A Matheuristic with Fixed-Sequence Reoptimization for a Real-Life Inventory Routing Problem

Yun He (), Christian Artigues (), Cyril Briand (), Nicolas Jozefowiez () and Sandra Ulrich Ngueveu ()
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Yun He: Laboratoire d’Analyse et d’Architecture des Systèmes, Centre National de la Recherche Scientifique, Université Paul Sabatier, Université de Toulouse, 31031 Toulouse Cedex 4, France; IMT Atlantique, 44307 Nantes Cedex 3, France; Laboratoire des Sciences de Numérique de Nantes, Centre National de la Recherche Scientifique, Unité Mixte de Recherche 6004, Université de Nantes, 44322 Nantes Cedex 3, France; School of Computer Science, University of Nottingham, Nottingham NG8 1BB, United Kingdom
Christian Artigues: Laboratoire d’Analyse et d’Architecture des Systèmes, Centre National de la Recherche Scientifique, Université Paul Sabatier, Université de Toulouse, 31031 Toulouse Cedex 4, France
Cyril Briand: Laboratoire d’Analyse et d’Architecture des Systèmes, Centre National de la Recherche Scientifique, Université Paul Sabatier, Université de Toulouse, 31031 Toulouse Cedex 4, France
Nicolas Jozefowiez: Laboratoire de Conception, Optimisation et Modélisation des Systèmes, Université de Lorraine, Metz 57000, France
Sandra Ulrich Ngueveu: Laboratoire d’Analyse et d’Architecture des Systèmes, Centre National de la Recherche Scientifique, INP Toulouse, Université de Toulouse, 31031 Toulouse Cedex 4, France

Transportation Science, 2020, vol. 54, issue 2, 355-374

Abstract: This paper proposes a matheuristic for solving a real-life inventory routing problem introduced in the ROADEF/EURO Challenge 2016. The method integrates a fixed-sequence mathematical program, two randomized greedy algorithms, and a column-generation-based heuristic. In particular, the paper discusses the performance of the fixed-sequence mathematical program, which considers a fixed sequence of customer visits and aims at (re)optimizing partial solutions by modifying arrival times and delivered or loaded quantities. Experiments show that the proposed algorithm for the fixed-sequence subproblem is efficient as a postoptimization process and is even able to improve the best solutions obtained during the challenge.

Keywords: inventory routing problem; matheuristic; mixed Integer linear fractional programming (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:54:y:2020:i:2:p:355-374

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