Title :
Immune genetic algorithm for flexible job-shop scheduling problem
Author :
Ma, Jia ; Zhu, Yunlong ; Shi, Gang
Author_Institution :
Shenyang Inst. of Autom., Chinese Acad. of Sci., Shenyang, China
Abstract :
An kind of immune genetic algorithm(IGA) is proposed for solving the flexible job-shop scheduling problem(FJSP). Based on the globalsearching method of classic genetic algorithm (SG), and using the diversity preservation strategy of antibodies in biology immunity mechanism, the method greatly improves the colony diversity of GA and compared to genetic algorithm. The results show that immune genetic algorithm performs better in aspect of global and local search ability and search speed.
Keywords :
genetic algorithms; job shop scheduling; search problems; biology immunity mechanism; colony diversity; diversity preservation strategy; flexible job-shop scheduling problem; global searching method; immune genetic algorithm; Immune system; Job shop scheduling; Planning; Processor scheduling; Turning; Vaccines; FJSP; immune genetic algorithm; immune operator; resource constrained;
Conference_Titel :
Automation and Logistics (ICAL), 2010 IEEE International Conference on
Conference_Location :
Hong Kong and Macau
Print_ISBN :
978-1-4244-8375-4
Electronic_ISBN :
978-1-4244-8374-7
DOI :
10.1109/ICAL.2010.5585331
