding centres of sections and we compare them on an illustrated examples.
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Paper Nr: 9
Title:

The Owen and the Owen-Banzhaf Values Applied to the Study of the Madrid Assembly and the Andalusian Parliament in Legislature 2015-2019
Authors:

José M. Giménez and María A. Puente
Abstract: This work focuses on the Owen value and the Owen-Banzhaf value, two classical concepts of solution defined on games with structure of coalition blocks. We provide a computation procedure for these solutions based on a method of double-level work obtained from the multilinear extension of the original game. Moreover, two applications to several possible political situations in the Madrid Assembly and the Andalusian Parliament (legislatures 2015-2019) are also given.
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Paper Nr: 12
Title:

Scheduling on Dedicated Machines with Energy Consumption Limit
Authors:

István Módos, Kiryl Kalodkin, Přemysl Šůcha and Zdeněk Hanzálek
Abstract: This work studies a problem of scheduling non-preemptive independent jobs on dedicated machines while considering an energy consumption limit. The problem is motivated by energy-demanding production processes, such as glass tempering and steel hardening, in which a material is heated to high temperature in furnaces. The production companies have contracts with electric utilities that specify a maximum energy consumption limit. If the heating in the furnaces is not planned carefully, the energy spikes overshoot the energy consumption limit, and the companies must pay large penalty fees. In this paper, we propose two exact methods that find schedules with the minimum makespan such that the energy limit is satisfied. The first proposed method is a Constraint Programming model and the second one finds the optimal solution by iteratively re-solving a Mixed Integer Linear Programming model with a decreasing scheduling horizon. The iterative algorithm exploits the fact that the start times do not need to be modeled explicitly, which leads to an efficient method for solving instances with a higher number of shorter jobs. The experimental results show that our methods outperform an adapted approach from the literature for a related problem.
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Paper Nr: 16
Title:

The Emission Ordering Strategy with Green Awareness under the Emission Trading System (ETS)
Authors:

S. Y. Wang and S. H. Choi
Abstract: Global concerns for environmental sustainability obligate manufacturers under the Emission Trading Scheme (ETS) to reduce carbon emission substantially. While green awareness inspires manufacturer investment in green upgrade, it is crucial for emission-limited firms to improve production scheduling in order to compete in the stringent low-carbon market. This paper solves the emission ordering problem by considering the green investment strategy. It adopts newsvendor models with novelty in the use of the Lagrange Multipliers and Karush-Kuhn-Tucker (KKT) conditions to achieve the optimality subject to emission constraints. Although this method has been used in economics, it is first explored in this paper for low-carbon production to achieve optimality together with the emission targets. The results call for the manufacturer to make better decisions for achieving both the optimality and the emission reduction.
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Paper Nr: 21
Title:

Newsvendor Model for Multi-Inputs and -Outputs with Random Yield: Applications to Agricultural Processing Industries
Authors:

Kannapha Amaruchkul
Abstract: Consider a newsvendor model, which we extend to include both multiple inputs and outputs. Different input types possess different levels of quality, and are purchased at different prices by a processing firm. Each type of input is processed into multiple outputs, which are sold at different prices. The yield for each output type is random and depends on the input type. We need to determine the purchase quantities of different types of input, before demands of different types of output are known. In our analytical results, we show that the expected total profit is jointly concave in the purchasing quantities and derive the optimality condition. Our multi-input and -output newsvendor model is suitable for processing industries in agriculture supply chain. In our numerical example, we apply our model to the rice milling industry, whose primary output is head rice and byproducts are broken rice, bran and husk. Our model can help the rice mill to decide which paddy types to procure and how much, in order to maximize the total expected profit from all outputs. We also show that the expected profit can be significantly better than using the standard newsvendor model.
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Paper Nr: 27
Title:

Using Phase-type Models to Monitor and Predict Process Target Compliance
Authors:

Sally I. McClean, David A. Stanford, Lalit Garg and Naveed Khan
Abstract: Processes are ubiquitous, spanning diverse areas such as business, production, telecommunications and healthcare. They have been studied and modelled for many years in an attempt to increase understanding, improve efficiency and predict future pathways, events and outcomes. More recently, process mining has emerged with the intention of discovering, monitoring, and improving processes, typically using data extracted from event logs. This may include discovering the tasks within the overall processes, predicting future trajectories, or identifying anomalous tasks. We focus on using phase-type process modelling to measure compliance with known targets and, inversely, determine suitable targets given a threshold percentage required for satisfactory performance. We illustrate the ideas with an application to a stroke patient care process, where there are multiple outcomes for patients, namely discharge to normal residence, nursing home, or death. Various scenarios are explored, with a focus on determining compliance with given targets; such KPIs are commonly used in Healthcare as well as for Business and Industrial processes. We believe that this approach has considerable potential to be extended to include more detailed and explicit models that allow us to assess complex scenarios. Phase-type models have an important role in this work.
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Paper Nr: 29
Title:

Makespan Minimization with Sequence-dependent Non-overlapping Setups
Authors:

Marek Vlk, Antonin Novak and Zdenek Hanzalek
Abstract: This paper deals with a scheduling problem that emerges in the production of water tubes of different sizes that require reconfiguration of the machines. The reconfiguration of the machines leads to the notion of sequence-dependent setup times between tasks. These setups are often performed by a single person who cannot serve more than one machine at the same moment, i.e., the setups must not overlap. Surprisingly, the problem with non-overlapping setups has received only a little attention so far. To solve this problem, we propose an Integer Linear Programming formulation, Constraint Programming models and a hybrid heuristic that leverages the strength of Integer Linear Programming in the shortest Hamiltonian path problem and the efficiency of Constraint Programming at sequencing problems with makespan minimization. The experimental evaluation shows that among the proposed exact approaches, the Constraint Programming is a superior method being able to solve instances with 3 machines and up to 11 tasks on each machine to optimality within a few seconds. The proposed hybrid heuristic attains high-quality solutions for instances with 50 machines and up to 116 tasks on each machine.
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Paper Nr: 39
Title:

Modeling the Esscher Premium Principle for a System of Elliptically Distributed Risks
Authors:

Tomer Shushi
Abstract: The Esscher premium principle provides an important framework for allocating a certain loaded premium for some claim (risk) in order to manage the risks of insurance companies. In this paper, we show how to model the celebrated Esscher premium principle for a system of elliptically distributed dependent risks, where each risk is greater or equal than its value-at-risk. Furthermore, we present calculations of the proposed multivariate risk measure, investigate its properties and formulas, and show how special elliptical models can be implemented in the theory.
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Paper Nr: 45
Title:

A Heuristic Method for the Multi-skill Project Scheduling Problem with Partial Preemption
Authors:

Oliver Polo-Mejía, Christian Artigues and Pierre Lopez
Abstract: In this article we consider a new scheduling problem known as the Multi-Skill Project Scheduling Problem with Partial Preemption. The main characteristic of this problem is the way we handle the resources release during the preemption periods: only a subset of resources are released. Since this problem is NP-hard, we propose a greedy algorithm based on priority rules, modeling the subproblem of technicians allocation as a Minimum-Cost Maximum-Flow problem. In order to improve the performance of the greedy algorithm, we propose a randomized tree-based local search algorithm. Computational tests are carried out and analyzed.
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Paper Nr: 47
Title:

A State Dependent Chat System Model
Authors:

Per Enqvist and Göran Svensson
Abstract: The main purpose of this paper is to introduce a model of a chat based communication system, as well as developing the necessary tools to enable resource optimization with regards to a measure of the service quality. The system is modeled by a Markov process in continuous time and with a countable state space. The construction of the intensity matrix corresponding to this system is outlined and proofs of a stationary state distribution and an efficient way of calculating it are introduced. A numerical example for system optimization when the service measure is the average sojourn time is included as well as a heuristic algorithm for quicker solution generation.
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Paper Nr: 53
Title:

Multi-label Classification for the Generation of Sub-problems in Time-constrained Combinatorial Optimization
Authors:

Luca Mossina, Emmanuel Rachelson and Daniel Delahaye
Abstract: This paper addresses the resolution of combinatorial optimization problems presenting some kind of recurrent structure, coupled with machine learning techniques. Stemming from the assumption that such recurrent problems are the realization of an unknown generative probabilistic model, data is collected from previous resolutions of such problems and used to train a supervised learning model for multi-label classification. This model is exploited to predict a subset of decision variables to be set heuristically to a certain reference value, thus becoming fixed parameters in the original problem. The remaining variables then form a smaller subproblem whose solution, while not guaranteed to be optimal for the original problem, can be obtained faster, offering an advantageous tool for tackling time-sensitive tasks.
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Paper Nr: 54
Title:

Virtual Network Functions Placement for Defense Against Distributed Denial of Service Attacks
Authors:

Sonia Haddad-Vanier, Celine Gicquel, Lila Boukhatem, Kahina Lazri and Paul Chaignon
Abstract: In this paper, we are interested in the problem of Virtual Network Function (NFV) placement to counter Distributed Denial of Service (DDoS) attacks. A DDoS attack is one of the most common and damaging types of cyberattacks. In Network Function Virtualization (NFV) technology network functions, more specifically security mechanisms, are implemented as software. Such approach significantly reduces the cost of the infrastructure and simplifies the deployment of new services. We propose two new models for this critical and complex problem. The first model is a mixed-integer linear program aiming at eliminating all DDos attacks before they reach their target. As its size grows exponentially with the network size, we propose a constraint generation algorithm to solve it. The numerical results obtained for different realistic network instances show the effectiveness of our approach. The second model is a bilevel programming problem that achieves a tradeoff between NFVs placement costs and security levels requirements. Our results show that this mechanisms overcomes DDos attacks by effectively filtering attacks while minimizing the total cost of deployed NFV.
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Paper Nr: 59
Title:

Primal Heuristic for the Linear Ordering Problem
Authors:

Ravi Agrawal, Ehsan Iranmanesh and Ramesh Krishnamurti
Abstract: In this paper, we propose a new primal heuristic for the Linear Ordering Problem (LOP) that generates an integer feasible solution from the solution to the LP relaxation at each node of the branch-and-bound search tree. The heuristic first finds a partition of the set of vertices S into an ordered pair of subsets {S1,S2} such that the difference between the weights of all arcs from S1 to S2 and the weights of all arcs from S2 to S1 is maximized. It then assumes that all vertices in S1 precede all vertices in S2 thus decomposing the original problem instance into subproblems of smaller size i.e. on subsets S1 and S2. It recursively does so until the subproblems can be solved quickly using an MIP solver. The solution to the original problem instance is then constructed by concatenating the solutions to the subproblems. The heuristic is used to propose integer feasible solutions for the branch-and-bound algorithm. We also devise an alternate node selection strategy based on the heuristic solutions where we select the node with the best heuristic solution. We report the results of our experiments with the heuristic and the node selection strategy based on the heuristic.
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Paper Nr: 61
Title:

Vehicle Routing Problem for Information Collection in Wireless Networks
Authors:

Luis F. Luyo, Agostinho Agra, Rosa Figueiredo, Eitan Altman and Eladio O. Anaya
Abstract: Advances in computer network architecture add continuously new features to vehicle routing problems. In this work, the Wireless Transmission Vehicle Routing Problem (WT-VRP) is studied. It looks for a route to the vehicle responsible for collecting information from stations as well as an efficient information collection planning. The new feature added here is the possibility of picking up information via wireless transmission, without visiting physically the stations of the network. The WT-VRP has applications in underwater surveillance and environmental monitoring. We discuss three criteria for measuring the efficiency of a solution and propose a mixed integer linear programming formulation to solve the problem. Computational experiments were done to access the numerical complexity of the problem and to compare solutions under the three criteria proposed.
Paper Nr: 72
Title:

Stochastic Dynamic Pricing with Strategic Customers and Reference Price Effects
Authors:

Rainer Schlosser
Abstract: In many markets, customers strategically time their purchase by anticipating future prices and by checking offer prices multiple times. Typically, customers base their decisions on historical reference prices and their individual willingness-to-pay, which can change over time. For sellers it is challenging to derive successful pricing strategies as customers’ reservation prices cannot be observed. In this paper, we present a stochastic dynamic finite horizon framework to determine optimized price adjustments for selling perishable goods in the presence of strategic customers, which (i) recur and (ii) anticipate future prices based on reference prices. We analyze the impact of different strategic behaviors on expected profits and the evolution of sales. Compared to myopic settings, we find that recurring customers lead to higher average prices, delayed sales, and increased profits. The presence of forward-looking customers has opposing but less intense effects.
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Paper Nr: 74
Title:

Using Data Mining Techniques to Forecast the Normalized Difference Vegetation Index (NDVI) in Table Grape
Authors:

