摘要
利用仿真工具将启发式方法与遗传算法相结合 ,提出了一种求解 Job Shop排序问题的混合算法框架 ,利用启发式规则引导遗传搜索过程 ,以提高遗传算法的求解效率。在求解过程中 ,遗传算法仅对每台机器的第 1道工序搜索寻优 ,通过仿真过程安排后续工序 ,在仿真过程中 ,利用启发式规则确定工件的加工优先级。在以上框架基础上 ,针对含调整时间的作业排序问题建立了一种混合算法 GA-SPTS,通过与已有算法的比较表明 ,该算法对这类问题具有很好的求解性能。
A hybrid algorithm framework was proposed for job shop scheduling, with which heuristic rules were integrated with genetic algorithm (GA) by means of simulation. With the framework, the searching efficiency of GA can be improved due to the guidance of the heuristic rules designed for the specific problems. The hybrid algorithm was implemented by optimizing the first operation of each machine with GA and arranging the successive operations through a simulation process in which heuristic rules were employed to determine the processing priority of jobs. Based on the framework, an algorithm called GA-SPTS was developed for job shop scheduling problems with sequence-dependent setup times, which shows high performance as compared with the existing algorithms.
出处
《航空学报》
EI
CAS
CSCD
北大核心
2001年第2期180-183,共4页
Acta Aeronautica et Astronautica Sinica
基金
国家自然科学基金!(79970 0 5 4)
航空基础科学基金!(99J5 10 68)
