ICORES 2013 Abstracts


Area 1 - Methodologies and Technologies

Full Papers
Paper Nr: 16
Title:

Planning and Control Model for a Forest Supply Chain

Authors:

C. Alayet, N. Lehoux, L. Lebel and M. Bouchard

Abstract: This paper presents a mixed-integer linear program (MILP) for a planning problem of multiple activities in the forest industry. The model developed aims at maximizing the total profit of the value chain by optimizing operations in harvesting, transportation, storage, and production. The main motivations for the model is a need to better account for important factors in planning and control, such as quality, freshness, and species of wood products. These factors have a direct influence on costs and supply decisions. In particular, the model developed will improve forest product companies’ industrial processes by a better control over the wood fibre freshness. Furthermore, our model is designed for a context where multiple independent companies supply their raw material from the same sources. It can therefore be used as a support tool for collaboration between actors in a forest supply chain.
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Paper Nr: 24
Title:

Cyclic-type Polling Models with Preparation Times

Authors:

N. Perel, J. L. Dorsman and M. Vlasiou

Abstract: We consider a system consisting of a server serving in sequence a fixed number of stations. At each station there is an infinite queue of customers that have to undergo a preparation phase before being served. This model is connected to layered queuing networks, to an extension of polling systems, and surprisingly to random graphs. We are interested in the waiting time of the server. The waiting time of the server satisfies a Lindley-type equation of a non-standard form. We give a sufficient condition for the existence of a limiting waiting time distribution in the general case, and assuming preparation times are exponentially distributed, we describe in depth the resulting Markov chain. We provide detailed computations for a special case and extensive numerical results investigating the effect of the system’s parameters to the performance of the server.
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Paper Nr: 26
Title:

A Distributionally Robust Formulation for Stochastic Quadratic Bi-level Programming

Authors:

Pablo Adasme, Abdel Lisser and Chen Wang

Abstract: In this paper, we propose a distributionally robust model for a (0-1) stochastic quadratic bi-level programming problem. To this purpose, we first transform the stochastic bi-level problem into an equivalent deterministic formulation. Then, we use this formulation to derive a bi-level distributionally robust model (Liao, 2011). The latter is accomplished while taking into account the set of all possible distributions for the input random parameters. Finally, we transform both, the deterministic and the distributionally robust models into single level optimization problems (Audet et al., 1997). This allows comparing the optimal solutions of the proposed models. Our preliminary numerical results indicate that slight conservative solutions can be obtained when the number of binary variables in the upper level problem is larger than the number of variables in the follower.
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Paper Nr: 86
Title:

A Hybrid Metaheuristic for the Bus Driver Rostering Problem

Authors:

Vitor Barbosa, Ana Respício and Filipe Alvelos

Abstract: This paper presents a new decomposition model for the Bus Driver Rostering Problem and proposes the hybridization of column generation and genetic algorithms to achieve good quality rosters in short time. The decomposition model is based on the definition of a subproblem for each driver, which is responsible for the creation of valid work-schedules for the rostering period. Column generation is used to obtain an optimal linear solution. This solution and the subproblems’ solutions obtained during the column generation are then used by the genetic algorithm to find good quality combinations of drivers’ schedules, i.e. good quality rosters. Computational tests show the efficiency and effectiveness of the proposed approach.
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Paper Nr: 101
Title:

Hill Climbing versus Genetic Algorithm Optimization in Solving the Examination Timetabling Problem

Authors:

Siti Khatijah Nor Abdul Rahim, Andrzej Bargiela and Rong Qu

Abstract: In this paper, we compare the incorporation of Hill Climbing (HC) and Genetic Algorithm (GA) optimization in our proposed methodology in solving the examination scheduling problem. It is shown that our greedy HC optimization outperforms the GA in all cases when tested on the benchmark datasets. In our implementation, HC consumes more time to execute compared to GA which manages to improve the quality of the initial schedules in a very fast and efficient time. Despite this, since the amount of time taken by HC in producing improved schedules is considered reasonable and it never fails to produce better results, it is suggested that we incorporate the Hill Climbing optimization rather than GA in our work.
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Short Papers
Paper Nr: 19
Title:

A Combinatorial Optimization Approach for the Electrical Energy Management in a Multi-source System

Authors:

Yacine Gaoua, Stéphane Caux and Pierre Lopez

Abstract: Minimizing the consumption of hydrogen by a fuel cell system in a hybrid vehicle can reduce its environmental impact and increase its autonomy. However an intelligent management of power distribution is essential to meet the demand of the powertrain. The characteristics of the sources constituting the energy chain of the hybrid vehicle (efficiency and energy losses) make the mathematical model nonlinear. Solution methods such as Dynamic Programming and Quasi-Newton which have so far been developed in previous works give satisfactory results but with very large computation times. In this paper, a new combinatorial model is proposed and a Branch-and-Cut method is developed to solve the problem to optimality. This approach leads to drastically reduced computation times.
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Paper Nr: 22
Title:

Now or Never? Optimal Introduction Timing for a Product Line Extension with Operational Cost Considerations

Authors:

Shan Li and Zuo-Jun Max Shen

Abstract: Synchronizing marketing and operations decisions is crucial for the success of a firm. We study a problem of determining optimal introduction timing for a line extension product in an integrated inventory (supply) and diffusion (demand) framework. Based on the Bass diffusion model (Bass, 1969), we propose a splitting Bass-like diffusion model to characterize the customer behavior in the adoption of a new product and its line extension variant. The model determines whether and when to introduce the line extension and the corresponding production quantities, while accounting for substitution, diffusion and market segmentation effects. It suggests that the optimal solution existing in the literature becomes suboptimal if operational costs are taken into consideration.

