CAJ | 학술논문

流水车间调度问题是一类传统的生产调度问题，其已被证明是NP-hard问题，而群体智能算法在求解此类问题中表现出优秀的性能。猫群算法是一种较新颖的群体智能算法，将猫群的行为模式分为搜寻模式和跟踪模式，通过一定比例的猫群数量执行两种不同的模式来达到优化的目的。通过将猫群算法与标准粒子群算法和蝙蝠算法在求解流水车间调度问题的结果进行比较，表明了猫群算法在调度问题中的良好优化性能以及应用前景。
류수차간조도문제시일류전통적생산조도문제，기이피증명시NP-hard문제，이군체지능산법재구해차류문제중표현출우수적성능。묘군산법시일충교신영적군체지능산법，장묘군적행위모식분위수심모식화근종모식，통과일정비례적묘군수량집행량충불동적모식래체도우화적목적。통과장묘군산법여표준입자군산법화편복산법재구해류수차간조도문제적결과진행비교，표명료묘군산법재조도문제중적량호우화성능이급응용전경。
Flow-shop Scheduling Problem ( FSP) is a kind of traditional production scheduling problem ,which has been shown to be NP-hard problem ,swarm intelligence algorithm showed excellent performance in solving such problems .Cat swarm optimization is a relatively new swarm intelligence algorithm ,the patterns of behavior of cats is divided into search mode and tracking mode to achieve the purpose of optimization performed by a certain percentage of the number of cats in two different modes .By the results of the comparison with standard particle swarm optimization and bats algorithm for solving the flow shop scheduling problem ,indi-cating that the basic cat swarm optimization scheduling problem in a well-optimized performance and application prospects .