CAJ | 학술논문

为使JIT生产模式下多车间混流装配线敏捷、高效地运行，研究了具有供需关系的多车间混流装配线计划排序问题。以JIT车间混流装配线上车型切换次数、关键件型号切换次数、车身喷涂颜色变化和违反选装件的选装频率次数最少为优化目标，采用加权平均法建立了多目标优化数学模型。针对遗传算法容易陷入局部最优和提前收敛的问题，提出了求解多车间混流装配计划排序的自适应遗传算法。通过交叉概率和变异概率的自适应调整、局部寻优和保优策略，提高了算法的寻优能力。最后通过算例验证了算法的有效性。
위사JIT생산모식하다차간혼류장배선민첩、고효지운행，연구료구유공수관계적다차간혼류장배선계화배서문제。이JIT차간혼류장배선상차형절환차수、관건건형호절환차수、차신분도안색변화화위반선장건적선장빈솔차수최소위우화목표，채용가권평균법건립료다목표우화수학모형。침대유전산법용역함입국부최우화제전수렴적문제，제출료구해다차간혼류장배계화배서적자괄응유전산법。통과교차개솔화변이개솔적자괄응조정、국부심우화보우책략，제고료산법적심우능력。최후통과산례험증료산법적유효성。
In order to agile and efficient operation of mixed-model assembly line’ s sorting of multiple work-shop based on JIT, this essay research the supply and demand between the multiple workshop. Multi-objec-tive was present:minimizing model switching times, key-module type switching, color switching times and violating optional frequency. Then the weighted average method was used to build the multi-objective mathe-matical model. The paper presents the adaptive genetic algorithm to solve mixed-model assembly line’ s Sor-ting of multiple workshops, which according to genetic algorithm easy to fall into local optimum and conver-gence problems in advance. Improving the searching capability of the algorithm which by means of adaptive crossover and mutation, local optimization and optimal policy. Finally use example to verify the efficiency of the algorithm.