CAJ | 학술논문

针对柔性作业车间调度求解问题，提出一种新型混合蜂群智能优化算法。该算法采用独特的编码方式和位置更新策略来避免不合法解的产生，在蜂群算法的基础上增加了有利于局部搜索的混沌算子提高了算法搜索精度，实现了全局搜索与局部搜索能力的有效平衡。最后将此算法在不同规模的实例上进行了仿真测试，并与最近提出的其他几种具有代表性的算法进行了比较，验证了该算法的有效性和优越性。
침대유성작업차간조도구해문제，제출일충신형혼합봉군지능우화산법。해산법채용독특적편마방식화위치경신책략래피면불합법해적산생，재봉군산법적기출상증가료유리우국부수색적혼돈산자제고료산법수색정도，실현료전국수색여국부수색능력적유효평형。최후장차산법재불동규모적실례상진행료방진측시，병여최근제출적기타궤충구유대표성적산법진행료비교，험증료해산법적유효성화우월성。
A novel hybrid artificial bee colony optimization algorithm( HABC) is presented for flexible Job-shop Scheduling Problem. This algorithm applies the novel coding mode to scheduling problem directly,and uses the chaotic operator in ABC algorithm to improve the search precision. The simulation results of some classical Job-shop scheduling problems and instance demonstrated that the proposed algorithm could effectively overcome the early-maturing and improve global search capability. Compared to other algorithms,the optimal solution or near optimal solution obtained by the proposed algorithm was better.