CAJ | 학술논문

围绕突发事件应急的特点，建立了运输成本最小、延误时间最短的多目标数学模型。通过范数理想点将多目标模型转化为单目标模型。设计粒子群优化算法，采用将学习因子、惯性权重设为线性变化和增加局部扰动的方式，建立了针对性的优化算法。结合实际应急案例进行了数值实验与案例分析，证明了算法的有效性，从而为应急条件下的物资调度提供了有效和可靠的方法。
위요돌발사건응급적특점，건립료운수성본최소、연오시간최단적다목표수학모형。통과범수이상점장다목표모형전화위단목표모형。설계입자군우화산법，채용장학습인자、관성권중설위선성변화화증가국부우동적방식，건립료침대성적우화산법。결합실제응급안례진행료수치실험여안례분석，증명료산법적유효성，종이위응급조건하적물자조도제공료유효화가고적방법。
For the problem of emergency supply scheduling , it should minimize both transportation cost and time delay .A multi-objective optimization model is established for this problem .This model is conver-ted to a single objective model by using technique for order preference by similarity to ideal solution . Then, particle swarm optimization algorithm is designed to solve the problem by setting learning factor and inertia weight to linear and increasing local perturbation .With the help of an empirical analysis in combi-nation with the example , the algorithm is proved suitable and valid .This is an effective and reliable ap-proach for emergency supply scheduling .