Javier E. Gómez-Lagos, Marcela C. González-Araya, Rodrigo O. Blu and Luis A. Espejo
Abstract: The Normalized Difference Vegetation Index (NDVI) is a simple indicator that quantifies aerial biomass in fruit crops, which is correlated with the fruit yield and quality produced by an orchard. Therefore, knowing the NDVI values would allow predicting productive parameters above mentioned, which in turn would help planning operational activities such as harvesting. In this study, we estimated the NDVI of a Chilean table grape orchard based on past data using data mining techniques. For this purpose, we developed a three-step method, obtaining NDVI predictions with high accuracy.
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Paper Nr: 77
Title:

A Selective Scheduling Problem with Sequence-dependent Setup Times: A Risk-averse Approach
Authors:

Maria E. Bruni, Sara Khodaparasti and Patrizia Beraldi
Abstract: This paper addresses a scheduling problem with parallel identical machines and sequence-dependent setup times in which the setup and the processing times are random parameters. The model aims at minimizing the total completion time while the total revenue gained by the processed jobs satisfies the manufacturer’s threshold. To handle the uncertainty of random parameters, we adopt a risk-averse distributionally robust approach developed based on the Conditional Value-at-Risk measure hedging against the worst-case performance. The proposed model is tested via extensive experimental results performed on a set of benchmark instances. We also show the efficiency of the deterministic counterpart of our model, in comparison with the state-of-the-art model proposed for a similar problem in a deterministic context.
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Short Papers
Paper Nr: 10
Title:

A Fuzzy Logic Controller for Demand Side Management in Smart Grids
Authors:

Sara Atef and Amr B. Eltawil
Abstract: Smart Grid Demand Side Management is the effective way for energy providers to encourage their customers on reducing their consumption during peak loads through several Demand Response programs. In this paper, An Artificial Intelligence approach based on a Fuzzy Logic control system is proposed for the home appliance scheduling problem. This is typically used in Home Energy Management Systems for the control of Heating, Ventilation, and Air Conditioning Systems (HVAC). The simulation results demonstrate the capability of the proposed model to manage and control of HVAC systems in a smarter way than traditional techniques. Furthermore, a reduction of 18.33% in total hourly energy consumption has been obtained after introducing a new parameter among the fuzzy input variables.
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Paper Nr: 11
Title:

The Capacitated Lot Sizing Problem with Batch Ordering: A MILP and Heuristic Approach
Authors:

Gustavo Macedo-Barragán, Samuel Nucamendi-Guillén, Elías Olivares-Benitez and Omar G. Rojas
Abstract: This article presents a mixed integer linear programming method and a heuristic algorithm to deal with the problem of multi-period, multiple-product batch purchases, with a finite time horizon, considering delivery times, order placement costs and independent batch size for each product. The objective of this problem is to minimize the costs of placing purchase orders and inventory. This problem is motivated by its application in a marketing company that handles the sale of fashion products (footwear and accessories) through catalogs and for which excess inventory represents a major problem given the short life cycle of its products. Experimental results show that the heuristic algorithm is able to obtain feasible solutions that improve in cost by up to 37% the best integer solutions reported by the model when it reaches the time limit. To validate the efficiency of the algorithm, a real scenario was solved for a trading company, obtaining results that improve by 28% compared to the current company’s situation. These results show that the heuristic approach is promising in terms of the quality of the solution and the computational time required.
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Paper Nr: 18
Title:

Investigation on Pricing Decisions of Remanufactured Products and Profit of Supply Chain
Authors:

Yasutaka Kainuma
Abstract: This study investigates the closed-loop supply chain (CLSC) with respect to hybrid manufacturing/remanufacturing systems. In this study, a hybrid manufacturing/remanufacturing model is designed that encompasses the simultaneous production of new manufactured products and remanufactured products; this model is used to investigate the profitability of a hybrid manufacturing/remanufacturing system. The impact on the demand for new products (cannibalization effect) caused by selling remanufactured products is a concern among companies with respect to promoting the CLSC. The purpose of this study is to examine the effects on the profits obtained by a company. Numerical experiments are conducted to confirm the profitability of a hybrid manufacturing/remanufacturing system; the relationship between the demand for manufactured products and that for re-manufactured products is also investigated. This study proposes a pricing model for remanufactured products by considering consumers’ willingness to pay. The analytical results indicate that the cannibalization effect was suppressed by considering these, and it is clear that remanufactured products increase company profits.
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Paper Nr: 23
Title:

Supply Chain Agility: Review of Situations
Authors:

Selmen Boubaker, Zied Jemaï, Evren Sahin and Yves Dallery
Abstract: Supply chains are often exposed to internal and external disturbances, events and changes, i.e. situations that harm their performance and present a serious threat to their subsistence. Agility, which is often presented as the ability to cope rapidly and effectively with changes become a competitive advantage for supply chains and is of vital competence. Different Authors mentioned external pressures that motivate supply chains to acquire agile capabilities. However, a well-structured study of external and internal situations needing agility was not found. The aim of our study is to review the existing literature on supply chain agility to better understand this concept and propose an overview of situations requiring supply chain agility, based on academic and industrial work.
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Paper Nr: 25
Title:

Inventory Replenishment Planning of a Distribution System with Warehouses at the Locations of Producers and Minimum and Maximum Joint Replenishment Quantity Constraints
Authors:

Bo Dai, Haoxun Chen, Yuan Li, Yidong Zhang, Xiaoqing Wang and Yuming Deng
Abstract: In this paper, an inventory replenishment planning problem in a three-echelon distribution system of Alibaba is studied. In addition to central distribution centers and front distribution centers, this system also has warehouses at the locations of producers. Multiple products are jointly replenished with minimum and maximum joint replenishment quantity constraints. Transshipments between distribution centers/warehouses are allowed. This problem, which is to determine the replenishment quantity of each product between any two inventory locations in the system, is formulated as a bi-objective optimization model that aims at finding a tradeoff between overall service level and total logistics cost of the system. This model is solved by applying an augmented ɛ-constraint method. The effectiveness of the model is demonstrated by numerical experiments generated from the data of Alibaba. The results show that having warehouses at the locations of producers can lead to lower logistics costs with a given customer service level.
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Paper Nr: 32
Title:

A Hybrid Genetic and Simulation Annealing Approach for a Multi-period Bid Generation Problem in Carrier Collaboration
Authors:

