【摘要】 针对非线性连续消耗应急物资调度中物资竞争和物资调度费用偏高问题,首先采用基于组合权重的改进灰色关联分析法,确定各个受灾点的物资需求紧迫度,并利用物资需求紧迫度设计了能够反映物资调度效果的物资缺失损失和满意度函数;其次以物资调度总费用最小化和受灾点满意度最大化为优化目标,构建了多受灾点、多出救点、多阶段、多目标的应急物资调度模型.针对该模型多目标的特点,将一种改进多目标粒子群算法(MOPSO)应用于基于Pareto最优解的多目标应急物资调度问题的求解,并通过模型对比实验和算法对比实验,验证了上述模型的合理性与算法的有效性.仿真结果表明,该模型与算法在优先供给需求紧迫度较高受灾点的同时,能够确保其他受灾点的物资供应时延是可接受的,并且获得了较高的满意度与较低的物资调度总费用.更多还原

【Abstract】 In view of material competition and high cost problems in nonlinear continuous consumption emergency material dispatching,the urgency degree of a demand is confirmed using an improved gray relational method based on combination weighting( which is also used to design the disaster site satisfaction coefficient and lack of material loss coefficient). A multi-objective emergency material dispatching model is established for multiple disaster sites,multiple rescue points,and multiple stages,with an aim of minimizing the total dispatching cost and maximizing multiple disaster sites’ satisfaction. In the light of these characteristics of the model,we propose an improved multi-objective particle swarm optimization algorithm based on Pareto dominance. The contrast test of the two models and the contrast test of the two algorithms verified the rationality of the model and the efficiency of the algorithm. Simulation results indicated that the model and algorithm obtained greater satisfaction and lower material dispatching cost,and ensured that disaster sites with higher degree obtained more emergency material and other disaster sites accepted the time delay of material supply.更多还原