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.

A matheuristic algorithm for the multi-depot inventory routing problem

De Maio A.
;
Lagana D.
2019

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.
Clustering; Matheuristic; Mixed-integer linear programming; Multi-depot inventory routing problem
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Descrizione: The published article is available at https://www.sciencedirect.com/science/article/abs/pii/S1366554518307749; DOI: 10.1016/j.tre.2019.01.005
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/300942
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