Elham J. Mamaghani, Haoxun Chen and Christian Prins
Abstract: In this article, a new vehicle routing problem appeared in carrier collaboration via a combinatorial auction (CA) is studied. A carrier with reserved requests wants to determine within a time horizon of multi periods (days) which requests to serve among a set of selective requests open for bid of the auction to maximize its profit. In each period, the carrier has a set of reserved requests that must be served by the carrier itself. Each request is specified by a pair of pickup and delivery locations, a quantity, and two time windows for pickup and delivery respectively. The objective of the carrier is to determine which selective requests may be served in each period in addition of its reserved requests and determine optimal routes to serve the reserved and selective requests to maximize its total profit. For this NP-hard problem, a mixed-integer linear programming model is formulated and a genetic algorithm combined with simulated annealing is proposed. The algorithm is evaluated on instances with 6 to 100 requests. The computational results show this algorithm significantly outperform CPLEX solver, not only in computation time but also in solution quality.
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Paper Nr: 33
Title:

Online Algorithms for Leasing Vertex Cover and Leasing Non-metric Facility Location
Authors:

Christine Markarian and Friedhelm A. der Heide
Abstract: We consider leasing variants of two classical N P-hard optimization problems, Vertex Cover (VC) and non-metric Facility Location (non-metric FL). These contain the well-known Parking Permit problem due to Meyerson [FOCS 2005] as a special sub-case and can be found as sub-problems in many operations research applications. We give the first online algorithms for these two problems, evaluated using the standard notion of competitive analysis in which the online algorithm whose input instance is revealed over time is compared to the optimal offline algorithm which knows the entire input sequence in advance and is optimal. Our algorithms have optimal and near-optimal competitive ratios for the leasing variants of VC and non-metric FL, respectively.
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Paper Nr: 34
Title:

Literature Review on Shortage Cost Modeling in Inventory Management
Authors:

Mohamed H. Selmi, Zied Jemai, Laurent Grégoire and Yves Dallery
Abstract: In this article, we emphasize on one hand the importance of quantifying the shortage cost in order to measure the optimal parameters for any selected inventory policy and thus enhance the performance of the supply chain and on the other hand the complexity of doing so. Then, we provide a detailed literature review of the existing various models for quantifying the shortage cost in an inventory management context along with a classification of this literature under three categories: Theoretical descriptive models, empirical approaches and simulation based models. Finally, we point out some gaps in this literature such as the lack of continuity of research in this field and the absence of generic fairly easy to apply but accurate methods and we suggest a few future perspectives.
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Paper Nr: 36
Title:

A Simulation based Optimization Study for Optimum Sequencing of Precast Components Considering Supply Chain Risks
Authors:

Mohamed M. Yusuf, Ahmed Karam and Amr B. Eltawil
Abstract: Unquestionably, Precast Supply Chain (PSC) abounds with many risks distributed along its echelons. Despite that there is a wide consensus among the previous studies about the negative impact of these risks on the PSC performance, its effect on making operational decisions in precast plants such as scheduling of Precast Components (PCs) is still ambiguous. So, this study aims at exploring and quantifying the effect of considering PSC risks on the optimum PCs sequences. To accomplish this, different processes of the PSC with their associated risks are modelled via a discrete event simulation model. Then, the developed simulation model is linked with an optimizer to generate PCs sequences that achieve on-time delivery of PCs with minimum production costs. This optimization process is conducted twice, with and without considering supply chain risks. Interestingly, the optimum PCs sequences generated in both cases are totally different. More importantly, the optimized PCs sequences produced without considering risks may backfire and cause higher production and penalty costs if they are applied to a PSC exposed to risk. So, investing in making a reliable risk management plan of the PSC not only can cushion the risks impact but also can lead to better sequences of PCs.
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Paper Nr: 52
Title:

Undominated Valid Inequalities for a Stochastic Capacitated Discrete Lot-sizing Problem with Lead Times, Cancellation and Postponement
Authors:

Carlos E. Testuri, Héctor Cancela and Víctor M. Albornoz
Abstract: The problem addresses the expected cost minimization of meeting the uncertain demand of a product during a discrete time planning horizon. The product is supplied by selecting fixed quantity shipments that have lead times. Due to the uncertainty of demand, corrective actions, such as shipment cancellations and postponements, must be taken with associated costs and delays. The problem is modeled as an extension of the discrete lot-sizing problem with different capacities and uncertain demand, which belongs to the N P-hard class. To improve the resolution of the problem by tightening its formulation, valid inequalities based on the (,̀S) inequalities approach are used. Given that the inequalities are highly dominated for most experimental instances, a scheme is established to determine undominated ones. Computational experiments are performed on the resolution of the model and variants that include subsets of undominated and representative valid inequalities for instances of several information structures of uncertainty. The experimental results allow to conclude that the inclusion of undominated and representative derived (,̀S) valid inequalities enable a more efficient resolution of the model.
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Paper Nr: 55
Title:

Improvements in the Current Brazil's Energy Dispatch Optimization: Load Forecast and Wind Power
Authors:

Gheisa T. Esteves, Paula M. Maçaira, Fernando C. Oliveira, Gustavo Amador and Reinaldo C. Souza
Abstract: In the last years, Brazil has been passing through some significant changes into its electricity matrix, where natural gas, wind power and other renewables sources are increasing its share on power generation. Those on going changes represent a challenge to power generation dispatch, demanding improvements and major changes on its management and optimization, especially due to growing levels of wind power generation. From the power demand perspective, the use of too optimist power demand forecasts for energy planning and dispatch optimization purposes affects it directly. This article intends to address those two issues, as it proposes an alternative model to forecast electricity demand and conceives a procedure to integrate wind power generation on the power dispatch model currently used in Brazil. The article study the Brazilian Northeast region as it is where most of the wind power farms are located. Power demand forecasts are obtained via electricity consumption forecasts made using Autoregressive Distributed Lag – ADL models, considering macroeconomics perspectives to estimate it. To integrate wind power integration on the actual dispatch model, the Markov Chain Monte Carlo method – MCMC was used to simulate wind power generation and calculate the net power demand, which was considered in the dispatch model.
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Paper Nr: 57
Title:

A Simulation-based Optimisation Approach for Inventory Management of Highly Perishable Food
Authors:

Ning Xue, Dario Landa-Silva, Grazziela P. Figueredo and Isaac Triguero
Abstract: The taste and freshness of perishable foods decrease dramatically with time. Effective inventory management requires understanding of market demand as well as balancing customers needs and preferences with products’ shelf life. The objective is to avoid food overproduction as this leads to waste and value loss. In addition, product depletion has to be minimised, as it can result in customers reneging. This study tackles the production planning of highly perishable foods (such as freshly prepared dishes, sandwiches and desserts with shelf life varying from 6 to 12 hours), in an environment with highly variable customers demand. In the scenario considered here, the planning horizon is longer than the products’ shelf life. Therefore, food needs to be replenished several times at different intervals. Furthermore, customers demand varies significantly during the planning period. We tackle the problem by combining discrete-event simulation and particle swarm optimisation (PSO). The simulation model focuses on the behaviour of the system as parameters (i.e. replenishment time and quantity) change. PSO is employed to determine the best combination of parameter values for the simulations. The effectiveness of the proposed approach is applied to some real-world scenario corresponding to a local food shop. Experimental results show that the proposed methodology combining discrete event simulation and particle swarm optimisation is effective for inventory management of highly perishable foods with variable customers demand.
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Paper Nr: 68
Title:

Approximation of Tandem Queues with Blocking
Authors:

Dug H. Moon and Yang W. Shin
Abstract: In this paper, we present an approximate analysis for tandem queues with single reliable server at each service station and a buffer of finite capacity between service stations. Blocking-After-Service (BAS) rule is adopted. The effects of the moments of service times to the throughput are investigated numerically and the service time is fitted with a phase type (PH) distribution by matching the first two moments. The system with phase type service times is approximated based on the decomposition method with two-server-one-buffer subsystem. Some numerical examples are presented for accuracy of approximation.
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Paper Nr: 75
Title:

Dynamic Index Tracking via Stochastic Programming
Authors:

Patrizia Beraldi, Antonio Violi, Maria E. Bruni and Gianluca Carrozzino
Abstract: Index tracking (IT) is an investment strategy aimed at replicating the performance of a given financial index, taken as benchmark, over a given time horizon. This paper deals with the IT problem by proposing a stochastic programming model where the tracking error is measured by the Conditional Value at Risk (CVaR) measure. The multistage formulation overcomes the myopic view of the static models considering a longer time horizon and provides a more flexible paradigm where the initial strategy can be revised to account for changed market conditions. The proposed formulation presents a bi-objective function, where the two conflicting criteria wealth maximization and risk minimization, are jointly accounted for by properly choosing the weight to attribute to the two terms. The model is encapsulated within a rolling horizon scheme and solved iteratively exploiting each time the more update information in the generation of the scenario tree. The preliminary computational experiments carried out by considering as benchmark the Italian index FSTE-MIB seem to be promising and show that, on an out-of-sample analysis, the tracking portfolios follow the benchmark very closely, overcoming it on the long run.
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Paper Nr: 80
Title:

Efficient Imputation Method for Missing Data Focusing on Local Space Formed by Hyper-Rectangle Descriptors
Authors:

Do G. Kim and Jin Y. Choi
Abstract: In real world data set, there might be missing data due to various reasons. These missing values should be handled since most data analysis methods are assuming that data set is complete. Data deletion method can be simple alternative, but it is not suitable for data set with many missing values and may be lack of representativeness. Furthermore, existing data imputation methods are usually ignoring the importance of local space around missing values which may influence quality of imputed values. Based on these observations, we suggest an imputation method using Hyper-Rectangle Descriptor (ܪܴܦ) which can focus on local space around missing values. We describe how data imputation can be carried out by using ܪܴܦ, named ܪܴܦ_݅݉݌ݑݐ݁, and validate the performance of proposed imputation method with a numerical experiment by comparing to imputation results without ܪܴܦ. Also, as a future work, we depict some ideas for further development of our work.
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Paper Nr: 83
Title:

Optimal Design of Production Systems: Metaoptimization with Generalized De Novo Programming
Authors:

Helena Brožová and Milan Vlach
Abstract: Milan Zelený, in a number of papers, proposed and developed specially structured LP model called De Novo Programming. This approach uses, in an essential way, a transformation of the original problem to continuous knapsack problem, and it concerns only models with capacity constraints and some implicit assumptions about the problem data. Here we extend this methodology to cases involving not only capacity constraints but also requirement and balance constraints. This extension is based on the methodology of Zelený and uses some principles of the STEM methods. We present an example of an adaptation of De Novo approach for models with both capacity, requirement and balance constraints.
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Paper Nr: 15
Title:

A Stochastic Optimization Approach of Flow Shop Sequencing Problem for On-time Delivery of Precast Components
Authors:

Mohamed M. Yusuf, Ahmed Karam and Amr B. Eltawil
Abstract: Recently, the flow shop sequencing problem in precast plants has been witnessing remarkable interest from many researchers. This paper contributes to recent literature by providing a simulation-based optimization approach to solve the precast flow shop sequencing problem taking into account the uncertainty of processing times of precast production operations. The proposed approach is developed by integrating a Discrete Event Simulation (DES) model, which is built to capture the realistic features of precast production activities, and OptQuest® to find the optimum sequencing of Precast Components (PCs). The proposed approach is validated against another approach from literature. In addition, its practicability is put to the test by applying the proposed approach to a real case study. The obtained results indicated that pre-casters can use this approach to attain better PCs sequences than that based on a rule of thumb.
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Paper Nr: 26
Title:

Project Portfolio Risk Prediction and Analysis using the Random Walk Method
Authors:

Xingqi Zou, Qing Yang, Qian Hu and Tao Yao
Abstract: Based on the interdependency relationship among projects, the paper analyses risk factors in the project portfolio network via the random walk algorithm. Sustainability is one of the most important challenges of the project and portfolio management. This paper analyses the interdependencies among projects in a portfolio from the perspective of sustainable development and builds models to measure the relationship among risk factors via the Multidomain matrix (MDM) method. Using the interdependency relationship among projects and potential relationship between different risk factors as inputs, the paper builds the model of portfolio risk network to predict the risk in the project portfolio via a random walk algorithm. Because the random walk is a personalized recommendation algorithm, so our proposed method can achieve an accurate prediction of portfolio risk through predicting the risk factors and their probabilities in the portfolio. Our method can also help project managers to rank these risk factors in the portfolio through distinguishing the most concerned risks.
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Paper Nr: 28
Title:

Modeling and Evaluation of a City Logistics System with Freight Buses
Authors:

Zheng Chang, Haoxun Chen and Farouk Yalaoui
Abstract: Freight bus is a new public transportation means for city logistics, and each freight bus can deliver and pick up goods at each customer/supplier location it passes. In this paper, we study the route planning problem of freight buses in an urban distribution system. Since each freight bus makes a tour visiting a set of pickup/delivery locations once at every given time interval in each day following a fixed route, the route planning problem can be considered a new variant of periodic vehicle routing problem with pickup and delivery. In order to solve the problem, a Mixed-Integer Linear Programming (MILP) model is formulated. Based on the model, we compare a distribution system with freight buses with that without freight bus. Preliminary numerical results on randomly generated instances show that the system with freight buses can significantly reduce transportation costs compared with the system without freight buses.
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Paper Nr: 31
Title:

An Iterative Request Exchange Mechanism for Carrier Collaboration in Less than Truckload Transportation
Authors:

Xiaohui Lyu, Haoxun Chen and Nengmin Wang
Abstract: In carrier collaboration, multiple carriers form an alliance and exchange some of their transportation requests to improve the overall profit of the alliance and the individual profit of each carrier. In this paper, we propose a mechanism for the request exchange with limited information sharing among the carriers. In each round of the mechanism, each carrier first outsources multiple bundles of requests with the corresponding transfer payments and then insources bundles of requests from other carriers. The auctioneer reassigns bundles of requests among carriers based on the outsourcing bundles and insourcing bundles of requests. The auction mechanism iterates until a certain criterion is met. Numerical experiments on randomly generated instances show that our iterative request exchange mechanism can provide high quality solutions.
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Paper Nr: 38
Title:

Which Tools Are Needed to Assist Audit Managers in Project Portfolio Selection When Divergent Views Emerge?
Authors:

Vivian Vivas and Mónica D. Oliveira
Abstract: In Brazil, government programs differ in terms of territorial coverage, of sectorial action, and vary according to regional contexts. Similarly to other public auditing organizations, the Ministry of Transparency and Comptroller General of the Union (CGU) is responsible for monitoring the application of funds in these government programs as a means to promote transparency and accountability in public spending. In order to fulfil this mission, it is necessary to select the audit projects to be executed by the CGU teams. Several multidisciplinary teams and stakeholders participate in this process of selecting auditing projects across distinct management and public policies themes, with different opinions and views arising. The most important challenges for CGU are to compare the audit projects submitted by these teams on a common and transparent basis (under the presence of scarce resources) and to consider in the selection of projects the divergent and often conflicting perspectives of those involved. In this study, we explore which tools from the multicriteria portfolio decision analysis and negotiation literature can be used to inform a transparent and negotiated selection of audit projects, as well as discuss which type of multicriteria portfolio decision analysis models and features for negotiation should be combined in future research.
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Paper Nr: 43
Title:

Flight Radius Algorithms
Authors:

Assia Kamal Idrissi, Arnaud Malapert and Rémi Jolin
Abstract: In this article, we present the flight radius problem (FRP) on the condensed flight network (CFN). Then, giving a specific flight that is defined by an origin and destination (OD) pair, the problem consists in finding routes that connect the OD pair and satisfy a regret constraint on time, distance or cost. The found routes help airline manager to find business opportunities. This problem arises in the real world, for instance in some air transportation companies. The FRP is formulated as finding a maximal subgraph of nodes belonging to routes satisfying a regret constraint. Such routes can be found using shortest paths algorithms (SPA). The CFN is generated using a time-independent approach and stored in the graph database Neo4j. Implementing SPA in Neo4j is challenging since the graph database stores the weights of the graph in a separate data structure. In this paper, we propose four methods to solve the FRP: these methods combine parallel and sequential processing with more optimization to overcome time and memory costs. The experimental evaluation demonstrates that the best algorithm is the extended Dijkstra algorithm which meets the real-time constraints of the targeted industrial application.
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Paper Nr: 58
Title:

Maximization of Profit for a Problem of Location and Routing, with Price-sensitive Demands
Authors:

Narda E. Ibarra-Delgado, Elias Olivares-Benitez, Samuel Nucamendi-Guillén and Omar G. Rojas
Abstract: This article seeks to study and solve a problem of profit maximization of a company by defining the location of an optimal number of facilities, allocation and routing of vehicles, and costs for home delivery to meet the demand of its customers. This study is based on an article in which, for the first time, a problem of location and routing and maximization of utilities with price-sensitive demands is integrated. This problem, unlike other studies that only minimize other metrics such as waiting times, route distances, and transportation costs, seeks a greater benefit by increasing profits by discriminating prices depending on the customer's location or adding an additional cost to retail sales. This paper presents a model for small instances based on the model proposed in the aforementioned article. Next, a two-phase heuristic is proposed that solves larger instances with a result close to that obtained in the previous article where a branch-and-price heuristic was used.
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Paper Nr: 78
Title:

The Risk-averse Profitable Tour Problem
Authors:

Maria E. Bruni, Lorenzo Brusco, Giuseppe Ielpa and Patrizia Beraldi
Abstract: In this paper, we tackle the risk-averse profitable tour problem with stochastic costs and risk measure objectives. This problem aims at determining a tour that maximizes the collected profit minus the total travel cost under a risk-averse perspective. We explore efficient implementations of a genetic algorithm and a tabu search method to solve the problem when the conditional value at risk and entropic risk measures are used. The computational study shows the superiority of the genetic algorithm over the tabu search on a set of instances adapted from the TSP library.
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Area 2 - Applications

Full Papers
Paper Nr: 1
Title:

Workforce Modelling in Support of Rejuvenation Objectives
Authors:

Etienne Vincent
Abstract: This paper presents a method for measuring the effect of staffing policies toward objectives of workforce rejuvenation. It describes two deterministic models based on the application of rates of personnel flows to workforce segments. The first model works by solving a system of linear equations describing personnel flows to obtain the workforce’s age profile at equilibrium. The second model, by iterating through successive future years, determines the age profile that will result from the set personnel flows. The dynamic model is necessary to identify shorter term effects of staffing policies.
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Paper Nr: 7
Title:

Container Yard Allocation under Uncertainty

Authors:

Yue Wu
Abstract: This paper investigates allocation of space in storage yard to export containers under uncertain shipment information. We define two types of stacks: one is called the dedicated stack and the other is called the shared stack. Since containers meant for the same destination are assigned to dedicated stacks in the same block, no re-handling is required for containers in dedicated stacks. However, containers in shared stacks have different destinations; re-handling is required. We develop a two-stage stochastic recourse programming model for determining an optimal storage strategy, called the dual-response storage strategy. The first-stage response, regarding the allocation of containers to dedicated stacks, is made before accurate shipment information becomes available. The second-stage response, regarding allocation of additional containers to shared stacks, is taken after realization of stochasticity. Then, the unused spaces in the yard area can be released for other purposes. Computational results are provided to demonstrate the effectiveness of the proposed dual-response storage strategy obtained from the stochastic model.
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Paper Nr: 62
Title:

Large Neighborhood Search for Periodic Electric Vehicle Routing Problem
Authors:

