We study the Multi-Depot Inventory Routing Problem (MDIRP) with homogeneous vehicle fleet and deterministic demand. We implement a branch-and-cut algorithm for this problem. Then, we design a matheuristic in which we first optimally solve a modified version of the Capacitated Concentrator Location Problem (CCLP) to generate a cluster of customers for each depot and, then, we exactly solve the problem based on these clusters with a branch-and-cut algorithm. Computational results are presented to compare the performance of the matheuristic with respect to the branch-and-cut, in order to analyze the value of the clustering approach in solving this problem.
The Impact of a Clustering Approach on Solving the Multi-depot IRP
DE MAIO, ANNARITA;Laganà, Demetrio
2017-01-01
Abstract
We study the Multi-Depot Inventory Routing Problem (MDIRP) with homogeneous vehicle fleet and deterministic demand. We implement a branch-and-cut algorithm for this problem. Then, we design a matheuristic in which we first optimally solve a modified version of the Capacitated Concentrator Location Problem (CCLP) to generate a cluster of customers for each depot and, then, we exactly solve the problem based on these clusters with a branch-and-cut algorithm. Computational results are presented to compare the performance of the matheuristic with respect to the branch-and-cut, in order to analyze the value of the clustering approach in solving this problem.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
