ORBEL 34

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Schedule


Thursday, 30 January
08:30-09:10Welcome-registration-coffeeB14-B15-B16
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
Health-care
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
Logistics
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
12:40-14:10LunchB14-B15-B16
14:10-15:10Parallel sessions
  Orbel Award
Chair: Jeroen Belien
Room: E501
Optimization
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
  • Partisanship in everyday life: predictive modeling with Facebook like data
    Stiene Praet (University of Antwerp)
    Co-authors: Peter Van Aelst, David Martens
  • Success Prediction with Dynamic Time Warping-based Feature Engineering for Activity Count Data
    Steven Van Goidsenhoven (KU Leuven)
    Co-authors: Galina Deeva, Seppe vanden Broucke, Jochen De Weerdt
  • Unravelling Drop-out in Fully Asynchronous Subscription-based MOOCs: When is Drop-out Failure or Success?
    Wai Kit Tsang (Ghent University)
    Co-authors: Annelies Raes, Kristof Coussement, Dries Benoit
  • Valuing lead time in a periodic-review multi-period order-up-to inventory system
    Jente Van Belle (Vrije Universiteit Brussel)
    Co-authors: Tias Guns; Wouter Verbeke
    Abstract:
    Short lead times reduce exposure to demand uncertainty but generally also entail high production costs. de Treville et al. (2014) propose a real-options model for optimizing production (and sourcing) choices under demand uncertainty through an effective balance of production cost and lead time. They consider a single-period newsvendor problem in which lead time is modeled as an endogenous decision variable with demand uncertainty increasing in lead time and excess demand modeled as a foregone sales opportunity. The model allows to determine the required decrease (justified increase) in unit production cost to compensate for higher (lower) demand uncertainty exposure coming from an increase (decrease) in lead time. In this paper, we propose several adjustments to this model that are necessary so that it can be used to analyze the effect of lead times in periodic-review multi-period order-up-to inventory systems in which excess demand is backordered. Under this commonly used inventory control policy, in each period t, (i) items produced in that period are added to inventory, (ii) demand is satisfied (fulfilled or backordered), (iii) the inventory position is reviewed, and (iv) the quantity to be produced at time t+h is determined based on the forecasted demand over lead time. Adjustments are suggested to take into account backordering costs and the shift from single-period to lead time demand forecasts. We apply the adjusted model to a real case study in which sales history and open order data is available for producing demand forecasts. To this end, we rely on the closed-form Black-Scholes option pricing formulas. Historical data is used to calibrate the model parameters which allows us to take into account the effect on demand uncertainty of the arrival rate and clustering behavior of the open order data. Finally, we also propose a data-driven counterpart of the model by relying on sample average approximation via inventory simulations. This alternative approach allows to consider inventory systems that make use of nonparametric distributions to determine optimal production quantities but is computationally more intensive than the real-options model.

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

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