Paper Nr: 25
Title:

Simulating the Repatriation of Canadian Forces Materiel from Afghanistan

Authors:

Bohdan Kaluzny and Raman Pall

Abstract: The Canadian Forces ceased combat operations in the Kandahar province of Afghanistan in 2011 and were instructed by the Government of Canada to complete its redeployment out of Kandahar by the end of December 2011. Materiel and equipment were transported back to Canada over several lines of communications. Nearly 1500 sea containers full of materiel, 800 vehicles, and 200 air pallets of material were returned to Canada by combinations of air, sea, and ground transport. This paper describes a discrete-event simulation model developed to analyze the repatriation of Canadian equipment from Afghanistan to Canada via the applicable lines of communication. The objective was to develop a model that could be used to analyze the repatriation in order to enable and improve future mission planning. The discrete-event simulation model is shown to be representative of the actual repatriation effort and is subsequently used to determine the impacts of different potential courses of action, measured mainly through results on the total cost and duration of the returns.
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Paper Nr: 35
Title:

Continuous-time Revenue Management in Carparks - Part Two: Refining the PDE

Authors:

Andreas Papayiannis, Paul Johnson, Dmitry Yumashev and Peter Duck

Abstract: In this paper, we study optimal revenue management applied to carparks, with the primary objective to maximize revenues under a continuous-time framework. This work is an extension to (Papayiannis et al., 2012) where the authors developed a Partial Differential Equation (PDE) model that could solve for the rate at which cash is generated through an infinitesimal time. However, in practice, carpark managers charge customers per day or per hour which is a finite period of time. Unfortunately, this situation was currently not captured by this previous work. Therefore, our current work attempts to reformulate the existing PDE in a way that it does capture the revenue that is generated within any finite time interval of length DT. The new model is compared against the Monte Carlo (MC) approach for several choices of DT; the results are remarkable as the improvement in computation speed and efficiency are significant. Since, the algorithm in the PDE still does not solve the ‘exact’ problem, a method is proposed to marry the benefits of the PDE with those of the MC approach. Our results are prominent as the optimal values generated in this case have shown to be extremely close to the MC ones while the computation times are kept to a minimum.
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Paper Nr: 45
Title:

Forecasting for Discrete Time Processes based on Causal Band-limited Approximation

Authors:

Nikolai Dokuchaev

Abstract: We study causal dynamic smoothing of discrete time processes via approximation by band-limited discrete time processes. More precisely, a part of the historical path of the underlying process is approximated in Euclidean norm by the trace of a band-limited process. We analyze related optimization problem and obtain some conditions of solvability and uniqueness. An unique extrapolation to future times of the optimal approximating band-limited process can be interpreted as an optimal forecast.
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Paper Nr: 79
Title:

Decision Models as Software Artifacts - Bridging the Business-Software Gap for Decision Support Systems

Authors:

Armando Guarnaschelli, Omar Chiotti and Héctor E. Salomone

Abstract: In this work we introduce a methodology for integrating the development of decision models with model driven software development approaches. This methodology captures the relationships between service oriented architecture software models and decision models by deriving from a common reference model, the data and conceptual elements of both types of models. Using this reference model and through successive model transformations and refinements, the methodology delivers integrated models and implementation models of software aimed to be more resilient to changes in business models. As all software artifacts are connected through a unique reference model, the collaboration with business partners is enabled at all levels by sharing or reusing existent reference models.
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Paper Nr: 90
Title:

Evolutionary Particle Filters: Model-free Object Tracking - Combining Evolution Strategies and Particle Filters

Authors:

Silja Meyer-Nieberg, Erik Kropat and Stefan Pickl

Abstract: Tracking situations or more generally state estimation of dynamic systems arise in various application contexts. Usually the state-evolution equations are assumed to be known up to certain parameters. But what can be done if this is not the case? This paper presents an innovative approach to solve this difficult and complex situation by using the inherent tracking abilities of evolution strategies. Combining principles of particle filters and evolution strategies leads to a new type of algorithms: evolutionary particle filters. Their tracking quality is examined in simulations.
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Paper Nr: 122
Title:

Segmenting and Selecting Cross-sale Prospects using Dynamic Pricing

Authors:

Fredrik Thuring, Jens Perch Nielsen, Montserrat Guillén and Catalina Bolancé

Abstract: In this paper we consider segmentation of a company’s customer data base with respect to the future expected profit, emerging from not yet sold products. We consider a situation where the company is interested in contacting a subset of the customers in the data base to offer additional products. The price at which the products are offered may vary and by utilizing an estimate of the price elasticity of demand, we are able to find closed a form expression of the optimal price as well as the corresponding expected profit, for each customer prospect. We implement the methodology and test it using real data from a major Scandinavian insurance company. We underline that a closed form expression of the optimal price is seldom found in the dynamic pricing literature, suggesting that our pricing formula would be of interest to a broad audience of economists, econometricians, pricing managers and actuaries.
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Paper Nr: 127
Title:

