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1. Optimization of human-aware logistics and manufacturing systems: A survey on the Human-Aware Models

Author

Thibault Prunet, Nabil Absi, Valeria Borodin, and Diego Cattaruzza

Subjects
Optimization, Human factors, Ergonomics, Manufacturing, Logistics, Transportation engineering, TA1001-1280
Abstract

Historically, Operations Research (OR) discipline has mainly been focusing on economic concerns. Since the early 2000s, human considerations are gaining increasing attention, pushed by the growing societal concerns of sustainable development on the same terms as the economic and ecological ones. This paper is the second part of a work that aims at reviewing the efforts dedicated by the OR community to the integration of human aspects into logistics and manufacturing systems. A focus is put on the models proposed to represent and quantify human characteristics, their practical relevance, and the complexity induced by their integration with mathematical optimization models. In this paper, the techniques used in the OR literature to represent the human considerations encountered in logistics and manufacturing systems are surveyed. The existing Human-Aware Models (HAM) are classified and reviewed by domain. Particular attention is paid to the field validity of each method, its relevance to specific use cases, the required data collection, and its usability within mathematical optimization models. Since the surveyed HAMs rely on concepts originating from different related scientific disciplines (e.g., ergonomics, occupational medicine), a brief introduction of these fields of study is proposed together with a work of contextualization that is carried out during the analysis.

Published
2024
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2. Optimization of human-aware logistics and manufacturing systems: A comprehensive review of modeling approaches and applications

Author

Thibault Prunet, Nabil Absi, Valeria Borodin, and Diego Cattaruzza

Subjects
Optimization, Human factors, Industry 5.0, Manufacturing, Logistics, Ergonomics, Transportation engineering, TA1001-1280
Abstract

Historically, Operations Research (OR) discipline has mainly been focusing on economic concerns. Since the early 2000s, human considerations are gaining increasing attention, pushed by the growing societal concerns of sustainable development on the same terms as the economic and ecological ones. This paper is the first part of a work that aims at reviewing the efforts dedicated by the OR community to the integration of human factors into logistics and manufacturing systems. A focus is put on the modeling and solution approaches used to consider human characteristics, their practical relevance, and the complexity induced by their integration within optimization models. The material presented in this work has been retrieved through a semi-systematic search of the literature. Then, a comprehensive analysis of the retrieved corpus is carried out to map the related literature by class of problems encountered in logistics and manufacturing. These include warehousing, vehicle routing, scheduling, production planning, and workforce scheduling and management. We investigate the mathematical programming techniques used to integrate human factors into optimization models. Finally, a number of gaps in the literature are identified, and new suggestions on how to suitably integrate human factors in OR problems encountered in logistics and manufacturing systems are discussed.

Published
2024
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3. A Branch-Price-and-Cut algorithm for the Multi-Commodity two-echelon Distribution Problem

Author

Matteo Petris, Claudia Archetti, Diego Cattaruzza, Maxime Ogier, and Frédéric Semet

Subjects
Two echelon routing problems, Multiple commodities, Split delivery, Branch-Price-and-Cut, Transportation engineering, TA1001-1280
Abstract

In the Multi-Commodity two-echelon Distribution Problem (MC2DP), multiple commodities are distributed in a two-echelon distribution system involving suppliers, distribution centres and customers. Each supplier may provide different commodities and each customer may request several commodities as well. In the first echelon, capacitated vehicles perform direct trips to transport the commodities from the suppliers to the distribution centres for consolidation purposes. In the second echelon, each distribution centre owns a fleet of capacitated vehicles to deliver the commodities to the customers through multi-stop routes. Commodities are compatible, i.e., they can be mixed in the vehicles. Finally, customer requests can be split by commodities, that is, a customer can be visited by several vehicles, but the total amount of each commodity has to be delivered by a single vehicle. The aim of the MC2DP is to minimize the total transportation cost to satisfy customer demands.We propose a set covering formulation for the MC2DP where the exponential number of variables relates to the routes in the delivery echelon. We develop a Branch-Price-and-Cut algorithm (BPC) to solve the problem. The pricing problem results in solving an Elementary Shortest Path Problem with Resource Constraints (ESPPRC) per distribution centre. We tackle the ESPPRC with a label setting dynamic programming algorithm which incorporates ng-path relaxation and a bidirectional labelling search. Pricing heuristics are invoked to speed up the procedure. In addition, the formulation is strengthened by integrating capacity cuts and two families of valid inequalities specific for the multiple commodities aspect of the problem.Our approach solves to optimality 439 over the 736 benchmark instances from the literature. The optimality gap of the unsolved instances is 2.1%, on average.

