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What is OR
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   Key speakers
   Detailed program
Conference dinner



Thursday, 30 January
09:10-09:30Opening sessionAmphi Cuccaroni
09:30-10:30Plenary session - Adam Letchford (Chair: Martine Labbé)Amphi Cuccaroni
10:30-11:20Coffee breakB14-B15-B16
11:20-12:40Parallel sessions
  Multi-objective Optimization
Chair: Sara Tari
Room: E501
Chair: Véronique François
Room: E502
Public Transportation
Chair: Javier Duran Micco
Room: E503
Global Optimization
Chair: Olivier Rigal
Room: E601
Analytics 1
Chair: Rafael Van Belle
Room: E602
12:40-14:10Lunch/ORBEL Board meetingB14-B15-B16/E501
14:10-15:10Parallel sessions
  Air, Rail and Multimodal Transportation
Chair: Paola Paregrini
Room: E501
Game Theory
Chair: Lotte Verdnock
Room: E502
Transportation of People
Chair: Yves Molenbruch
Room: E503
Multi-level Optimization
Chair: Concepcion Dominguez
Room: E601
Analytics 2
Chair: Vedavyas Etikala
Room: E602
15:10-15:50Coffee breakB14-B15-B16
15:50-16:40Parallel sessions
  Sport Timetabling
Chair: Dries Goossens
Room: E501
Project Management and Scheduling
Chair: Fan Yang
Room: E502
Rich Routing and Graphs
Chair: Alexandre Bontems
Room: E503
Chair: Yuan Yuan
Room: E601
Analytics 3
Chair: Jari Peeperkorn
Room: E602
16:50-17:30ORBEL general assemblyAmphi Cuccaroni
19:00-20:00CocktailBar Zango
20:30-23:00DinnerLa Terrasse des Ramparts

Friday, 31 January
09:30-10:30Plenary session - Miguel F. Anjos (Chair: Luce Brotcorne)Amphi Cuccaroni
10:30-11:20Coffee breakB14-B15-B16
11:20-12:40Parallel sessions
  Automatic Configuration and Metaheuristics Analysis
Chair: Kenneth Sorensen
Room: E501
Real Life and Integrated Problems
Chair: Jeroen Belien
Room: E502
Warehouse Management
Chair: Harol Mauricio Gamez
Room: E601
Analytics 4
Chair: Noureddine Kouaissah
Room: E602
14:10-15:10Parallel sessions
  Orbel Award
Chair: Jeroen Belien
Room: E501
Chair: Julien Dewez
Room: E502
Trucking Optimization
Chair: Hatice Çalik
Room: E601
Analytics 5
Chair: Diego Olaya
Room: E602
15:10-15:50Coffee breakB14-B15-B16
15:50-16:50Parallel sessions
  Learning and Optimization
Chair: Johan Van Kerckhoven
Room: E501
Lot-sizing and Inventory
Chair: Philippe Chevalier
Room: E502
Rich Routing
Chair: Cristian Aguayo
Room: E601
17:00-17:15ORBEL award and closing sessionAmphi Cuccaroni
17:15-18:30Closing cocktailB14-B15-B16

Thursday 11:20 - 12:40 Multi-objective Optimization
Room E501 - Chair: Sara Tari

Thursday 11:20 - 12:40 Health-care
Room E502 - Chair: Véronique François

Thursday 11:20 - 12:40 Public Transportation
Room E503 - Chair: Javier Duran Micco

Thursday 11:20 - 12:40 Global Optimization
Room E601 - Chair: Olivier Rigal

Thursday 11:20 - 12:40 Analytics 1
Room E602 - Chair: Rafael Van Belle

Thursday 14:10 - 15:10 Air, Rail and Multimodal Transportation
Room E501 - Chair: Paola Pellegrini

Thursday 14:10 - 15:10 Game Theory
Room E502 - Chair: Lotte Verdnock

Thursday 14:10 - 15:10 Transportation of People
Room E503 - Chair: Yves Molenbruch

