Thursday 21st of September 2017
 

Heterogeneous Vehicle Routing Problem with profits Dynamic solving by Clustering Genetic Algorithm


Sawsan Amous Kallel and Younes Boujelbene

The transport problem is known as one of the most important combinatorial optimization problems that have drawn the interest of many researchers. Many variants of these problems have been studied in this decade especially the Vehicle Routing Problem (VRP). The transport problem has been associated with many variants such as the Heterogeneous Vehicle Routing Problem (HVRP) and others dynamic problems. We propose in this study dynamic performance measures added to HVRP that we call “Heterogeneous Vehicle Routing Problem with Dynamic Profits” (HVRPDP), and we solve this problem by proposing a new scheme based on a clustering genetic algorithm heuristics that we will specify later. Computational experiments with the benchmark test instances confirm that our approach produces acceptable quality solutions compared with previous results in similar problems in terms of generated solutions and processing time. Experimental results prove that the method of clustering genetic algorithm heuristics is effective in solving the HVRPDP problem and hence has a great potential.

Keywords: The Heterogeneous Vehicle Routing Problem, dynamic problems, genetic algorithm heuristics, k-means clustering.

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ABOUT THE AUTHORS

Sawsan Amous Kallel
Research Unit in Applied Economics, Faculty of Economics and Management, Tunisia

Younes Boujelbene
Director of the Research Unit UREA


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