Yang Yun, Ma Changxi, Ling Gang
School of Traffic and Transportation, Lanzhou Jiaotong University, An'ning West Rd., #88, Lanzhou, Gansu Province, 730070, China.
Physica A. 2022 Jul 1;597:127291. doi: 10.1016/j.physa.2022.127291. Epub 2022 Mar 25.
In order to avoid the huge hidden dangers caused by emergencies, it is particularly vital to make a reasonable pre-location and layout of emergency logistics facilities. A multi-objective pre-location model of temporary distribution station for emergency materials was built, which considered the problems of information shortage and uncertain demand after the incident with minimum time, maximum time satisfaction, minimum delivery cost and psychological trauma to the masses. The priority of candidate points was solved by comprehensive evaluation methods, the nominal demand of served points was estimated by triangular fuzzy number theory (TFN), and the location model was solved by non-dominated sorting genetic algorithm. In addition, the optimal schemes without priority and considering it were compared and analyzed, the practicability of the model is verified by concrete examples. The results show the time and cost reduction of 7.754% and 25.651%, an increment of total satisfaction value of the scheme considering location priority. Therefore, the model and algorithm provide theoretical support and practical ideas for solving the location problem, which can better complete the task of the location problem for temporary distribution stations of urban emergency materials.
为避免突发事件造成的巨大隐患,对应急物流设施进行合理的预先选址与布局尤为重要。构建了应急物资临时配送站多目标选址模型,该模型考虑了事件发生后信息短缺和需求不确定的问题,以时间最短、时间满意度最高、配送成本最低以及对群众心理创伤最小为目标。通过综合评价方法求解候选点的优先级,利用三角模糊数理论(TFN)估计服务点的名义需求,并采用非支配排序遗传算法求解选址模型。此外,对有无优先级的最优方案进行了比较分析,通过具体实例验证了模型的实用性。结果表明,时间和成本分别降低了7.754%和25.651%,考虑选址优先级的方案总满意度值有所提高。因此,该模型和算法为解决选址问题提供了理论支持和实践思路,能够更好地完成城市应急物资临时配送站的选址任务。