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Schedule
Thursday, 30 January |
08:30-09:10 | Welcome-registration-coffee | B14-B15-B16 |
09:10-09:30 | Opening session | Amphi Cuccaroni |
09:30-10:30 | Plenary session - Adam Letchford (Chair: Martine Labbé) | Amphi Cuccaroni |
10:30-11:20 | Coffee break | B14-B15-B16 |
11:20-12:40 | Parallel sessions |
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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 |
12:40-14:10 | Lunch/ORBEL Board meeting | B14-B15-B16/E501 |
14:10-15:10 | Parallel sessions |
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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 |
15:10-15:50 | Coffee break | B14-B15-B16 |
15:50-16:40 | Parallel sessions |
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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 |
16:50-17:30 | ORBEL general assembly | Amphi Cuccaroni |
19:00-20:00 | Cocktail | Bar Zango |
20:30-23:00 | Dinner | La Terrasse des Ramparts |
Friday, 31 January |
09:30-10:30 | Plenary session - Miguel F. Anjos (Chair: Luce Brotcorne) | Amphi Cuccaroni |
10:30-11:20 | Coffee break | B14-B15-B16 |
11:20-12:40 | Parallel sessions |
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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 |
12:40-14:10 | Lunch | B14-B15-B16 |
14:10-15:10 | Parallel sessions |
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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 |
15:10-15:50 | Coffee break | B14-B15-B16 |
15:50-16:50 | Parallel sessions |
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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 |
17:00-17:15 | ORBEL award and closing session | Amphi Cuccaroni |
17:15-18:30 | Closing cocktail | B14-B15-B16 |
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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
- An Exact Model for the order picking problem
Farzaneh Rajabighamchi (Maastricht) Co-authors: Christof Defryn, Stan Van Hoesel
- Integrating Classification, Labelling and Packaging Regulations in Manual Order Picking
Sarah Vanheusden (Hasselt University, research group logistics) Co-authors: Teun van Gils, Katrien Ramaekers and An Caris
- Integration of multiple order picking planning problems and vehicle routing: state of the art
Ruben D'haen (UHasselt) Co-authors: Kris Braekers, Katrien Ramaekers
- The Scattered Storage Assignment Problem
Harol Mauricio Gamez Alban (University of Antwerpen) Co-authors: Trijntje Cornelissens and Kenneth Sörensen Abstract: Scattered storage assignment (SSA) is the process where different quantities of a specific SKU (stock-keeping unit) are dispersed and distributed strategically throughout multiple warehouse positions [1]. In recent years, some studies have developed to solve the scattered storage problem, which is usually a variant about how to storage SKU through a warehouse positions. The aim is to reduce travel times during the order picking, since it increases the probability of finding the products of an e-commerce order in the same or nearby aisles. The first approach of solution for the SSA is introduced by [2] as an alternative to reduce walking time. They were able to prove that their SSA algorithm is better than random storage assignments (which are the most typical assignments in real world) in terms of the picking effort.
This type of storage is adequate when a large variety of products are ordered but in small quantities. This occurs primarily with e-commerce orders from individual retailers or consumers. In general the allocation of storage positions for each product is done taking into account
the following characteristics: In each position only one type of product is allowed, every single storage position has a predefined capacity for each type of product, the distances between positions are known, products of the same order should be as close as possible to each other, and each product demand must be stored in a single storage position.
In order to solve the previous problem characteristics, this paper proposes an exact algorithm that assigns the items to multiple storage locations around the warehouse trying to minimize the distance between the products of the same order. The exact algorithm is related with the
lifting procedure developed by [3], and and the recent improvement proposed by [4] for the Knapsack problem. Finally, a set of random instances were developed to compare the results of the algorithm and test its performance.
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
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ORBEL - Conference chairs: Diego Cattaruzza and Maxime Ogier
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