An improved hybrid algorithm for solving the generalized vehicle routing problem

Authors:
Petric C. Pop;Oliviu Matei;Corina Pop Sitar
Affiliations:
Technical University of Cluj-Napoca, North University Center of Baia Mare, Department of Mathematics and Computer Science, Baia Mare, Romania;Technical University of Cluj-Napoca, North University Center of Baia Mare, Department of Electrical Engineering, Baia Mare, Romania;Technical University of Cluj-Napoca, North University Center of Baia Mare, Department of Economics, Romania
Venue:
Neurocomputing
Year:
2013

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HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II

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Abstract

The generalized vehicle routing problem (GVRP) is a natural extension of the classical vehicle routing problem (VRP). In GVRP, we are given a partition of the customers into groups (clusters) and a depot and we want to design a minimum length collection of routes for the fleet of vehicles, originating and terminating at the depot and visiting exactly one customer from each group, subject to capacity restrictions. The aim of this paper is to present an efficient hybrid heuristic algorithm obtained by combining a genetic algorithm (GA) with a local-global approach to the GVRP and a powerful local search procedure. The computational experiments on several benchmark instances show that our hybrid algorithm is competitive to all of the known heuristics published to date.