A New Adaptive Genetic Algorithm for Job-Shop Scheduling
2009 ◽
Vol 626-627
◽
pp. 771-776
Keyword(s):
Job Shop
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In order to minimize makespan for job-shop scheduling problem (JSP), an improved adaptive genetic algorithm (IAGA) based on hormone modulation mechanism is proposed. This algorithm has characteristics with avoiding overcoming premature phenomenon and slow evolution. The proposed IAGA algorithm is applied to dynamic job-shop scheduling problem (DJSP) and the satisfied result is obtained. By employing the proposed IAGA, machines can be used more efficiently, which means that tasks can be allocated appropriately, production efficiency can be improved, and the production cycle can be shortened efficiently. Therefore it embodies good adaptation to the DJSP (rush order, machine malfunction, and so on).
2014 ◽
Vol 989-994
◽
pp. 2609-2612
2011 ◽
Vol 38
(6)
◽
pp. 7243-7250
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2013 ◽
Vol 401-403
◽
pp. 2037-2043
2021 ◽
Vol 1879
(2)
◽
pp. 022078