DocumentCode :
2760093
Title :
An Immune-Genetic Algorithm for Dynamic Job-Shop Scheduling
Author :
Chai, Yong-Sheng ; Zhou, Yu-lan ; Chen, Yibao ; Zhu, Bin
Author_Institution :
Machinery Coll., Yantai Univ.
Volume :
2
fYear :
0
fDate :
0-0 0
Firstpage :
7338
Lastpage :
7342
Abstract :
An immune genetic algorithm (IGA) was proposed for dynamic job-shop scheduling. By introducing mechanism of immunity into genetic algorithm, such as injecting vaccines and controlling antibody-concentration, the problems on easy appeared precocity and low searching efficiency were avoided. Taking account of the capacity of machines, the algorithm can deal with the problem of job-shop dynamic scheduling or rescheduling. Also, for lessening calculation time, parameters of IGA were gained by vast tests based on known researches. By appointing a new scheduling-time or releasing the resources of machines, the algorithm ensured the consistency to the rescheduling. At last, one instance was analyzed and realized to show that the result of the scheduling is reliable
Keywords :
computational complexity; genetic algorithms; job shop scheduling; antibody-concentration control; dynamic job-shop scheduling; immune genetic algorithm; machine capacity; vaccines injection; Algorithm design and analysis; Dynamic scheduling; Educational institutions; Genetic algorithms; Heuristic algorithms; Machinery; Neural networks; Scheduling algorithm; Testing; Vaccines; capacity of machine; dynamic scheduling; immune genetic algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
Type :
conf
DOI :
10.1109/WCICA.2006.1714511
Filename :
1714511
Link To Document :
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