A Matheuristic for the Multivehicle Inventory Routing Problem

Claudia Archetti (), Natashia Boland () and Grazia Speranza ()
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Claudia Archetti: Department of Economics and Management, University of Brescia, 25122 Brescia, Italy
Natashia Boland: School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332
Grazia Speranza: Department of Economics and Management, University of Brescia, 25122 Brescia, Italy

INFORMS Journal on Computing, 2017, vol. 29, issue 3, 377-387

Abstract: We consider the inventory routing problem, in which a supplier has to replenish a set of customers by means of a limited fleet of capacitated vehicles over a discrete time horizon. The goal is to minimize the total cost of the distribution that comprises the inventory cost at the supplier and at the customers and the routing cost. We present a matheuristic that combines a tabu search and mathematical programming formulations. When compared with two exact methods on 640 small instances, the matheuristic finds 192 (48%) optima over the 402 instances with known optima and improves 125 upper bounds. Tested on 240 large instances (with up to 200 customers) for which no optimal solutions are known, it improves the best solution for 220 (92%) of the 240 instances.

Keywords: inventory routing; matheuristics; mixed integer linear programming; tabu search (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (23)

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