The min-max multi-depot vehicle routing problem: heuristics and computational results

Xingyin Wang, Bruce Golden and Edward Wasil
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Xingyin Wang: Department of Mathematics, University of Maryland, College Park MD, USA
Bruce Golden: Robert H. Smith School of Business, University of Maryland, College Park MD, USA
Edward Wasil: Kogod School of Business, American University, Washington DC, USA

Journal of the Operational Research Society, 2015, vol. 66, issue 9, 1430-1441

Abstract: In the multi-depot vehicle routing problem (MDVRP), there are several depots where vehicles can start and end their routes. The objective is to minimize the total distance travelled by all vehicles across all depots. The min-max multi-depot vehicle routing problem (Min-Max MDVRP) is a variant of the standard MDVRP. The primary objective is to minimize the length of the longest route. We develop a heuristic (denoted by MD) for the Min-Max MDVRP that has three stages: (1) simplify the multi-depot problem into a single depot problem and solve the simplified problem; (2) improve the maximal route; (3) improve all routes by exchanging customers between routes. MD is compared with two alternative heuristics that we also develop and an existing method from the literature on a set of 20 test instances. MD produces 15 best solutions and is the top performer. Additional computational experiments on instances with uniform and non-uniform distributions of customers and varying customer-to-vehicle ratios and with real-world data further demonstrate MD’s effectiveness in producing high-quality results.

Date: 2015
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