Published
2024
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32. A sequential approach for a multi-commodity two-echelon distribution problem

Author

Diego Cattaruzza, Frédéric Semet, Maxime Ogier, Claudia Archetti, Wenjuan Gu, M. Grazia Speranza, Cattaruzza, Diego, Beijing University of Posts and Telecommunications (BUPT), ESSEC Business School, Integrated Optimization with Complex Structure (INOCS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Università degli Studi di Brescia = University of Brescia (UniBs), Essec Business School, and Università degli Studi di Brescia [Brescia]

Subjects
Mathematical optimization, General Computer Science, [INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], Computer science, sequential solution, Supply chain, Commodity, 0211 other engineering and technologies, Distribution (economics), 02 engineering and technology, Set (abstract data type), Consolidation (business), Order (exchange), 0502 economics and business, local fresh food supply chain, routing problem, multicommodity, Distribution center, 050210 logistics & transportation, 021103 operations research, business.industry, 05 social sciences, General Engineering, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Heuristics, business
Abstract

International audience; We address a Multi-Commodity two-echelon Distribution Problem (MC2DP) where three sets of stakeholders are involved: suppliers, distribution centers, and customers. Multiple commodities have to be sent from suppliers to customers, using multiple distribution centers for consolidation purposes. Commodities are collected from the suppliers and delivered to the distribution centers with direct trips, while a fleet of homogeneous vehicles distributes commodities to customers. Commodities are compatible, that is any vehicle can transport any set of commodities as long as its capacity is not exceeded. The goal is to minimize the total transportation cost from suppliers to customers. We present two sequential schemes based on the solution, in a different order, of a collection and a delivery subproblem. In both cases, the solution of the first subproblem determines the quantity of each commodity at each distribution center. The second subproblem takes this information as input. We also propose different strategies to guide the solution of the first subproblem in order to take into account the impact of its solution on the second subproblem. The proposed sequential heuristics are evaluated and compared both on randomly generated instances and on a case study related to a short and local fresh food supply chain. The results show the impact of problem characteristics on solution strategies.

Published
2022

33. Using Machine Learning to Enhance Clarke and Wright Heuristic

Author

Clément Legrand, Luca Accorsi, Vigo Daniele, Diego Cattaruzza, Marie-Eléonore Kessaci, Laetitia Jourdan, Operational Research, Knowledge And Data (ORKAD), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), University of Bologna/Università di Bologna, Université de Lille-Centrale Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Centrale Lille-Centre National de la Recherche Scientifique (CNRS), and University of Bologna

Subjects
[INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2021

34. Mixed integer programming formulations for the generalized traveling salesman problem with time windows

Author

Yuan Yuan, Frédéric Semet, Cyriaque Rousselot, Diego Cattaruzza, Maxime Ogier, Integrated Optimization with Complex Structure (INOCS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), and Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)

Subjects
Vertex (graph theory), 050210 logistics & transportation, 021103 operations research, 05 social sciences, 0211 other engineering and technologies, 02 engineering and technology, Directed graph, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Management Science and Operations Research, [INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM], Travelling salesman problem, Theoretical Computer Science, Management Information Systems, Combinatorics, Decision variables, Computational Theory and Mathematics, Time windows, 0502 economics and business, Cluster (physics), Integer programming, ComputingMilieux_MISCELLANEOUS, Mathematics
Abstract

The generalized traveling salesman problem with time windows (GTSPTW) is defined on a directed graph where the vertex set is partitioned into clusters. One cluster contains only the depot. Each vertex is associated with a time window, during which the visit must take place if the vertex is visited. The objective is to find a minimum cost tour starting and ending at the depot such that each cluster is visited exactly once and time constraints are respected, i.e., for each cluster, a single vertex is visited during its time window. In this paper, four mixed integer linear programming formulations for the GTSPTW are proposed and compared. They are based on different definitions of variables. All the formulations are compact, which means the number of decision variables and constraints is polynomial with respect to the size of the instance. Dominance relations between their linear relaxations are established theoretically. Computational experiments are conducted to compare the linear relaxations and branch-and-bound performances of the four formulations. The results show that two formulations are better than the other ones.

