A matheuristic algorithm for the multi-depot inventory routing problem. (February 2019)

• Record Type: Journal Article
• Authors: Bertazzi, Luca; Coelho, Leandro C.; De Maio, Annarita; Laganà, Demetrio
• Is Part Of: Transportation research. Volume 122(2019)
• Page Start: 524
• Page End: 544
• Publication Date: 2019-02
• Subjects: Multi-depot inventory routing problem -- Mixed-integer linear programming -- Matheuristic -- Clustering; Logistics -- Periodicals; Transportation -- Periodicals; 388.011
• DOI: 10.1016/j.tre.2019.01.005
• Languages: English
• ISSNs: 1366-5545

Abstract

Highlights: We provide a mathematical formulation for the multi-depot Inventory Routing Problem. We design a three-phase matheuristic algorithm for solving the problem. We design and implement a branch-and-cut algorithm for solving the problem. We show the performance of the proposed matheuristic on a real case study. Abstract: In this paper we solve a practical Multi-Depot Inventory Routing Problem ( MDIRP ). One minimizes routing costs by determining how to serve the customers from different depots, managing their inventory levels to avoid stock-outs. The MDIRP optimizes the trade-off between inventory and routing decisions in an integrated way. We formulate this problem as a mixed-integer linear programming model and design a three-phase matheuristic to solve the problem. The solutions of our matheuristic are compared with those from a branch-and-cut algorithm on classical IRP instances, new instances and a real case study, showing to be very effective.