A Unified Branch-Price-and-Cut Algorithm for Multicompartment Pickup and Delivery Problems

Author:

Aerts-Veenstra Marjolein1ORCID,Cherkesly Marilène2ORCID,Gschwind Timo3ORCID

Affiliation:

1. Department of Operations, Faculty of Economics and Business, University of Groningen, 9747 AJ Groningen, Netherlands;

2. Département d’analytique, opérations et technologies de l’information, Université du Québec à Montréal and GERAD, Montréal, Québec H3C 3P8, Canada;

3. School of Business and Economics, RPTU Kaiserslautern-Landau, 67663 Kaiserslautern, Germany

Abstract

In this paper, we study the pickup and delivery problem with time windows and multiple compartments (PDPTWMC). The PDPTWMC generalizes the pickup and delivery problem with time windows to vehicles with multiple compartments. In particular, we consider three compartment-related attributes: (1) compartment capacity flexibility that allows the capacities of the compartments to be fixed or flexible, (2) item-to-compartment flexibility that specifies which items are compatible with which compartments, and (3) item-to-item compatibility that considers that incompatible items cannot be simultaneously in the same compartment. To solve the PDPTWMC, we propose an exact branch-price-and-cut algorithm in which the pricing problem is solved by means of a unified bidirectional labeling algorithm. The labeling algorithm can tackle all possible combinations of the studied compartment-related attributes of the PDPTWMC. Furthermore, we implement several acceleration techniques that allow to, among others, reduce the symmetry in the label extensions with empty compartments, the symmetry in the dominance between compartments with similar attributes, and the complexity of the algorithm with fixed compartment capacity. Finally, we introduce benchmark instances for the PDPTWMC and conduct an extensive computational campaign to test the limits of our algorithm and to derive relevant managerial insights in order to highlight the applicability of considering the studied compartment-related attributes. Funding: This work was supported by Nederlandse Organisatie voor Wetenschappelijk Onderzoek [Grant 439.18.459] and the Natural Sciences and Engineering Research Council of Canada [Grant 2017-06106]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2023.0252 .

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

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