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Meetings 2012-2013

  • June 2013, Monday 24 (02:00 pm): Gilbert Laporte (Canada Research Chair in Distribution Management, HEC Montréal)

    Minimizing Greenhouse Emissions in Vehicle Routing :

    The Vehicle Routing Problem holds a central place in distribution management. In the classical version of the problem the aim is to distribute goods to a set of geographically dispersed customers under a cost minimization objective and various side constraints. In recent years a number of researchers have started investigating the joint minimization of cost and greenhouse emissions in vehicle routing, giving rise to the so-called "Pollution-Routing Problem". Whereas cost depends primarily on distance travelled, emissions are a function of distance, vehicle load, speed and a variety of other factors. The aim of this talk is to describe recent research results in this context.

    About the speaker: Gilbert Laporte, Ph.D., MSRC
    CIRRELT and Canada Research Chair in Distribution Management -HEC Montréal
    Canada Research Chair: http://www.hec.ca/chairedistributique
    Bio sketch
    Google Scholar profile
    E-mail: Gilbert.Laporte@cirrelt.ca
    Where: HEC-Management School of the University of Liege - 14, rue Louvrex (N1)- 4000 Liège

  • June 2013, Thursday 13 (09:30 am): Thierry Pironet (University of Liège)

    Stochastic Optimization in Multi-Periods Transportation Problems

    Transportation problems are usually formalized as independent single period deterministic models (VRP-PDP) while they are mostly stochastic, subsequent and multi-periods in nature even if the decision process is daily performed. Some on-line, time-dependent, periodic or dynamic settings are now addressed requiring some distinctions among themselves. On the other hand, stochastic optimization techniques such as stochastic programming allow us to tackle some ranges of problems (2 or multi stages problems, continuous variables, convex recourse function, continuous distribution law), yet if we consider reality such as a rolling horizon problem with integer-binary variables and highly discrete distribution law there is still a gap to fill in optimization techniques. Transportation problems often belongs to this family of here or there, yes or no, now-tomorrow or never decision problems. So, our first aim is to show the economic benefit for a company to deal with the approximated multi-periods stochastic model instead of its deterministic mono-period caricature. The second aim is to provide a methodological procedure and a toolbox of algorithms to deal with the hard stochastic optimization and its numerical statistical validation. Finally, we discuss the robustness of the procedures when the distribution law is different from the expected one.

    Where: HEC-Management School of the University of Liege - 14, rue Louvrex (N1, room 334)- 4000 Liège
  • March 2013, Monday 11 (09:30 am): Prof. José F. Oliveira (University of Porto, Portugal)

    2D Rectangular Cutting and Packing Problems: all the same or all different?

    There are many optimization problems dealing with the cutting of rectangles from larger rectangular pieces. These problems appear in literature, but under a very diverse set of names. Designations as, for instance, cutting stock, bin packing, rectangular packing, rectangular cutting, pallet loading, are common. Sometimes the same designation is even used for obviously different problems. But do these designations really correspond to different problems, in the sense that they must be solved with different resolution approaches? In this talk we will go through the different 2D rectangular cutting and packing problems, highlighting the differences among several classes of problems and exemplifying some resolution approaches, both (meta)heuristic and exact. Some conclusions about the computational experiments and test instances used in those experiments will also be drawn.

    Where: HEC-Management School of the University of Liege - 14, rue Louvrex (N1, room 035)- 4000 Liège

  • February 2013, Monday 25 (11:30 am): Julien Hambuckers (HEC-ULg).

    New issues for the goodness-of-fit tests of the error distribution in Finance : a comparison between Sinh-arcsinh and Generalized Hyperbolic distributions

    Since 2008, the financial crisis shows the limits of the current risk models, in particular for Value-at-Risk (VaR) predictions. In this article, we consider a multiplicative heteroskedastic structure of fiancial returns and we propose a non-conventional methodology to study new issues concerning the goodness-of-fit tests of the error distribution in finance. More precisely, we use different estimation and model selection procedures (Berk-Jones (1978) tests, Sarno and Valente (2004) hypothesis testing, Diks et al. (2011) weighting method), based on the local adaptive volatility estimator (LAVE) of Mercurio and Spokoiny (2004) and the bootstrap methodology, to solve the problem of heteroskedasticity and to compare the fit performances of candidate density functions with a focus on the tail. In particular, we introduce the sinh-arcsinh (SHASH) distributions (Jones and Pewsey, 2009) and we show that this family of density functions provides better bootstrap version of the integrated mean squared error (IMSE) and better weighted Kullback-Leibler distances than the HYP and NIG density functions, on five stock indexes datasets, indicating that the SHASH functions are suitable candidates for VaR models.
    Joint work with C. Heuchenne.

    Where: HEC-Management School of the University of Liege - 14, rue Louvrex (N1, room 315)- 4000 Liège

  • January 2013, Monday 21(02:00 pm): Prof. Jean-Sébastien Tancrez from Louvain School of Management (Université catholique de Louvain).

