Collaborative Optimization of Charging Network and Charging Strategy with Practical Battery Wear Model
Electric vehicles(EVs)have attracted increasing attention in the field of logistics owing to the strong support received from the government and the continuous increase in social environmental awareness.Compared to traditional logistics vehicles,EVs have additional charging costs such as charging time cost and battery wear cost.In this study,the routing problem of EVs is formulated as an integer programming model based on a nonlinear charging model and a practical battery wear model.Subsequently,a three-phase algorithm called SIGALNS is proposed for solving it.Based on the proposed model,a series of instances are generated showing the benefits of combining charging time,battery wear and distribution.Finally,sensitivity analyses are systematically conducted on wearing cost and charging time under a realistic background.The results show that the optimal planning of an EV network considering time and wear costs is in line with the practical needs of EV logistics enterprises;this can help reduce operating costs.The results of this paper demonstrate the impact of charging strategy on the cost of electric logistics vehicle logistics service network from a practical perspective,and propose a collaborative optimization scheme of distribution scheduling and charging plan to reduce the comprehensive operating cost of enterprises.The models and algorithms proposed in this study can provide a decision-making basis for logistics enterprises that use electric logistics vehicles as delivery vehicles to make operational decisions.
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