Tayeb O. Kouider, Wahiba R. Cherif-Khettaf and Ammar Oulamara
Abstract: In this paper, we address the Periodic Electric Vehicle Routing Problem, named PEVRP. This problem is motivated by a real-life industrial application and it is defined by a planning horizon of several periods typically ”days”, in which each customer has a set of allowed visit days and must be served once in the time horizon. The whole demand of each customer must be fulfilled all together. A limited fleet of electric vehicles is available at the depot. The EVs could be charged during their trips at the depot and in the available external charging stations. The objective of the PEVRP is to minimize the total cost of routing and charging over the time horizon. We propose a Large Neighborhood Search (LNS) framework for solving the PEVRP. Different implementation schemes of the proposed method including customer and station insertion strategies, three destroy operators and three insertion operators are tested on generalized benchmark instances. The computational results show that LNS produces competitive results compared to results obtained in previous studies. An analysis of the performance of the proposed operators is also presented.
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Short Papers
Paper Nr: 3
Title:

Optimising the Services Capacity Operation with Service Supply Chain and Option Theories for Elderly Healthcare Systems in China
Authors:

Jun Zhao and L. K. Chu
Abstract: Traditional elderly healthcare service modes already can hardly meet the rapidly growing demand and high customer expectations. The community-based elderly service mode (CESM), as a new mode merging with the advantages of home-based and institution-based elderly service modes, is not yet widely applied in China. We first analyse the problems of CESM in terms of the government purchase of services (GPS) policy, governance theories and community elderly services coordination management. Then, we conclude the research in the fields of the GPS, community governance and service supply chain coordination, and study the experience of Hong Kong’s community care services system. On the basis, we propose an innovative structure of community-based elderly healthcare service supply chain (EHSSC), and define the connotation of EHSSC and its operational processes. Further, we optimise the operational mode for the EHSSC by using the option contract and service voucher scheme, define the roles and functions of government, community elderly service integrators, community elderly service providers and the elderly in EHSSC. The operation processes of community elderly services capacity are illustrated to systematically address the issues of ‘who participates in’ and ‘how to operate’ in CESM and coordinate the services capacity between the upstream and downstream. Finally, we put forward some constructive suggestions for the implementation of EHSSC with the option contract and service vouchers.
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Paper Nr: 14
Title:

Extended Colored Traveling Salesperson for Modeling Multi-Agent Mission Planning Problems
Authors:

Branko Miloradović, Baran Çürüklü, Mikael Ekström and Alessandro V. Papadopoulos
Abstract: In recent years, multi-agent systems have been widely used in different missions, ranging from underwater to airborne. A mission typically involves a large number of agents and tasks, making it very hard for the human operator to create a good plan. A search for an optimal plan may take too long, and it is hard to make a time estimate of when the planner will finish. A Genetic algorithm based planner is proposed in order to overcome this issue. The contribution of this paper is threefold. First, an Integer Linear Programming (ILP) formulation of a novel Extensive Colored Traveling Salesperson Problem (ECTSP) is given. Second, a new objective function suitable for multi-agent mission planning problems is proposed. Finally, a reparation algorithm to allow usage of common variation operators for ECTSP has been developed.
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Paper Nr: 22
Title:

Project Portfolio Selection Considering Return-risk Evaluation and Multiple-Criteria Decision Analysis
Authors:

Guilherme B. Marcondes
Abstract: Companies often face a challenge when they need to select their projects for execution because the resources are not enough for all of them. For supporting decision, they need to employ some form of selecting the best portfolio to run. There are several proposals in the literature, many allowing an evaluation of efficiency between expected return and risk. However, these proposals indicate a list of efficient portfolios, but not the one best suited for execution. On the other hand, multi-criteria analysis methods allow a more specific indication, but they are difficult to be executed when the number of projects increases. This work seeks to cover this gap by proposing a selection method that combines the return-risk assessment using mean-Gini approach, complemented by the application of the multi-criteria decision method PROMETHEE II. The result is the objective indication of the best project portfolio to be executed by the company.
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Paper Nr: 40
Title:

Smart City Development: A Business Process-centric Conceptualisation
Authors:

Vahid Javidroozi, Hanifa Shah and Gerald Feldman
Abstract: Smart city development has been proposed as a response to urbanisation challenges and changing citizen needs in the cities. It allows the city as a complex system of systems to be efficient and integrated, in order to work as a whole, and provide effective services to citizens through its inter-connected sector. This research attempts to conceptualise smart city, by looking at its requirements and components from a process change perspective, not a merely technology-led innovation within a city. In view of that, the research also gains benefits from the principles of smart city development such as systems thinking approach, city as a system of systems, and the necessity of systems integration. The outcome of this study emphasises the significance of considering a city as a system of systems and necessity of city systems integration and city process change for smart city development. Consequently, the research offers a city process-centric conceptualisation of smart city.
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Paper Nr: 42
Title:

On the Advancement of Project Management through a Flexible Integration of Machine Learning and Operations Research Tools
Authors:

Nikos Kanakaris, Nikos Karacapilidis and Alexis Lazanas
Abstract: Project Management is a complex practice that is associated with a series of challenges to organizations and experts worldwide. Aiming to advance this practice, this paper proposes a hybrid approach that builds on the synergy between contemporary Machine Learning and Operations Research tools. The proposed approach integrates the predictive orientation of Machine Learning techniques with the prescriptive nature of Operations Research algorithms. It can aid the planning, monitoring and execution of common PM tasks such as resource allocation, task assignment, and task duration estimation. The applicability of our approach is demonstrated through two realistic examples.
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Paper Nr: 44
Title:

Risk Analysis of Distributed Generation Scenarios
Authors:

Paula M. Maçaira, Margarete Afonso de Sousa, Reinaldo C. Souza and Fernando C. Oliveira
Abstract: Assertiveness in generation forecast is an important issue for utilities when they are planning their operation. Hydropower Generation forecast has a strong stochastic component and thinking about small hydropower plants (SHP) is even more complex. In recent years, many SHP was installed in Brazil due to a Government incentive and the distributed generation penetration has an impact in technical losses’ estimation. The objective of this study is to propose a methodology to generate synthetic scenarios of distributed generation for hydro sources. A case study was carried on with historical generation data from SHP located in Minas Gerais. The periodic regression model was considered the best model for forecast hydropower generation. Three distributed generation scenarios are obtained using Conditional Value at Risk analysis after combining multiple scenarios from inflow forecasting generated with the periodic regression model.
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Paper Nr: 70
Title:

Market Power in Emissions Trading and Renewable Energy Policy
Authors:

