Abstract
The generalized vehicle routing problem (GVRP) is one of the challenging combinatorial optimization problems that finds a lot of practical applications. The GVRP is a natural extension of the classical vehicle routing problem (VRP) and it is an NP-hard optimization problem belonging to the class of generalized combinatorial optimization problems. The aim of this paper is to present a new approach to tackle this complex problem. Combining this approach with a genetic algorithm results an efficient hybrid soft computing technique for solving the generalized vehicle routing problem. The proposed algorithm is competitive with other heuristics published to date in both solution quality and computation time. The computational results for several benchmarks problems are reported and the results point out that our proposed algorithm is an appropriate method to explore the search space of this complex problem and leads to good solutions in a reasonable amount of time.
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Pop, P., Matei, O., Valean, H. (2011). An Efficient Hybrid Soft Computing Approach to the Generalized Vehicle Routing Problem. In: Corchado, E., Snášel, V., Sedano, J., Hassanien, A.E., Calvo, J.L., Ślȩzak, D. (eds) Soft Computing Models in Industrial and Environmental Applications, 6th International Conference SOCO 2011. Advances in Intelligent and Soft Computing, vol 87. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19644-7_30
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DOI: https://doi.org/10.1007/978-3-642-19644-7_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19643-0
Online ISBN: 978-3-642-19644-7
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