DocumentCode :
2483537
Title :
Improved immune genetic algorithm for JSP
Author :
Ju, Quanyong ; Zhu, Jianying
Author_Institution :
Sch. of Mechatron. Eng., Jinling Inst. of Technol., Nanjing
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
2642
Lastpage :
2647
Abstract :
According to the information processing mechanism of immune system in life sciences, based on simple genetic algorithm, a new approach of immune genetic algorithm for job shop scheduling is proposed through combining immune algorithm with improved genetic algorithm (strategy of multiple crossover per couple with incest prevention). A immune genetic algorithm aiming at job shop scheduling is set up. The fitness of antibody is increased by injecting vaccinations and degeneration of antibodies is prevented by immune selections. Aiming at the problem of job shop scheduling, the approach of distilling and injecting vaccination is solved, which is difficulty in immune algorithm. The approach is proposed based on antibodypsilas gene segments which are associated with its machine. Finally, convergence efficiency and accuracy of antibodies with immune genetic algorithm in solving ten standard job shop scheduling problems is testified. The results indicate the proposed algorithm is competitive, being able to produce better solutions then other approach.
Keywords :
genetic algorithms; job shop scheduling; antibody; immune genetic algorithm; information processing; job shop scheduling; life sciences; vaccinations; Automation; Genetic algorithms; Genetic engineering; Immune system; Information processing; Intelligent control; Job shop scheduling; Mechatronics; Scheduling algorithm; Space technology; genetic algorithm; immune genetic algorithm; immune system; job shop scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4593340
Filename :
4593340
Link To Document :
بازگشت