A Fuzzy-stochastic Inventory Model without Backorder under Uncertainty in Customer Demand

Authors:

Pankaj Dutta and Madhukar Nagare

Abstract: In the current business scenario, a vital aspect of a realistic inventory model is to accurately estimate the customer demand especially in uncertain environment. Keeping this fact in mind recent trend of research includes uncertain demand, either random or fuzzy. In this paper, we amalgamate both random behavior and fuzzy perception into the optimization setting in modeling an inventory model without backorder. Treating customer demand as fuzzy random variable, we aim at providing an approach of modeling uncertainty that is closer to real situations. In addition, a distinct characteristic of this study is that the decision maker’s degree of optimism is incorporated in this model using possibilistic mean value approach. The objective is to determine the optimal order quantity associated with cost minimization. An illustrative numerical example is presented to clarify the reality of the model.
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Paper Nr: 17
Title:

A Fluid Limit for the Engset Model - An Application to Retrial Queues

Authors:

Stylianos Georgiadis, Pascal Moyal, Tamás Bérczes and János Sztrik

Abstract: We represent the classical Engset-loss model by the stochastic process counting the number of customers in the system. A fluid limit for this process is established for all the possible values of the various parameters of the system, as the number of servers tends to infinity along with the number of sources. Our results are derived through a semi-martingale decomposition method. A numerical application is provided to illustrate these results. Then, we represent a finite-source retrial queue considering in addition the number of sources in orbit. Finally, we extend the fluid limit results to a retrial queueing system, discussing different cases.
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Paper Nr: 18
Title:

Process Monitoring in Production Systems with Large Diversity of Products

Authors:

José Gomes Requeijo and Adriano Mendonça Souza

Abstract: The main objectives of Statistical Process Control (SPC) are monitoring and analyzing the capability of processes. Traditionally, the analysis of the process capability is performed at the end of Phase 1 (preliminary) and periodically during Phase 2 (monitoring) of the SPC, using the indices Cp and Cpk. SPC and capability analysis of production systems with a large diversity of products present difficulties in implementation. In order to meet the needs required by the current production systems, this paper presents methods for both the statistical control and capability analysis of the processes. These methodologies include two situations, when there are sufficient data to estimate the process parameters (mean, variance) and when it does not exist. In the first case, it is suggested the implementation of control charts Z and W and capability indices ZL and ZU. In the second case, when there is a limited amount of data, the authors suggest the implementation of control charts Q and capability indices QL and QU. The methodologies are illustrated with two case studies, concluding that they allow streamline the statistical control of the various processes and reduce the downside, in Phase 2 of the SPC, where the capability analysis is made only periodically.
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Paper Nr: 31
Title:

A Fuzzy Approach to Risk Analysis in Information Systems

Authors:

Eloy Vicente, Antonio Jiménez and Alfonso Mateos

Abstract: Assets are interrelated in risk analysis methodologies for information systems promoted by international standards. This means that an attack on one asset can be propagated through the network and threaten an organization’s most valuable assets. It is necessary to valuate all assets, the direct and indirect asset dependencies, as well as the probability of threats and the resulting asset degradation. These methodologies do not, however, consider uncertain valuations and use precise values on different scales, usually percentages. Linguistic terms are used by the experts to represent assets values, dependencies and frequency and asset degradation associated with possible threats. Computations are based on the trapezoidal fuzzy numbers associated with these linguistic terms.
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Paper Nr: 57
Title:

Developing Tools for the Team Orienteering Problem - A Simple Genetic Algorithm

Authors:

João Ferreira, José A. Oliveira, Guilherme A. B. Pereira, Luís Dias, Fernando Vieira, João Macedo, Tiago Carção, Tiago Leite and Daniel Murta

Abstract: Presently, the large-scale collection process of selective waste is typically expensive, with low efficiency and moderate effectiveness. Despite the abundance of commercially available software for fleet management, real life managers are only minimally helped by it when dealing with resource and budgetary requirements, scheduling activities, and acquiring resources for their accomplishment within the constraints imposed on them. To overcome these issues, we intend to develop a solution that optimizes the waste collection process by modelling this problem as a vehicle routing problem, in particular as a Team Orienteering Problem (TOP). In the TOP, a vehicle fleet is assigned to visit a set customers, while executing optimized routes that maximize total profit and minimize resources needed. In this work, we propose to solve the TOP using a genetic algorithm, in order to achieve challenging results in comparison to previous work around this subject of study. Our objective is to develop and evaluate a software application that implements a genetic algorithm to solve the TOP. We were able to accomplish the proposed task and achieved interesting results with the computational tests by attaining the best known results in half of the tested instances.
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Paper Nr: 67
Title:

OR-based Eco-efficiency Measuring for Economic-ecological Trade-offs Analysis

Authors:

L. Lauwers and J. Van Meensel

Abstract: Traditional eco-efficiency measurements insufficiently support trade-offs analysis. The objective of the paper is to explore trade-offs analysis support from the branch of productive efficiency analysis techniques. The paper focuses on the linear programming based data envelopment analysis (DEA) models, adjusted for an analogous treatment of the economic and environmental outcomes. In particular, the models are adjusted for the materials balance principle. They allow for differentiating between win-win and trade-offs while substituting for inputs or outputs. Their results are obvious for simple production processes, but the message gets blurred with multiple inputs, outputs and outcomes. The paper explores multiple economic-ecological trade-offs with materials-balance-based efficiency DEA models with a simple illustrative case of 62 typical pig firms. Separate DEA models calculate technical, economic and the efficiency for nutrient, water and energy use. Mutual win-wins and trade-offs are shown. Shortcomings are discussed and further model adjustments based on directional distance functions, instead of radial ones, are proposed.
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Paper Nr: 69
Title:

Supply Chain Risk Assessment Applying System Dynamics Approach - Case Study: Apparel Industry

Authors:

Marzieh Mehrjoo and Zbigniew J. Pasek

Abstract: A remarkable increase in the demand and supply uncertainty, as the primary sources of supply chain risk and other sources such as: capacity constraints, supply variability, parts quality problems, long lead times, war and natural disasters have increased the necessity of assessing and managing the risk in the supply chain. The purpose of this study is to investigate the impact of two categories of risk, demand uncertainty and delays, on the performance of an apparel supply chain. A system dynamics approach was used to study the behavior and relationships within the supply chain of this industry. The proposed model facilitates the study and identification of the critical components of the supply chain. In addition, the model provides a tool to generate multiple business scenarios for effective decision making.
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Area 2 - Applications

Full Papers
Paper Nr: 9
Title:

Course Opening, Assignment and Timetabling with Student Preferences

Authors:

Sacha Varone and David Schindl

Abstract: We consider the following problem of course scheduling and assignment of students. Students express their preferences for each course from several sets of proposed courses and each student has to take a certain number of courses from each set. A minimum number of students is required to open a course and a maximum number of students is specified for each course. The courses have to be scheduled on a limited number of periods so that simultaneous courses have no students in common. This problem can be seen as a generalization of the Student Project Allocation problem. It consists in determining which courses to open, specifying the schedule for these opened courses, and assigning students to them, so that their preferences are maximized. Our model is an Integer Programming problem, which we solve with a common available solver using an iterative process.
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Paper Nr: 10
Title:

Management of Emergency Response Teams under Stochastic Demands

Authors:

Iliya Markov and Sacha Varone

Abstract: We propose a stochastic optimization model for the composition of emergency response teams. An emergency intervention requires first an evaluation of the situation which results in the need of different skills. People involved in the response team must therefore comply with the required skills, be available, with a past and future workload respecting contractual compliance. In addition, we must also anticipate the possibility of future interventions that will require rare skills. It is the uncertain future demand for these skills that introduces stochasticities to the system. Since shifting agents between emergencies may be impossible or impractical, we would like to ensure that rare skills are not wasted but assigned to the emergency that most needs them. We model this with a mixed integer linear program implemented in AMPL and capable of being solved in real-time on common solvers.
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Paper Nr: 29
Title:

Multi-start Approach for Solving an Asymmetric Heterogeneous Vehicle Routing Problem in a Real Urban Context

Authors:

José Cáceres-Cruz, Daniel Riera, Roman Buil, Angel A. Juan and Rosa Herrero

Abstract: Urban transportation is a strategic domain that has become an important issue for client satisfaction in distribution companies. In academic literature, this problem is categorized as a Vehicle Routing Problem, a popular research stream that has undergone significant theoretical advances but has remained far from practice implementations. Most Vehicle Routing Problems usually assume homogenous fleets, that is, all vehicles are considered of the same type and size. In reality, this is usually not the case as most companies use different types of trucks to distribute their products. Also, researchers consider symmetric distances between customers. However, in intra-urban distribution it is more appropriate to consider asymmetric costs. In this study, we address the Heterogeneous Fixed Fleet Vehicle Routing Problem with some additional constraints: (a) Asymmetric Cost matrix, (b) Service Times and (c) Routes Length restrictions. Our objective function is to reduce the total routing costs. We present an approach using a multi-start algorithm that combines a randomized Clarke & Wright’s Savings heuristic and a local search procedure. We execute our algorithm with data from a company that distributes food to more than 50 customers in Barcelona. The results reveal promising improvements when compared to an approximation of the company’s route planning.
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Paper Nr: 38
Title:

The Pareto Frontier for Vehicle Fleet Purchases - Cost versus Sustainability

Authors:

Daniel Reich, Sandra L. Winkler and Erica Klampfl

Abstract: Vehicle fleets for large corporations can have thousands of vehicles that are replaced between every few months and every few years. With the emergence of hybrid, plug-in hybrid, and other new vehicle technologies, combined with an increasing focus on sustainability, planning fleet purchases has and continues to become a significantly more complicated undertaking. This paper introduces Ford’s Fleet Purchase Planner system designed to present fleet customers with optimal purchase strategies that incorporate their companies’ cost and sustainability considerations.
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Paper Nr: 51
Title:

A Maintenance-optimal Swapping Policy - For a Fleet of Electric or Hybrid-electric Vehicles

Authors:

Ahmad Almuhtady, Seungchul Lee, Edwin Romeijn and Jun Ni

Abstract: Motivated by high oil prices, several large fleet companies initiated future plans to hybridize their fleets to establish immunity for their optimized business models against severe oil price fluctuations, and adhere to increasing awareness of environmentally-friendly solutions. The hybridization projects increased maintenance costs especially for highly costly and degradable components such as Li-ion batteries. This paper introduces a degradation-based resource allocation policy to optimally utilize batteries on fleet level. The policy, denoted as Degradation-based Optimal Swapping Policy, incorporates optimal implementation of swapping and substitution actions throughout a plan of finite time horizon to minimize projected maintenance costs. The swapping action refers to the inter-change in the placement of two batteries within a fleet. The substitution action refers to the replacement of degraded batteries with new ones. The policy takes advantage of the different degradation rates in the batteries health states; due to different loading conditions; achieving optimal placement at different time intervals throughout the plan horizon. A mathematical model for the policy is provided. The optimization of the generated model is studied through several algorithms. Numerical results for sample problems are shown to illustrate the capability of the proposed policy in establishing substantial savings in the projected maintenance costs compared to other policies.
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Paper Nr: 81
Title:

The Package Server Location Problem

Authors:

Arnaud Malapert, Jean-Charles Régin and Jean Parpaillon

Abstract: In this paper, we introduce a new multi-objective optimization problem derived from a real-world application: the package server location problem. A number of package servers are to be located at nodes of a network. Demand for these package servers is located at each node, and a subset of nodes are to be chosen to locate one or more package servers. Each client is statically associated to a package server. The objective is to minimize the number of package servers while maximizing the efficiency and the reliability of the broadcast of packages to clients. These objectives are contradictory: the broadcast becomes more efficient as the number of servers increases. This problem is analyzed as a multi-objective optimization problem and a mathematical formulation is proposed. In addition, the criteria combination can be specified via a small dedicated language. Results for exact multi-objective solution approaches based on mixed integer linear programming are reported.
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Paper Nr: 95
Title:

Faustmann Optimal Pine Stands Stochastic Rotation Problem

Authors:

Eduardo Navarrete and Jaime Bustos

Abstract: The Faustmann optimal rotation harvesting pine stands models under Logistic and Gompertz wood stock and Brown price stochastic diffusion processes are reformulated as stochastic one dimensional optimal stopping problem, which are solvable with the Hamilton-Jacobi-Bellman equations. The stochastic models predict a significant increase of the deterministic optimal cut, with 47.0% and 48.0% in the cases of the Logistical and Gompertz wood stock diffusion respectively. The application of these models to a Chilean forest company shows discrepancies due to the absence of consideration to wood stock and price uncertainties that the company actual cut policy shows. The experimental data significantly validate the Faustmann stochastic logistic model. They give a better approximation of the company cut policy, underestimating it by 8.09% and producing a more reliable saturation volume than the Gompertz model. The sensitivity analysis shows that both volatilities have a similar linear effect in the optimal cut, but the wood stock volatility volume elasticity of 0.687 almost doubles the stumpage price volume elasticity of 0.350, showing the importance of this uncertainty.
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Paper Nr: 118
Title:

Evaluation of Efficiency of Brazilian Airlines using the MCDEA-TRIMAP Model

Authors:

Eliane Ribeiro Pereira, Maria Cecília de Carvalho Chaves and João Carlos C. B. Soares de Mello

Abstract: The deregulation of the domestic airline industry brought a significant increase in competition between airlines, pushing them to continuously update their strategies. This article reviews the operating performance of these companies, from the contrast in the results of the DEA classic model and MCDEA-TRIMAP efficiency indicators. The use of such methodology allows the increase of discriminatory power of the productive units evaluated and a better evaluation of them. The application of the DEA model to the data from the Brazilian Airline industry for the year 2008 indicated three companies as efficient, while the use of MCDEA TRIMAP index allowed the identification of the most efficient company in 2008. The index provided better discrimination of the production units in the study.
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Short Papers
Paper Nr: 15
Title:

A Discrete Time Valuation of Callable Financial Securities with Regime Switches

Authors:

Kimitoshi Sato and Katsushige Sawaki

Abstract: In this paper, we consider a model of valuing callable financial securities when the underlying asset price dynamic is modeled by a regime switching process. The callable securities enable both an issuer and an investor to exercise their rights to call. We show that such a model can be formulated as a coupled stochastic game for the optimal stopping problem with two sopping boundaries. We provide analytical results of optimal stopping rules of the issuer and the investor under general payoff functions defined on the underlying asset price, the state of the economy and the time. In particular, we derive specific stopping boundaries for the both players by specifying for the callable securities to be the callable American call and put options. Also, numerical examples are presented to investigate the impact of parameters on the value function as well as on the optimal stopping rules.
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Paper Nr: 32
Title:

A Linearization Approach for Project Selection with Interdependencies in Resource Costs

Authors:

