CAJ | 학술논문

为了对装配环境下的车间作业进行调度,提出了一种基于可行域搜索的遗传算法.为保证算法在进化过程中染色体始终保持合法性和可行性,在种群的初始化、交叉和变异等阶段,分别设计实现了首代修复算子、可行域交叉算子和可行域变异算子.可行域交叉算子和可行域变异算子的设计组合实现了算法的可行域搜索,减小了搜索空间,省去了复杂的解码修复操作,提高了求解效率,为解决复杂的装配车间调度问题提供了有价值的参考.通过与简单规则、禁忌搜索、普通遗传算法实验结果的比较,验证了所提算法的合理性和优越性.
위료대장배배경하적차간작업진행조도,제출료일충기우가행역수색적유전산법.위보증산법재진화과정중염색체시종보지합법성화가행성,재충군적초시화、교차화변이등계단,분별설계실현료수대수복산자、가행역교차산자화가행역변이산자.가행역교차산자화가행역변이산자적설계조합실현료산법적가행역수색,감소료수색공간,성거료복잡적해마수복조작,제고료구해효솔,위해결복잡적장배차간조도문제제공료유개치적삼고.통과여간단규칙、금기수색、보통유전산법실험결과적비교,험증료소제산법적합이성화우월성.
To solve the Job Shop scheduling problems in assembly environment, a genetic algorithm based on feasible solution space searching named Feasible Solution Space Genetic Algorithm (FSSGA) was proposed. To ensure the validity and feasibility of chromosomes in the whole evolution process, the first generation of repair operator in the stage of population initialization, the feasible crossover operator in the stage of crossover and the feasible mutation operator in the stage of mutation were designed and realized. The combinatorial design of feasible crossover operator and feasible mutation operator realized the feasible solution search of FSSGA, which not only reduced the searching space but also omitted the complex operations of decoding and repairing. FSSGA improved the solution efficiency and provided valuable reference for solving complex assembly Job Shop scheduling problems. The rationality and su-periority of FSSGA was embodied in the comparative experiment of simple rules, tabu search, simple genetic algo-rithm and FSSGA.