A new crossover to solve the full truckload vehicle routing problem using genetic algorithm

TitreA new crossover to solve the full truckload vehicle routing problem using genetic algorithm
Publication TypeConference Paper
Year of Publication2016
AuthorsK. Bouyahyiouy, E, Bellabdaoui, A
Conference NameProceedings of the 3rd IEEE International Conference on Logistics Operations Management, GOL 2016

This paper considers the full-truckload selective multi-depot vehicle routing problem under time windows constraints (denoted by FT-SMDVRPTW), which is a generalization of the vehicle routing problem (VRP). Our objective function is to maximize the total profit that the vehicle generates during its trip. In this study, we'll present a review of literature about full truckload vehicle routing; we'll define the FT-SMDVRPTW that will be resolved via using genetic algorithm. A new complex two-part chromosome is used to represent the solution to our problem. Through a selection based on the elitist method and roulette method, an improved crossover operator called selected two-part chromosome crossover (S-TCX), and swap mutation operator new individuals are generated. Finally, we give a numerical example on a randomly generated instance to illustrate our approach. © 2016 IEEE.




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