【摘要】 修复约束满足算法(修复法)是在完整初始解的基础上不断对变量进行修复,最终得到可行解.对此,提出一种求解flow shop排序问题的改进修复法(IRCS_WT),通过采用新的变量表达方式,设计了一种以启发式优化规则为指导的变量选择算法(LWT),并采用一种变量互换算法(LTEE)保证算法的全局搜索性能.将新算法应用于31个标准算例,与传统算法及遗传算法的优化结果进行比较,结果表明在相同运算时间下改进算法具有明显的优越性.更多还原

【Abstract】 Repair-based constraint satisfaction method is one of the two main categories of constraint satisfaction(CS) algorithms.It starts with an arbitrary completed solution,and then resolves conflicts by local repair.An improved repair-based constraint satisfaction(IRCS_WT) method for flow shop scheduling is proposed.In IRCS_WT,a heuristic rule of largest weighted tardiness priority(LWT) is proposed for variables ordering procedure,and a new heuristic of largest tardy and early variables exchanging(LTEE) is designed to escape from local optima.Computational experiments of 31 flow shop scheduling problems are conducted to compare the IRCS_WT with other two heuristic methods,extended NEH and filtered beam search(FBS),as well as genetic algorithm(GA).The results show that IRCS_WT significantly outperforms the competitors with the same running time.更多还原