Published
2021
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35. A column generation based heuristic for the generalized vehicle routing problem with time windows

Author

Diego Cattaruzza, Daniele Vigo, Frédéric Semet, Maxime Ogier, Yuan Yuan, Integrated Optimization with Complex Structure (INOCS), Université libre de Bruxelles (ULB)-Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Université de Lille-Centrale Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Centrale Lille-Centre National de la Recherche Scientifique (CNRS), Alma Mater Studiorum University of Bologna (UNIBO), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Yuan Y., Cattaruzza D., Ogier M., Semet F., Vigo D., Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO), Operations Analytics, Amsterdam Business Research Institute, and Semet, Frédéric

Subjects
Mathematical optimization, time windows, [INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], Computer science, Heuristic (computer science), trunk/in-car delivery, Trunk/in-car delivery, 0211 other engineering and technologies, Transportation, 02 engineering and technology, [INFO] Computer Science [cs], Delivery options, generalized vehicle routing problem, last mile delivery, 0502 economics and business, Vehicle routing problem, [INFO]Computer Science [cs], Local search (optimization), Column generation, Generalized vehicle routing problem, Business and International Management, Time windows, ComputingMilieux_MISCELLANEOUS, Civil and Structural Engineering, 050210 logistics & transportation, 021103 operations research, Delivery option, business.industry, 05 social sciences, Directed graph, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Last mile delivery, Vertex (geometry), Time window, Routing (electronic design automation), business, Reduced cost, delivery options
Abstract

The generalized vehicle routing problem with time windows (GVRPTW) is defined on a directed graph G = ( V , A ) where the vertex set V is partitioned into clusters. One cluster contains only the depot, where is located a homogeneous fleet of vehicles, each with a limited capacity. The other clusters represent customers. A demand is associated with each cluster. Inside a cluster, the vertices represent the possible locations of the customer. A time window is associated with each vertex, during which the visit must take place if the vertex is visited. The objective is to find a set of routes such that the total traveling cost is minimized, exactly one vertex per cluster is visited, and all the capacity and time constraints are respected. This paper presents a set covering formulation for the GVRPTW which is used to provide a column generation based heuristic to solve it. The proposed solving method combines several components including a construction heuristic, a route optimization procedure, local search operators and the generation of negative reduced cost routes. Experimental results on benchmark instances show that the proposed algorithm is efficient and high-quality solutions for instances with up to 120 clusters are obtained within short computation times.

Published
2021
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36. An efficient and general approach for the joint order batching and picker routing problem

Author

Diego Cattaruzza, Maxime Ogier, Olivier Briant, Hadrien Cambazard, Anne-Laure Ladier, Nicolas Catusse, Optimisation Combinatoire (G-SCOP_OC), Laboratoire des sciences pour la conception, l'optimisation et la production (G-SCOP), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Recherche Opérationnelle pour les Systèmes de Production (G-SCOP_ROSP), Integrated Optimization with Complex Structure (INOCS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Décision et Information pour les Systèmes de Production (DISP), Université Lumière - Lyon 2 (UL2)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)

Subjects
050210 logistics & transportation, Mathematical optimization, Order picking, 021103 operations research, Information Systems and Management, column generation, General Computer Science, Computer science, 05 social sciences, 0211 other engineering and technologies, [SCCO.COMP]Cognitive science/Computer science, 02 engineering and technology, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Management Science and Operations Research, picker routing, Travelling salesman problem, Industrial and Manufacturing Engineering, Field (computer science), Modeling and Simulation, 0502 economics and business, Benchmark (computing), Column generation, Routing (electronic design automation), order batching
Abstract

International audience; Order picking is the process of retrieving products from inventory. It is mostly done manually by dedicated employees called pickers and is considered the most expensive of warehouse operations. To reduce the picking cost, customer orders can be grouped into batches that are then collected by traveling the shortest possible distance.This work presents an exponential linear programming formulation to tackle the joint order batching and picker routing problem. Variables, or columns, are related to the picking routes in the warehouse. Computing such routes is generally an intractable routing problem and relates to the well known traveling salesman problem (TSP). Nonetheless, the rectangular warehouse’s layouts can be used to efficiently solve the corresponding TSP and take into account in the development of an efficient subroutine, called oracle. We therefore investigate whether such an oracle allows for an effective exponential formulation.Experimented on a publicly available benchmark, the algorithm proves to be very effective. It improves many of the best known solutions and provides very strong lower bounds. Finally, this approach is applied to another industrial case to demonstrate its interest for this field of application.

