Abstract

Due to the lack of medical materials in some emergency public events, for example, the outbreak of COVID-19, it is urgent to establish a medical emergency material warehouse. Taking Xi’an, China, as an example, this study aims to select suitable sites of Xi’an medical emergency material warehouse. In this study, the problem of site selection models as a multiobjective optimization problem. The coverage function and comprehensive efficiency function are designed as two conflicting objectives. Then, a multiobjective evolutionary algorithm based on multiple memetic direction is proposed to optimize the two objectives concurrently. The crossover and mutation operators are designed for evolutionary multiobjective site selection. The proposed crossover operator is able to balance the global and local search abilities, and the proposed mutation operator fuses the distribution information of hospital location, service population, and the overall coverage. Experiments on real dataset verify the superiority of the proposed evolutionary multiobjective site selection method.

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