Mari Ito and Ryuta Takashima
Abstract: Policies for reducing greenhouse gas emissions, e.g., cap-and-trade (C&T) as emissions permits trading and renewable portfolio standards (RPS) as renewable energy policies, have recently been introduced in various countries. In this study, we examine market equilibria under C&T and RPS in a bi-level optimization framework. For the lower level, generation of outputs of renewable and non-renewable sectors and electricity prices are decided by maximizing their profits. For the upper level, the policy maker chooses optimal policy level in an attempt to maximize the social welfare. Our results indicate that C&T is the best scheme for both increasing social welfare and reducing greenhouse gas emissions.
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Paper Nr: 76
Title:

A Matheuristic Approach for Resource Scheduling and Design of a Multi-energy System
Authors:

A. Bartolini, G. Comodi, F. Marinelli, A. Pizzuti and R. Rosetti
Abstract: Modern energy system are evolving due to the opportunities and challenges that new technologies pose in the energy sector. These changes create the requirements of decision tools able to effectively sustain the processes of design and retrofit of energy systems. In this paper a multi-energy system management problem is taken into account and a mixed integer linear programming (MILP) formulation is proposed to model both the design and the resource scheduling of energy districts. However, since the size of the formulation restricts its applicability to small cases far from the application of interest, a matheuristic based on constraint relaxations and variable fixing has been designed. Preliminary computational results show that the proposed solution strategy is able to achieve good solutions (i.e., solutions with small optimality gaps) on restricted random instances, and to solve in reasonable times instances derived from a real case study.
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Paper Nr: 2
Title:

Determining Equilibrium Staffing Flows in the Canadian Department of National Defence Public Servant Workforce
Authors:

Etienne Vincent and Stephen Okazawa
Abstract: In large workforces, such as the Public Servant workforce of the Canadian Department of National Defence, many staffing actions (hires, departures, promotions, transfers) are actioned each year. Estimating the number of such actions that will take place in the department’s various units is relevant to the assignment of Human Resource support capacity. The rates at which staffing actions are required is also indicative of the health of workforce occupational segments. This paper presents a method for estimating the number of staffing actions that will be required to maintain a workforce to a state of equilibrium. It also shows how that method was practically implemented in support of Strategic Human Resource Planning for Canada’s Department of National Defence civilian workforce.
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Paper Nr: 20
Title:

Simulation of Vehicle Movements for Planning Construction Logistics Centres
Authors:

Fei Ying, Mike O’Sullivan and Ivo Adan
Abstract: Materials supply is one of important elements in construction operation and a major factor affecting the quality of construction projects. With materials accounting for 60% of the on-site cost of a typical construction project, effective management of this vital resource is essential. Logistics processes, being crucial for successful completion of the project, are often entrusted to external professionals specialized in logistic services, such as logistics centres. However, this tendency is yet to be developed in construction. The purpose of this paper is to examine the potential of managing logistics costs by planning construction logistics centres. The planned centres are then evaluated using vehicle movement simulations. The enclosed results from the simulations indicate that using a logistics centre will have reduced waste for the construction project considered. A literature review and case study analysis are employed, with simulation results using Flexsim. The paper emphasizes that creating a logistics centre for a project at its early stages of planning and then designing an integrated logistics service for that project may help find ways of making the overall construction project more effective by improving management of materials.
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Paper Nr: 41
Title:

Applications of Sparse Modelling and Principle Component Analysis for the Virtual Metrology of Comprehensive Multi-dimensional Quality
Authors:

Sumika Arima, Takuya Nagata, Huizhen Bu and Satsuki Shimada
Abstract: This paper discussed the virtual metrology (VM) modelling of multi-class quality to describe the relationship between the variables of a production machine's condition and the estimated/forecasted product quality soon after finishing the machine processing. Applications of PCA and LASSO technique of the Sparse modelling were introduced to define the multi-dimensional quality. Because the high accuracy and quick computations are required for the VM modelling, in this study, the PCA-LASSO combination was applied before building the VM models based on the kernel SVM (kSVM), particularly the linear kernel for real-time use. As the result of evaluation of a CVD (Chemical vapor deposition) process in an actual semiconductor factory, LASSO and linear-SVM could reduce the scale of the machine variable's set and calculation time by almost 57% and 95% without deterioration of accuracy even without PCA. In addition, as the PCA-LASSO, the multi-dimensional quality was rotated to the orthogonality space by PCA to summarize the extracted variables responding to the primary independent hyperspace. As the result of the PCA-LASSO combination, the scale of machine variables extracted was improved by 83%, besides the accuracy of the linear-SVM is 98%. It is also effective as the pre-process of Partial Least Square (PLS).
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Paper Nr: 50
Title:

Periodic Vehicle Routing Problem in a Health Unit
Authors:

F. Alves, F. Alvelos, A. C. Rocha, Ana I. Pereira and Paulo Leitão
Abstract: In logistics of home health care services in the Health Units, the managers and nurses need to carry out the schedule and the vehicles routes for the provision of care at the patients’ homes. Currently, in Portugal, these services are increasingly used but the problem is still, usually, solved manually and without computational resources. The increased demand for home health care due to the boost of the elderly people number entails a high associated cost which, sometimes, does not guarantee the quality of the service. In this sense, the periodic vehicle routing problem is a generalization of the classical vehicle routing problem in which routes are determined for a time horizon of several days. In this work, it is provided a periodic vehicle routing problem applied in the Health Unit in Bragança. An integer linear programming formulation for the real database, allowed to solve the problem in an efficient and optimized way using the CPLEX R software.
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Paper Nr: 73
Title:

A Multi-objective Approach to the Optimization of Home Care Visits Scheduling
Authors:

Filipe Alves, Lino Costa, Ana C. Rocha, Ana I. Pereira and Paulo Leitão
Abstract: Due to the increasing of life expectancy in the developed countries, the demand for home health care services is growing dramatically. Usually, home services are planned manually and lead to various optimization problems in their activities. In this sense, health units are confronted with appropriate scheduling which may contain multiple, often conflicting, objectives such as minimizing the costs related to the traveling distance while minimizing the traveling time. In order to analyze and discuss different trade-offs between these objectives, it is proposed a multi-objective approach to home health care scheduling in which the problem is solved using the Tchebycheff method and a Genetic algorithm. Different alternative solutions are presented to the decision maker that taking into account his/her preferences chooses the appropriate solution. A problem with real data from a home health care service is solved. The results highlight the importance of a multi-objective approach to optimize and support decision making in home health care services. Moreover, this approach provides efficient and good solutions in a reasonable time.
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