Published
2020
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37. Two-echelon distribution with a single capacitated city hub

Author

Dominique Feillet, Pamela C. Nolz, Nabil Absi, Diego Cattaruzza, Austrian Institute of Technology [Vienna] (AIT), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Integrated Optimization with Complex Structure (INOCS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), and This work received funding from the European Union’s Horizon 2020 Research and Innovation Program, the Austrian Federal Ministry for Climate Action, Environment, Energy, Mobility, Innovation and Technology (BMK) in the framework of the research programme ‘JPI Urban Europe’ under grant agreement n° 854921 (CIVIC), and from the Climate and Energy Fund of the Austrian Federal Government in the 'Austrian Electric Mobility Flagship Projects' programme under grant agreement n° 845100 (EMILIA).

Subjects
education.field_of_study, Operations research, Heuristic, business.industry, Computer science, 030503 health policy & services, 05 social sciences, Population, Distribution (economics), 050109 social psychology, Transportation, Context (language use), [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Management Science and Operations Research, Distribution system, 03 medical and health sciences, Modeling and Simulation, Synchronization (computer science), 0501 psychology and cognitive sciences, 0305 other medical science, education, business, Metaheuristic, ComputingMilieux_MISCELLANEOUS, Integer (computer science)
Abstract

In this paper, we investigate the synchronization between the two echelons in two-echelon urban distribution systems. The first echelon aims at transferring goods from a warehouse to a (single) city hub located in the city center. The second echelon, managed with a fleet of environmentally friendly vehicles, delivers goods to final customers, from the city hub. The two echelons are synchronized in time but also with regards to the capacity of the city hub. As far as we know, this is the first study considering the latter issue in the context of two-echelon distribution. To deal with the synchronization while optimizing the distribution, we propose a three-phase heuristic solution approach. At first, our approach optimizes the distribution for the second echelon. Then, it manages the synchronization. Finally, it optimizes the distribution for the first echelon. Population-based metaheuristics and integer programs are used. Results show the effectiveness of the method and permit to derive managerial insights on the distribution.

Published
2020
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38. A note on the lifted Miller-Tucker-Zemlin subtour elimination constraints for routing problems with time windows

Author

Frédéric Semet, Yuan Yuan, Diego Cattaruzza, Maxime Ogier, Integrated Optimization with Complex Structure (INOCS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), and Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)

Subjects
Mathematical optimization, time windows, 021103 operations research, Computer science, Applied Mathematics, routing problems, 0211 other engineering and technologies, 02 engineering and technology, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Management Science and Operations Research, 01 natural sciences, Travelling salesman problem, Industrial and Manufacturing Engineering, Miller-Tucker-Zemlin, 010104 statistics & probability, Time windows, Vehicle routing problem, 0101 mathematics, Routing (electronic design automation), subtour elimination constraints, Software
Abstract

International audience; We propose lifted versions of the Miller-Tucker-Zemlin subtour elimination constraints for routing problems with time windows (TW). The constraints are valid for problems such as the travelling salesman problem with TW, the vehicle routing problem with TW, the generalized travelling salesman problem with TW, and the general vehicle routing problem with TW. They are corrected versions of the constraints proposed by Desrochers and Laporte (1991).

Published
2020
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39. A heuristic branch-cut-and-price algorithm for the ROADEF/EURO challenge on Inventory Routing

Author

Dominique Feillet, Maxime Ogier, Nabil Absi, Diego Cattaruzza, Frédéric Semet, Département Sciences de la Fabrication et Logistique (SFL-ENSMSE), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-CMP-GC, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Integrated Optimization with Complex Structure (INOCS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Institut Mines-Télécom [Paris] (IMT), Ecole Nationale Supérieure des Mines de St Etienne-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Ogier, Maxime, Université libre de Bruxelles (ULB)-Inria Lille - Nord Europe, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL)

Subjects
Inventory routing problem, 050210 logistics & transportation, Mathematical optimization, 021103 operations research, [INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], Computer science, Heuristic, 05 social sciences, 0211 other engineering and technologies, Transportation, 02 engineering and technology, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], [INFO] Computer Science [cs], Challenge ROADEF/EURO, 0502 economics and business, Extended formulation, Special section, [INFO]Computer Science [cs], Inventory Routing Problem, Routing (electronic design automation), Heuristic branch-cut-and-price, Civil and Structural Engineering
Abstract

