Optimization of Charging/Battery-Swap Station Location of Electric Vehicles with an Improved Genetic Algorithm-Based Model

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 under different charging modes with an improved computing efficiency.The example also proved that meeting more demand for power supply of electric vehicles does not necessarily mean increasing the sites of charging/battery-swap stations.Instead,optimizing the level and location planning of charging/battery-swap stations can maximize the investment profit.The proposed model can provide a reference for the government and enterprises to better plan the location of charging/battery-swap facilities.Hence,it is of both theoretical and practical value.

A geographical information system approach for evaluating the optimum location of point-like facilities in a hierarchical network

Nhis paper discusses a methodology for solving the problem of finding an optimum location for a number of facilities entering an existing hierarchical network.The locational optimization problem is approached with a continuous model.The facilities are considered as point-like.The proposed methodology solves these problems by using Voronoi diagrams to define the catchment area and minimizes the average distance traveled by the users.The approach is implemented by loose coupling between the Directed Tabu Search algorithm for continuous nonlinear optimization with constraints and the Geographical Information System where the cost function is evaluated.In the case study example,facilities operate in a hierarchical network consisting of bank branches and Automated Teller Machines(ATM)of a private Greek bank.A new bank branch location and the insertion of an ATM were examined and compared,providing an improvement of 25.6 and 12.8%,respectively.The proposed approach resulted in visualizing the optimum location on the map,providing the ability to study the modifications that occurred.This could be a useful tool in the hands of practitioners and provide new options in the decision-making process.