Unconventional Heuristics for Vehicle Routing Problems

Eva Volna and Martin Kotyrba1

Faculty of Science Department of Informatics and Computers, University of Ostrava, 30 dubna 22, 70103 Ostrava, Czech Republic

1Corresponding author. E-mail: martin.kotyrba@osu.cz

Abstract: The Vehicle Routing Problem (VRP) is one of the most challenging combinatorial optimization tasks. This problem consists in designing an optimal set of routes for a fleet of vehicles in order to serve a given set of customers. Vehicle routing problem forms an integral part of the supply chain management, which plays a significant role in productivity improvement in organizations through an efficient and effective delivery of goods/services to customers. This problem is known to be NP-hard; hence many heuristic procedures for its solution have been suggested. For such problems, it is often desirable to obtain approximate solutions, so they can be found fast enough and are sufficiently accurate for the purpose. In this paper, we have performed an experimental study that indicates a suitable use of genetic algorithms for the vehicle routing problem. We tested instances from Capacitated Vehicle Routing Problem Library (CVRPLIB) series A, B, E, M and X. The obtained experimental outputs were compared with the following heuristics: the Clarke and Wright heuristic, sweep algorithm, and Taillard’s algorithm.

Keywords VRP – Vehicle Routing Problem, combinatorics, Clarke and Wright heuristic, Sweep algorithm,Taillard’s algorithm, Genetic algorithm.
Mathematics Subject Classification: 97K20, 90C59


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