National audience; In this paper, we propose a heuristic solution method for the Inventory Routing Problem introduced during the 2016 ROADEF/EURO challenge, that we coin as REC-IRP. Inventory routing has attracted researchers for many years due to both its practical and theoretical interests (Coelho et al.; 2013). The REC-IRP proposed for the challenge is original and complex for several reasons : the logistic ratio optimization objective, the hourly time-granularity for inventory constraints, the driver/trailer allocation management. Clearly, designing an exact solution approach is out of reach for large size instances as those proposed during the challenge.However, we decided to address the REC-IRP with a branch-cut-and-price framework : a cut-and-column generation procedure is developed, along with a heuristic pricing algorithm to generate new columns and a heuristic fixing procedure to generate integer solutions

Published
2020
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40. A column generation approach for the joint order batching and picker routing problem

Author

Olivier Briant, Hadrien Cambazard, Diego Cattaruzza, Nicolas Catusse, Anne-Laure Ladier, Maxime Ogier, Optimisation Combinatoire (G-SCOP_OC ), Laboratoire des sciences pour la conception, l'optimisation et la production (G-SCOP), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Recherche Opérationnelle pour les Systèmes de Production (G-SCOP_ROSP ), Integrated Optimization with Complex Structure (INOCS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Décision et Information pour les Systèmes de Production (DISP), Université Lumière - Lyon 2 (UL2)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), and Ogier, Maxime

Subjects
[INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], [SCCO.COMP] Cognitive science/Computer science, [SCCO.COMP]Cognitive science/Computer science, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO]
Abstract

International audience; Picking is the process of retrieving products from inventory.It is mostly done manually by dedicated employees called pickers and is considered the most expensive of warehouse operations.To reduce the picking cost, customer orders can be grouped into batches that are then collected by traveling the shortest possible distance.This work presents an exponential linear programming formulation to tackle the joint order batching and picker routing problem.Variables, or columns, are related to the picking routes in the warehouse.Computing such routess is generally an intractable routing problem and relates to the well known traveling salesman problem (TSP).Nonetheless, the rectangular warehouse's layouts can be used to efficiently solve the corresponding TSP and take into account in the development of an efficient subroutine, called oracle.We therefore investigate whether such an oracle allows for an effective exponential formulation.In order to tackle the exponential number of variables, we develop a column generation heuristic with performance guarantee.The pricing problem approximates the distances, and when finding a solution the oracle is used to get the optimal distance of this solution.The performance of the proposed column generation is strengthen using stabilization techniques and a rich column set.Experimented on a publicly available benchmark, the algorithm proves to be very effective.It improves many of the best known solutions and provides very strong lower bounds.Finally, this approach is applied to another industrial case to demonstrate its interest for this field of application.

Published
2019

41. The generalized vehicle routing problem with time windows

Author

Yuan Yuan, Diego Cattaruzza, Maxime Ogier, Frédéric Semet, Daniele Vigo, Integrated Optimization with Complex Structure (INOCS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO), and YUAN, Yuan

Subjects
time windows, generalized vehicle routing problem, [INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], [INFO]Computer Science [cs], set covering, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], [INFO] Computer Science [cs], ComputingMilieux_MISCELLANEOUS
Abstract

International audience; Global e-commerce sales are estimated to hit $4.5 trillion in 2021. This poses huge challenges forlast mile delivery services. Currently deliveries are performed at customer?s home/workplacewhere customers wait to get orders. Recently, companies developed locker delivery. Customerschoose a nearby locker as their pickup location for orders. In the past two years, trunk de-livery has been proposed: orders can be delivered to the trunks of cars. Trunk delivery isdifferent from the former two since the car may be in different locations during the day. Thus,synchronization between cars and couriers is required to perform the delivery.This work studies a last-mile system that combines home/workplace, locker and trunk deliv-ery services. We call the resulting problem the generalized vehicle routing problem with timewindows (GVRPTW).We describe the GVRPTW with a set covering model. The solution is obtained by solvingthis model on a restricted route pool, subset of all feasible routes. The route pool is first filledusing construction heuristic: first pivots customers are selected, then next inserted customersare selected based on a regret paradigm. Finally routes are re-optimized with a labelingalgorithm. The route pool is iteratively enriched 1) with routes obtained by exploiting thedual information retrieved by the resolution of the linear relaxation of the set covering model;2) with new routes obtained by intensification of the research around feasible solutions via alocal search procedure.The algorithm is tested on benchmark instances from the literature.

