An Improved Clonal Selection Algorithm for Job Shop Scheduling

The job shop scheduling problem (JSSP) is a notoriously difficult problem in combinatorial optimization. Extensive investigation has been devoted to developing efficient algorithms to find optimal or near-optimal solutions. This paper proposes an improved immune clonal selection algorithm, called im...

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Bibliographic Details
Published in2009 International Symposium on Intelligent Ubiquitous Computing and Education : 15-16 May 2009 pp. 34 - 37
Main Authors Hong Lu, Jing Yang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2009
Subjects
artificial immune systems
clonal selection algorithm
Engineering management
Immune system
Industrial engineering
Job shop scheduling
job shop scheduling problem
Manufacturing
Optimal scheduling
Pervasive computing
Processor scheduling
Resource management
Scheduling algorithm
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ISBN9780769536194
0769536190
DOI10.1109/IUCE.2009.26

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Summary:The job shop scheduling problem (JSSP) is a notoriously difficult problem in combinatorial optimization. Extensive investigation has been devoted to developing efficient algorithms to find optimal or near-optimal solutions. This paper proposes an improved immune clonal selection algorithm, called improved clonal selection algorithm for the JSSP. The new algorithm has the advantage of preventing from prematurity and fast convergence speed. Numerous well-studied benchmark examples in job-shop scheduling problems were utilized to evaluate the proposed approach. The computational results show that the proposed algorithm could obtain the high-quality solutions within reasonable computing times, and the results indicate the effectiveness and flexibility of the immune memory clonal selection algorithm.
ISBN:9780769536194
0769536190
DOI:10.1109/IUCE.2009.26