Thursday 14:10 - 15:10 Multi-level Optimization
Room E601 - Chair: Concepcion Dominguez

Thursday 14:10 - 15:10 Analytics 2
Room E602 - Chair: Vedavyas Etikala

Thursday 15:50 - 16:50 Sport Timetabling
Room E501 - Chair: Dries Goossens

Thursday 15:50 - 16:50 Project Management and Scheduling
Room E502 - Chair: Fan Yang

Thursday 15:50 - 16:50 Rich Routing and Graphs
Room E503 - Chair: Alexandre Bontems

Thursday 15:50 - 16:50 Logistics
Room E601 - Chair: Silia Mertens

Thursday 15:50 - 16:50 Analytics 3
Room E602 - Chair: Jari Peeperkorn

Friday 11:20 - 12:40 Automatic Configuration and Metaheuristics Analysis
Room E501 - Chair: Kenneth Sorensen

Friday 11:20 - 12:40 Real Life and Integrated Problems
Room E502 - Chair: Jeroen Belien

Friday 11:20 - 12:40 Warehouse Management
Room E601 - Chair: Harol Mauricio Gamez

Friday 11:20 - 12:40 Analytics 4
Room E602 - Chair: Noureddine Kouaissah
  • Classification for Imbalanced Data Using Feature Selection and Undersampling Methods
    You-jin Park (National Taipei University of Technology)
    In data mining and machine learning, the real-world data involve a large number of features, and frequently suffer from problem of class imbalance. However, in general, all of the features are not necessary since many of them can be redundant or even irrelevant, which may decrease the performance of an employed algorithm, e.g., a classification algorithm, and also traditional classifiers for a highly imbalanced dataset tend to bias in majority classes and, as a result, the minority class samples are usually misclassified as majority class. So, to overcome these problems, a proper feature selection approach that identifies informative feature subsets from large dimensional datasets, and an efficient sampling technique that removes some majority samples or creates new minority class samples can be used. The feature selection aims to reduce the dimensionality of the data and increase the performance of an algorithm by selecting only a small, but suitable subset of relevant features from the original large-scale dataset. So, various useful feature selection algorithms have been developed and applied to the problem of finding a suitable subset of features in multivariate datasets, often posed as single- or multi-objective optimization problems. And also, to cope with classification for imbalanced data, many machine learning approaches have been developed, most of which have been based on sampling techniques, cost sensitive learning, and ensemble methods. Particularly, some undersampling approaches have been utilized to eliminate the harms of skewed distribution by discarding the intrinsic samples in the majority class. Therefore, in this research, we propose an efficient, but simple cluster-based undersampling method for resolving class imbalance problem with a new feature selection method based on pairwise comparison, and then compare the performance of the classification model to those of others models with respect to various performance measures.
  • Multi-task Neural Networks for Uplift Modeling
    Sam Verboven (Vrije Universiteit Brussel)
    Co-authors: Jeroen Berrevoets, Wouter Verbeke
  • Portfolio selection using semiparametric estimators and a copula PCA based approach
    Noureddine Kouaissah (International University of Rabat, Rabat Business School )

Friday 14:10 - 15:10 Orbel Award
Room E501 - Chair: Jeroen Belien

    Friday 14:10 - 15:10 Optimization
    Room E502 - Chair: Julien Dewez

    Friday 14:10 - 15:10 Trucking Optimization
    Room E601 - Chair: Hatiz Çalik

    Friday 14:10 - 15:10 Analytics 5
    Room E602 - Chair: Diego Olaya

    Friday 15:50 - 16:50 Learning and Optimization
    Room E501 - Chair: Jorik Jooken

    Friday 15:50 - 16:50 Lot-sizing and Inventory
    Room E502 - Chair: Philippe Chevalier

    Friday 15:50 - 16:50 Rich Routing
    Room E601 - Chair: Cristian Aguayo

      ORBEL - Conference chairs: Diego Cattaruzza and Maxime Ogier