GPU-based Parallel Heuristics for Capacited Vehicle Routing Problem

Abstract

This paper presents the novel GPU-based parallel strategy for the heuristic algorithms to solve the large-scale Capacited Vehicle Routing Problem (CVRP). A combination of five improvement heuristic approaches has been used to improve the constructed feasible solution. It is noticed that a large amount of CPU time is spent in the solution improvement phase while improving a feasible solution. We aim to discover an independent part of the improvement heuristic approaches and make it run over the GPU platform simultaneously. The proposed parallel version has been tested on large-scale instances of up to 20000 customers. The parallel version offers speedup up to 176.12 × compared to the corresponding sequential version.