Published
2019

42. A Two-Phase Approach for an Integrated Order Batching and Picker Routing Problem

Author

Maxime Ogier, Diego Cattaruzza, Martin Bué, Frédéric Semet, Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria), Integrated Optimization with Complex Structure (INOCS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), and Ogier, Maxime

Subjects
050210 logistics & transportation, Focus (computing), Order picking, 021103 operations research, [INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], Operations research, Computer science, Heuristic (computer science), 05 social sciences, 0211 other engineering and technologies, [SCCO.COMP]Cognitive science/Computer science, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], 02 engineering and technology, Division (mathematics), picker routing, Warehouse management, Set (abstract data type), Dynamic programming, [SCCO.COMP] Cognitive science/Computer science, Order (business), 0502 economics and business, Routing (electronic design automation), order batching
Abstract

International audience; This article addresses an integrated warehouse order picking problem. The company HappyChic is specialized in men’s ready-to-wear. A central warehouse is dedicated to supplying, every day, the shops of one brand. We focus on the picking area of this warehouse which relies on human picking system. For each picking wave (period of a working day), a set of customer orders has to be prepared. An order is a set of product references, with quantities, i.e., the numbers of items required. The problem consists in jointly deciding: (1) the division of orders into several boxes,respecting weight and size constraints; (2) the batching of boxes into trolleys, that implicitly defines the routing into the picking area. The objective function aims to minimize the total distance. To deal with the large size instances of HappyChic in short computation times, we design a heuristic method based on the split and dynamic programming paradigms. The results are very convincing: the total covered distance decreases by more than 20%. Moreover, we propose an adaptation of the algorithm to prepare homogeneous boxes with respect to classes of products. Thelogistic department of HappyChic is convinced by results obtained in this research work, and the warehouse management system is currently being updated in order to integrate the proposed algorithm.

Published
2019
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43. A three-phase matheuristic for the Packaging and Shipping Problem

Author

Luce Brotcorne, Bayrem Tounsi, Frédéric Semet, Diego Cattaruzza, Integrated Optimization with Complex Structure (INOCS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), ANR-11-VPTT-0009,Respet,gestion de RésEaux de Services Porte à porte Efficace pour le Transport de marchandises(2011), Cattaruzza, Diego, Transports Terrestres Durables - gestion de RésEaux de Services Porte à porte Efficace pour le Transport de marchandises - - Respet2011 - ANR-11-VPTT-0009 - TTD - VALID, Université libre de Bruxelles (ULB)-Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), and Université de Lille-Centrale Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Centrale Lille-Centre National de la Recherche Scientifique (CNRS)

Subjects
Flexibility (engineering), 0209 industrial biotechnology, 021103 operations research, Operations research, [INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], Computer science, Heuristic, Applied Mathematics, Postponement, 0211 other engineering and technologies, Time horizon, 02 engineering and technology, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Solver, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, 020901 industrial engineering & automation, Production planning, Modeling and Simulation, Workforce, Production (economics), [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation
Abstract

E-commerce has been continuously growing in the last years to a primary retail market. Recently in France, the threshold of 1 billion of online transactions was overcome. Due to a high demand fluctuation of e-commerce, the workforce sizing for the logistic chain is a challenging problem. Companies have to develop good strategies to have a sustainable workforce size while guaranteeing a high-level service. In this paper, we consider the management of the workforce for a warehouse of an e-commerce company. Specifically, we address issues as i) How the workforce at the warehouse can be determined; ii) What is the daily operational production planning; iii) How the demand peaks can be smoothed, and the production maintained ideally constant over the time horizon. To provide answers to these issues, we introduce the Packaging and Shipping Problem (PSP). The PSP looks for a solution approach that jointly determines the workforce over a multi-period horizon and daily operational plans while minimizing the total logistics cost. We consider two strategies that aim to enhance the flexibility of the process and the efficiency of resources use: reassignment and postponement. To tackle the Packaging and Shipping Problem we propose a model, and a three-phase matheuristic. This heuristic is proved to be competitive with respect to the direct solution of the model with a commercial solver on real-life based instances.