    A location-inventory model for large three-level supply chains

    We study the location-inventory problem in three-level supply networks. Our model integrates three decisions: the distribution centers location, flows allocation, and shipment sizes. We propose a nonlinear continuous formulation, including transportation, fixed, handling and holding costs, which decomposes into a closed-form equation and a linear program when the DC flows are fixed. We thus develop an iterative heuristic that estimates the DC flows a priori, solves the linear program, and then improves the DC flow estimations. Extensive numerical experiments show that the approach can design large supply networks both effectively and efficiently, and a case study is discussed.
    Joint work with Jean-Charles Lange and Pierre Semal.

    Where: HEC-Management School of the University of Liege - 14, rue Louvrex (N1, room 311)- 4000 Liège

  • December 2012, Tuesday 11 (10:30 am): Prof. dr. Kenneth Sörensen (University of Antwerp)

    Metaheuristics - the metaphor exposed

    In recent years, the field of combinatorial optimization has witnessed a true tsunami of "novel" metaheuristic methods, most of them based on a metaphor of some natural or man-made process. The behavior of virtually any species of insects, the flow of water, musicians playing together --- it seems that no idea is too far-fetched to serve as inspiration to launch yet another metaheuristic. In this talk we will argue that this line of research is threatening to lead the area of metaheuristics away from scientific rigour. We will examine the historical context that gave rise to the increasing use of metaphors as inspiration and justification for the development of new methods, discuss the reasons for the vulnerability of the metaheuristics field to this line of research, and point out its fallacies. At the same time, truly innovative research of high quality is being performed as well. We conclude the talk by discussing some of the properties of this research and by pointing out some of the most promising research avenues for the field of metaheuristics.

    Where: HEC-Management School of the University of Liege - 14, rue Louvrex (N1, room 311)- 4000 Liège

  • November 2012, Tuesday 27 (10:30am): Dr. Alper Döyen (HEC-ULg)

    Disaster Mitigation and Humanitarian Relief Logistics

    We are interested in two distinct problems within the disaster management context. These problems are modeled as two-stage stochastic integer programs since stochasticity is inherent in natural disasters. First, we consider a humanitarian relief logistics model which can be used as a pre-disaster planning tool that also considers post-disaster decisions to give an effective response aftermath an earthquake. In this model, decisions are made for location of pre- and post-disaster rescue centers, the amount of relief items to be stocked at the pre-disaster rescue centers, the amount of relief item flows at each echelon, and the amount of relief item shortage. The objective is to minimize the total cost of facility location, inventory holding, transportation, and shortage. Since building and transportation network retrofitting decisions influence the pre-disaster planning of post-disaster response decisions, we propose an integrated model that includes these retrofitting decisions as well. Model seeks to minimize the total cost of retrofitting, transportation and relief item shortage under a limited mitigation budget, which is allocated efficiently among the retrofitting alternatives. The amount of relief item demand is a decision variable that is determined according to the post-disaster damage of buildings. The deterministic equivalents of both models are mixed-integer linear programming models and they are solved by Lagrangean heuristic methods. Results on randomly generated test instances show that the proposed solution methods for both models exhibit good performance under different parameter settings. In addition, various analyses are carried out to clearly understand the model behavior and to validate the incorporation of uncertainty.

    Where: HEC-Management School of the University of Liege - 14, rue Louvrex (N1, room 311)- 4000 Liège

  • November 2012, Tuesday 20(10:30am): Pr. Mario Cools (University of Liege)

    Calibration opportunities for activity-based travel demand models predicting passenger transport

    In the field of passenger demand modeling, activity-based travel demand models are often cited as state-of-the-art models. Having many advantages over classical methods, one of the difficulties of this “new” type of models is the matching of model outcomes with traffic counts observed on the network. This presentation will focus on some of the calibration opportunities in this regard, and will also formulate a critical note to these state-of-the-art models.

    Where: HEC-Management School of the University of Liege - 14, rue Louvrex (N1, room 138)- 4000 Liège

  • November 2012, Tuesday 13 (10:30am): Bruno F. Santos (University of Coimbra, Portugal)

    Optimization approaches applied to the strategic planning of transportation infrastructures

    The strategic decisions with regard to the investments in transportation infrastructures usually involve large amounts of money. Therefore, decisions should be carefully analyzed. Cost-benefit analysis, usually based on trial-and-error approaches, does not allow the full exploration of the solution space. This can only be done by using optimization techniques. This talk will give an overview of the work developed by the author on the usage of optimization approaches to solve strategic transportation investment planning problems. The different approaches will be illustrated with the application to several case studies, including the definition of national/regional road network plans and the location of freight intermodal terminals in Belgium.

    Where: HEC-Management School of the University of Liege - 14, rue Louvrex (N1, room 311)- 4000 Liège

  HEC-Management School - University of Liège