Bida Zhang1,*, Qiang Yan1, Hairui Zhang2, Lin Zhang3
CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1177-1194, 2023, DOI:10.32604/cmes.2022.022089
Abstract The joint location planning of charging/battery-swap facilities for electric vehicles is a complex problem. Considering the differences between these two modes of power replenishment, we constructed a joint location-planning model to minimize construction and operation costs, user costs, and user satisfaction-related penalty costs. We designed an improved genetic algorithm that changes the crossover rate using the fitness value, memorizes, and transfers excellent genes. In addition, the present model addresses the problem of “premature convergence” in conventional genetic algorithms. A simulated example revealed that our proposed model could provide a basis for optimized location planning of charging/battery-swapping facilities at different levels… More >
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