Published
2018

44. A column generation based approach for the joint order batching and picker routing problem

Author

Olivier Briant, Hadrien Cambazard, Diego Cattaruzza, Nicolas Catusse, Anne-Laure Ladier, Maxime Ogier, Optimisation Combinatoire (G-SCOP_OC ), Laboratoire des sciences pour la conception, l'optimisation et la production (G-SCOP), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Recherche Opérationnelle pour les Systèmes de Production (G-SCOP_ROSP ), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Integrated Optimization with Complex Structure (INOCS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Décision et Information pour les Systèmes de Production (DISP), Université Lumière - Lyon 2 (UL2)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)

Subjects
column generation, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], picker routing, ComputingMilieux_MISCELLANEOUS, order batching
Abstract

National audience

Published
2018

45. Adaptive large neighborhood search for multicommodity VRP

Author

Wenjuan Gu, Diego Cattaruzza, Maxime Ogier, Frédéric Semet, Integrated Optimization with Complex Structure (INOCS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Ogier, Maxime, and Gu, Wenjuan

Subjects
[INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], [SCCO.COMP] Cognitive science/Computer science, local search, [SCCO.COMP]Cognitive science/Computer science, adaptive large neighborhood search, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], multicommodity VRP, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2018

46. A relax-and-repair heuristic for the Swap-Body Vehicle Routing Problem

Author

Sylvain Housseman, Dominique Feillet, Nabil Absi, Diego Cattaruzza, Département Sciences de la Fabrication et Logistique (SFL-ENSMSE), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-CMP-GC, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Integrated Optimization with Complex Structure (INOCS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Ecole Nationale Supérieure des Mines de St Etienne-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Université libre de Bruxelles (ULB)-Inria Lille - Nord Europe, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL)

Subjects
Mathematical optimization, Swap-body, Computer science, Equal-cost multi-path routing, Population, 0211 other engineering and technologies, General Decision Sciences, 02 engineering and technology, Management Science and Operations Research, Relax-and-repair, Vehicle routing problem, Genetic algorithm, 0202 electrical engineering, electronic engineering, information engineering, Destination-Sequenced Distance Vector routing, education, Greedy algorithm, Triangular routing, Static routing, education.field_of_study, 021103 operations research, Heuristic, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Vehicle routing, Link-state routing protocol, Multipath routing, 020201 artificial intelligence & image processing
Abstract

International audience; In this paper we address the Swap-Body Vehicle Routing Problem, a variant of the Truck and Trailer Routing Problem. It was introduced in the VeRoLog Challenge 2014. We develop a solution approach that we coin Relax-and-Repair. It consists in solving a relaxed version of the SB-VRP and deriving a feasible solution by repairing the relaxed one. We embed this approach within a population-based heuristic. During computation we store all feasible routes in order to derive better solutions by solving a set-partitioning problem. In order to take advantages of nowadays multi-core machines, our algorithm is designed as a collaborative parallel population-based heuristic. Experimental results show that our relax-and-repair algorithm is very competitive and point the impact of each phase on the quality of the obtained solutions. The advantage of our approach is that it can be adapted to solve complex industrial routing problems.

Published
2017
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47. Simulation of Mutualized Urban Logistics Systems with Real-time Management

Author

Dominique Feillet, Diego Cattaruzza, Frédéric Meunier, Rafik Makhloufi, Nabil Absi, Centre d'Enseignement et de Recherche en Mathématiques et Calcul Scientifique (CERMICS), École des Ponts ParisTech (ENPC), Département Sciences de la Fabrication et Logistique (SFL-ENSMSE), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-CMP-GC, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), and Feillet, Dominique

Subjects
Optimization, Schedule, Service (systems architecture), Engineering, [INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], Operations research, Real-Time Management, media_common.quotation_subject, 0211 other engineering and technologies, Context (language use), 02 engineering and technology, Transport engineering, Set (abstract data type), Real-time Control System, 0502 economics and business, 11. Sustainability, Quality (business), Urban Logistics, ComputingMilieux_MISCELLANEOUS, media_common, 050210 logistics & transportation, 021103 operations research, business.industry, Event (computing), 05 social sciences, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Freight Distribution, Probability distribution, business, Simulation
Abstract

