A memetic differential evolution algorithm for the vehicle routing problem with stochastic demands

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Abstract

This chapter introduces a new hybrid algorithmic approach based on the Differential Evolution (DE) algorithm for successfully solving a number of routing problems with stochastic variables. More precisely, we solve one problem with stochastic customers, the Probabilistic Traveling Salesman Problem and one problem with stochastic demands, the Vehicle Routing Problem with Stochastic Demands. The proposed algorithm uses a Variable Neighborhood Search algorithm in order to increase the exploitation abilities of the algorithm. The algorithm is tested on a number of benchmark instances from the literature and it is compared with a hybrid Genetic Algorithm.

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Marinakis, Y., Marinaki, M., & Spanou, P. (2015). A memetic differential evolution algorithm for the vehicle routing problem with stochastic demands. Adaptation, Learning, and Optimization, 18, 185–204. https://doi.org/10.1007/978-3-319-14400-9_9

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