Ali Shafahi and Ali Haghani

Abstract: In this paper a new formulation is proposed for project selection problem which considers project interdependencies. Project interdependencies are factored in using the learning curve concept. The problem is modeled as a Mixed Integer Program (MIP) with quadratic constraints. To solve the problem the quadratic constraints are linearized using a new method proposed in this paper and the benefits of this approach compared to the conventional methods are emphasized. The application of this methodology is illustrated using a numerical example. The result shows the superiority of this method in reducing the number of variables dramatically.
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Paper Nr: 55
Title:

Evidence for the Relationship between Pilot Effectiveness, Surface Anomalies, and Operational Efficiency Data

Authors:

Daniel Howell and Sherry Borener

Abstract: To justify an investment in a safety-related program, the U.S. Federal Aviation Administration must develop a business justification with a positive return on investment. While the assumed value of an avoided aviation accident is quite large, the rarity of such events many times makes a business case built strictly on safety metrics untenable. It is therefore helpful to examine if there are efficiency or capacity impacts related to the investment. One area of interest to the aviation safety community is fatigue and pilot effectiveness. Previous research has examined the connection between operator fatigue and accident frequency. In this study, we examine the relationships between pilot effectiveness, measured surface anomalies, and archived operational efficiency data at Atlanta Hartsfield-Jackson International Airport and Memphis International Airport to provide evidence to support future taxi path conformance or crew rest requirement investments.
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Paper Nr: 61
Title:

An Empirical Comparison of DEA and SFA Method to Measure Hospital Units’ Efficiency

Authors:

George Katharakis, Maria Katharaki and Theofanis Katostaras

Abstract: Although frontier techniques have been used to measure healthcare efficiency, their utility in decision making process is limited by both methodological questions concerning their application. The present paper aims to examine the data envelopment analysis (DEA) and stochastic frontier analysis (SFA) results in order to facilitate a common understanding about the adequacy of these methods. A two-stage bootstrap DEA method and the Translog formula of the SFA were performed. Multi-inputs and multi-outputs were used in both of the approaches assuming two scenarios either including environmental variables or not. Thirty-two Greek public hospital units constitute the sample. The main output of the analysis was that the efficiency scores increased with the incorporation of environmental variables. Moreover, environmental variables being hospital status and geographical position were found significantly correlating with inefficiency, while patient mobility was not found strongly correlating. DEA and SFA were found to yield divergent efficiency estimates due to the nature of the environmental variables and the measurement error. The analysis concludes that there is a need for careful attention by stakeholders since the nature of the data and its availability influence the measurement of the efficiency and thus it is necessary to be specific when choosing the mathematical form.
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Paper Nr: 66
Title:

A New Approach to Prevent Deadlock in S3PR Nets with Unreplicable Resources

Authors:

Asaftei Timotei and José-Manuel Colom

Abstract: Deadlock prevention in Resource Allocation Systems with shared resources represents an important goal in systems design. When using Petri net based modeling, typical methods for attaining this goal use syphon analysis. This paper develops a new method to prevent deadlock in S3PR nets based on minimal siphons and Pruning Graphs. The method consists in two steps: first is the increasing of the number of copies of a replicable resource and second is the splitting of the total copies of the replicable resources. We use the Pruning Graph to choose the replicable resources we are going to split. The algorithm uses only structural information of the net and a simple example is used to illustrate its application.
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Paper Nr: 70
Title:

Optimal Staffing Policy - A Service System with Stochastic Travel Times

Authors:

M. Al-Foraih, P. Johnson, G. Evatt and P. Duck

Abstract: Private sector operators of response services such as ambulance, fire or police etc. are often regulated by targets on the distribution of response times. This may result in inefficient overstaffing to ensure those targets are met. In this paper, we use a network chain of M=M=K queues to model the arrival and completion of jobs on the system so that quantities such as the expected total time waiting for all jobs can be calculated. The Markov nature enables us to evoke the Hamilton Jacobi Bellman equation (HJB) principle to optimize the required number of staff whilst still meeting targets.
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Paper Nr: 71
Title:

Three Dimensional Packing Algorithm with Consideration of Loading and Unloading Order

Authors:

Naoki Kobatake, Hidenori Ohta and Mario Nakamori

Abstract: A novel packing problem for truck or containership transportation is considered. A truck or a ship visits several accumulation places in a delivery tour, and items are loaded or unloaded at each accumulation place. In order to carry items as many as possible at one delivery tour, we often have to unpack and repack some items even at nondestination places if they blockade loading other items. Such packing and repacking, however, will make the transportation cost increase. Thus, a packing that requirs smaller number of unpacking and repacking is desired. In this paper, we extend the slicing-tree which is a method of a representation of packing and propose an algorithm to pack items into the container with minimum the number of unpacking and re-packing.
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Paper Nr: 74
Title:

Comparison of Two Fuzzy Multi Criteria Decision Methods for Potential Airport Location Selection

Authors:

Sedat Belbag, Muhammet Deveci and Ahmet Serhat Uludag

Abstract: Facility location selection is a very important multi criteria decision problem for many companies. As other strategic decisions, any failure in facility location selection has also irreversible consequences that affect the future of a company. Multi criteria decision methods (MCDM) are widely used in comparison related problems. These methodologies give more obvious and rational solutions in decision process. This study is proposed fuzzy TOPSIS and fuzzy ELECTRE I to overcome facility location selection problem. We combine fuzzy sets theory with two different multi criteria decision methods to eliminate the vagueness of linguistic factors that stem from the uncertain and imprecise assessment of decision-makers. The proposed methods have been applied to a facility location selection problem that determines a potential second airport in Ankara, Turkey.
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Paper Nr: 88
Title:

An Efficient Implementation of a Static Move Descriptor-based Local Search Heuristic

Authors:

Onne Beek, Birger Raa and Wout Dullaert

Abstract: The Vehicle Routing Problem is a well-studied problem. Since its formulation in 1959, a great number of powerful solution methods have been designed. However, for large scale problems, few techniques are able to consistently find good solutions within an acceptable time limit. In this paper, the concept of Static Move Descriptors, a recently published technique for speeding up Local Search algorithms, is analyzed and an efficient implementation is suggested. We describe several changes that significantly improve the performance of an SMD-based Local Search algorithm. The result is an efficient and flexible technique that can easily be adapted to different metaheuristics and can be combined with other complexity reduction strategies.
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Paper Nr: 93
Title:

Stochastic Optimization Model of Fuel Procurement, Transportation and Storage for Coal-Fired Thermal Plants in Hydrothermal Systems

Authors:

A. Dias, R. Kelman, F. Thomé, M. Pereira, S. Binato, E. Faria and G. Ayala

Abstract: This work presents an optimal strategy of coal procurement for thermal plants, including transportation and storage in order to guarantee continuous supply of the fuel. The stochastic programming model developed takes into account the uncertainty associated with inflows in a hydrothermal system and other complex logistics and commercial aspects related to the international coal market. Different study cases are analysed and the results are presented through comparisons of different strategies applied to different scenarios of dispatch.
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Paper Nr: 106
Title:

Lagrangian Road Pricing

Authors:

Vianney Boeuf and Sébastien Blandin

Abstract: We consider the problem of trajectory-based road pricing with the objective of reducing congestion on a road network. It is well-known that traffic conditions resulting from typical non-cooperative behavior of selfish drivers do not minimize total travel time spent on the road network. In the context of real-time GPS data collection from all vehicles, drivers can be charged differently based on their origin and destination, and according to the path they take from that origin to that destination. In this work, we propose a new formulation of the set of multi-commodity prices based on a price potential, and describe an efficient algorithm to construct such multi-commodity prices. We provide an analysis of the subset of valid prices satisfying several specific user-driven constraints. The numerical performances of the method proposed are assessed on a benchmark network, and the social benefits resulting from the commodity-based potential pricing scheme introduced in this article are discussed.
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Paper Nr: 123
Title:

Linear Programming Formulation of the Elevator Trip Origin-destination Matrix Estimation Problem

Authors:

Juha-Matti Kuusinen, Mirko Ruokokoski, Janne Sorsa and Marja-Liisa Siikonen

Abstract: Elevator group control dispatches elevators to passengers’ calls in a dynamic environment where new calls constantly emerge. At the moment of making a dispatching decision, it is not known when and at which floors new passengers will register new calls, what is the number of passengers waiting behind these and existing calls, and what are their destinations. Robust dispatching decisions require that future passenger traffic is forecast based on the realized passenger flow in a building. The problem is that this flow cannot be directly measured. It can, however, be estimated by finding the passenger counts for the origins and destinations of every elevator trip occurring in a building. An elevator trip consists of successive stops in one direction of travel with passengers inside the elevator. We formulate the elevator trip origin-destination matrix estimation problem as a minimum cost network flow problem. We also present a branch-and-bound algorithm for finding all solutions to the problem and study its performance based on numerical experiments.
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Paper Nr: 129
Title:

Job Order Assignment at Optimal Costs in Railway Maintenance

Authors:

Franziska Heinicke, Axel Simroth, Roberto Tadei and Mauro M. Baldi

Abstract: Tamping is an important part of railway maintenance. Well tamped ballast reduces track irregularities and increases travel safety and comfort. But if the ballast is in a bad condition, the train speed must be restricted, which leads to delays and penalty costs for the operator. In this paper a novel model for the tamping scheduling problem in a short-term planning horizon is presented. In contrast to other railway maintenance scheduling problems the penalty costs caused by deferring tamping activities are considered in the scheduling process beside the travel costs. Three greedy heuristics are presented and compared in different benchmarks. An outlook discusses issues of interest for further research.
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Paper Nr: 59
Title:

Telescope Network Scheduling - Rationale and Formalisms

Authors:

Sotiria Lampoudi and Eric Saunders

Abstract: Scheduling of university and institutional telescopes is typically performed manually, and astronomers are used to interacting with a human to explain their requirements for resources and time. Las Cumbres Observatory Global Telescope (LCOGT) is deploying a worldwide network of robotic telescopes. At LCOGT manual scheduling is infeasible due to: 1) the number of resources and observations that must be scheduled, 2) the scheduling-time dependencies that arise when concurrent or consecutive access to telescopes is required, and 3) the need to rapidly re-calculate the schedule to accommodate near-real-time requests from high priority observing programmes (e.g. transient followup programmes), and changing resource availability due to weather and other reasons. In this paper we develop a formalism capable of expressing the complex requirements and preferences of astronomers concerning resource and time allocation on a telescope network, and formulate the offline telescope network scheduling problem as the problem of choosing and scheduling (i.e. assigning concrete start and end times to) a maximum priority, non-overlapping subset of an input list of requests.
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Paper Nr: 65
Title:

Enforcing Liveness in S3PR Nets by Specialization of Resources

Authors:

Asaftei Timotei and José-Manuel Colom

Abstract: Siphon-based control methods are often used in deadlock prevention in Petri nets models for resource allocation systems caused by the shared resources. In this article we used the properties of the minimal siphons of the S3PR and Pruning Graph to develop a new method to prevent the deadlock. This method consists in the increasing of the number of copies of a given resource type, and in the splitting of the total copies of resources in two new types of resources that will be used in a private way for each one of the two disjoint groups in which the old holder places of the original resource type are divided. The algorithm uses only structural information of the net.
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Paper Nr: 73
Title:

Equivalence between Two Flowshop Problems - MaxPlus Approach

Authors:

Nhat Vinh Vo and Christophe Lenté

Abstract: In this paper, a flowshop problem with minimal and maximal delays, setup and removal times is tackled. It is shown that this problem is equivalent to another flowshop problem with only minimal and maximal delays, which can be seen as a central problem. The proof is done using an algebraic way which allows to identify the role of each constraint, once the modeling is performed.
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Paper Nr: 76
Title:

Scheduling with Tool Switching in Flexible Manufacturing Systems

Authors:

Selin Özpeynirci and Burak Gökgür

Abstract: In our problem, there are a number of jobs to be processed on parallel computer numerically controlled machines. Each job requires a set of tools and the required tools must be loaded to process the jobs. The machines have limited tool magazine capacities and the number of tools available in the system is limited due to economic restrictions, which leads to the need for switching tools. We assume that the tool switching time constitutes a significant portion of total processing time and does not depend on the number or type of tools changed. The problem is to assign the jobs and the required tools to machines and determine the schedule so that the makespan is minimized. A mathematical model and a heuristic approach based on the decomposition of the problem are developed.
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Paper Nr: 98
Title:

Assessment of Operational Risks Associated to New Product Development - An Application using a Bayesian Networks Method

Authors:

Tito Armando Rossi Filho, Guilherme Luis Roehe Vaccaro and José Antônio Valle Antunes Junior

Abstract: This work presents an application of a method for assessing the operational risks associated to the development of new products, aiming to address the uncertainties of technical and managerial risks. The method has been developed using the Design Research approach, which enabled the development of a set of artifacts linked through six steps, where the main artifact is a Bayesian Network model. The performance evaluation of the application was carried out by a tentative application in a new product being developed at a design center of a global company, where the main focus was to assess the risks associated with reliability failures. This research, besides contributing with a proposal of an application to support the new product risk management, indicates potential enhancements to the decision making process, and to the knowledge management in project environments.
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Paper Nr: 105
Title:

A Predictive-Reactive Dynamic Scheduling under Projects’ Resource Constraints for Construction Equipment

Authors:

Mona Asudegi and Ali Haghani

Abstract: Major portion of projects’ cost is dedicated to construction equipment’s costs which signify the importance of employing optimal equipment’s schedules in projects. In this paper the problem of construction equipment scheduling for a company with several ongoing projects in different regions is studied. The goal is scheduling heavy construction equipment and their assignments to jobs so that the total cost for the company and disruptions in projects’ schedules is minimized while considering the priorities and critical paths of the projects. A robust predictive-reactive integer model with a hybrid dynamic approach is employed in modeling the problem. Case studies showed considerable savings in cost and minimizing disruption in schedules in real time.
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Paper Nr: 107
Title:

Decision Support System with Mark-Giving Method

Authors:

Otilija Sedlak, Marija Cileg and Tibor Kis

Abstract: Just as in many other areas, strategic management makes use of mathematical modelling in cases such as setting strategic goals, formulation of strategies, selection and realization of the chosen strategy, and strategic control. Criteria and restrictions of alternatives are also encompassed in the space of uncertainty and indeterminacy. They have multiple meanings, in addition to being incomplete and fuzzy. The ordering method is based on the assessment, i.e. mark-giving method used by teachers in education. Values of criteria are treated as fuzzy sets, given as marks. It can be easy programmed by fuzzy logic software.
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Paper Nr: 125
Title:

The Impact the Price Promotion Has on the Manufacturer’s Performance

Authors:

Wenting Pan, Yung-Jae Lee and Tina Zhang

Abstract: We consider a supply chain network where there is one manufacturer and multiple identical retailers in a consumer non-durable market. The retail purchase price is exogenous, and demand is deterministic. The retailers apply the Economic Order Quantity (EOQ) model to minimize the total cost. In observation of the manufacturer’s periodic instantaneous promotion, the retailers would place a one-time order from the manufacturer to take advantage of the deal during the promotion period. The objective of this paper is to examine the impact this price promotion has on the manufacturer’s performance. We find that this promotion policy has a negative impact on the manufacturer’s performance. Interestingly, we also find that this negative impact is less damaging when the utilization of the facility is lower.
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