This work aims at proposing a new organization of urban merchandize distribution based on mutualized and optimized resources. In this context, our contribution is twofold. On one hand, we develop a set of models to manage merchandize distribution. We develop a new reservation system that enables customers to request a merchandize transportation service (delivery and collect) or to book a vehicle for self-service purposes. Requests are processed by two main decision modules (1) an online module that immediately searches for a feasible solution for a request, and decides to accept or reject it, and (2) an offline module that looks for optimized solutions starting from the feasible schedule defined by the online module. On the other hand, we develop a new discrete event simulator, called MODUMS which integrates the proposed models, implements such a logistic system and evaluates its economic and environmental impact. MODUMS takes as inputs realistic information about the transportation means, geographic data and demand information requests that are generated according to some probability distributions. It gives as outputs indicators on the impact of mutualization on the quality of urban logistics in terms of, for example, number of delayed or rejected requests, filling rate of vehicles, total distance and quantity of CO2.

Published
2015

48. The Multi-Trip Vehicle Routing Problem with Time Windows and Release Dates

Author

Nabil Absi, Dominique Feillet, Diego Cattaruzza, Cattaruzza, Diego, Département Sciences de la Fabrication et Logistique (SFL-ENSMSE), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-CMP-GC, Integrated Optimization with Complex Structure (INOCS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Institut Mines-Télécom [Paris] (IMT), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189 (CRIStAL), Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Ecole Centrale de Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Ecole Centrale de Lille, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne-Université Clermont Auvergne (UCA)-Centre National de la Recherche Scientifique (CNRS), Université libre de Bruxelles (ULB)-Inria Lille - Nord Europe, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189 (CRIStAL)

Subjects
050210 logistics & transportation, Dynamic Source Routing, Engineering, Static routing, education.field_of_study, 021103 operations research, [INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], business.industry, 05 social sciences, Policy-based routing, Population, 0211 other engineering and technologies, Transportation, 02 engineering and technology, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Travelling salesman problem, Transport engineering, Link-state routing protocol, 0502 economics and business, Vehicle routing problem, Destination-Sequenced Distance Vector routing, business, education, Civil and Structural Engineering, Computer network
Abstract

The MODUM project studies a distribution system based on city distribution centers (CDI) located around a city. Trucks with merchandise that has to be sent to customers arrive from main road axis called Doors. Then, they stop at CDI, where goods are unloaded. CDIs are located around the city center. Environmentally-friendly vehicles (called vans in the following) are used to accomplish final deliveries to customer locations. Delivery trips start from one CDI, visit assigned customers and end at one of the CDIs. Moreover, trips can end at parking points. The possibility of leaving vans at parking points will not be developed in this paper. CDIs are connected with a shuttle. The shuttle circularly goes from one CDI to another CDI, displacing merchandise. This allows to locate merchandise already in the CDI to a more convenient place for the final delivery. Moreover, carriers can deliver merchandise to the CDI they prefer. The shuttle service is carried out with a regular frequency during the working day. Outbound flows, starting with a pick-up at customer location, are considered as well into the system. However, deliveries and picks-up are treated separately and cannot be accomplished in the same trip. Vans have to drive into city centers through small roads, respecting size and weight limitations. They normally have a limited capacity and if they are electrical vehicles, their autonomy is limited as well. It is natural to allow vans to accomplish several trips during the working day. Moreover, with each client, is associated a time window (TW) during which service should be accomplished. Release dates on goods are taken into account. They represent the arrival of merchandise to the CDI.

Published
2013
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49. A multi-commodity transportation planning problem in supply chain management

Author

Wenjuan Gu, Claudia Archetti, Diego Cattaruzza, Maxime Ogier, Frédéric Semet, Maria Grazia Speranza, Integrated Optimization with Complex Structure (INOCS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), University of Brescia, and Gu, Wenjuan

Subjects
sequential solving, [INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], collection, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], delivery, routing problem, multicommodity, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

50. An integrated multi-period stochastic problem in e-fullfilment optimization

Author

Frédéric Semet, Luce Brotcorne, Diego Cattaruzza, Bayrem Tounsi, Integrated Optimization with Complex Structure (INOCS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université libre de Bruxelles (ULB)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), ANR-11-VPTT-0009,Respet,gestion de RésEaux de Services Porte à porte Efficace pour le Transport de marchandises(2011), Semet, Frédéric, and Transports Terrestres Durables - gestion de RésEaux de Services Porte à porte Efficace pour le Transport de marchandises - - Respet2011 - ANR-11-VPTT-0009 - TTD - VALID

Subjects
[INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

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