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作 者:范志强 梁宁宁 罗一帆 李姗姗 FAN Zhiqiang;LIANG Ningning;LUO Yifan;LI Shanshan(School of Business Administration,Henan Polytechnic University,Jiaozuo,Henan 454003,China;School of Finance and Economics Administration,Henan Polytechnic University,Jiaozuo,Henan 454003,China)
机构地区:[1]河南理工大学工商管理学院,河南焦作454003 [2]河南理工大学财经学院,河南焦作454003
出 处:《工业工程与管理》2024年第2期26-36,共11页Industrial Engineering and Management
基 金:国家社会科学基金资助项目(23BGL058);河南省哲学社会科学规划项目(2022BJJ048);河南省高校基本科研业务费专项资金资助(SKJZD2020-01)。
摘 要:各受灾点因灾情不同对获取不同类别物资的需求紧迫度存在较大差异,忽略这一现实情况的模型会导致有限应急物资无法公平分配和高成本等问题。与已有文献相比,首先,引入了CRITIC法计量各灾点对有限物资需求的波动性与冲突性,提出需求紧迫度量化方法;其次,运用极小极大函数对已有研究的公平目标予以改进;然后,针对突发灾害时长途调运物资的现实情况,采用“储备点-中转站-受灾点”三级结构进行分析;之后,建立了以各灾点最大物资短缺度最小和调度成本最小为目标的多目标混合整数规划模型;最后,利用模糊理论对模型进行等价转化,设计改进遗传算法进行求解。算例分析证明,该模型在保障多受灾点之间物资分配公平性的同时,能够有效控制调度成本,可为现实突发灾害应急物资调度提供决策支持。Each disaster site has its own disaster situation,which leads to great differences in the demand urgency of different types of materials in each disaster site.The model that ignores this reality,will lead to some problems,such as unfair distribution of limited emergency materials and high costs.Firstly,compared with the existing literatures,the CRITIC method was introduced to measure the volatility and conflict of demand for limited supplies at each disaster site,and a demand urgency measurement method was proposed.Secondly,the minimax function was used to improve the fairness objective of the existing research.Thirdly,in view of the reality of long-distance transportation,the three-level structure was adopted for reserve points,transfer stations and disaster sites.Then,a new multi-objective mixed integer programming model was established in order to minimize the maximum material shortage degree of each disaster site and the total cost.Finally,the model was transformed by fuzzy theory and solved by the improved adaptive priority-based genetic algorithm(IAPGA).Experiment results indicate that the model can effectively control the cost and ensure the fairness distribution among all disaster sites,which can provide effective decision support for the emergency material scheduling problem.
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