Title :
Solving the Flexible Job Shop Scheduling Problems Based on the Adaptive Genetic Algorithm
Author :
Wei, Qiao ; Qiaoyun, Li
Author_Institution :
Lab. & Equip. Manage. Office, Shandong Univ. at Weihai, Weihai, China
Abstract :
Considering the flexible job shop scheduling problem (FJSSP) more accorded with practice, a correspondent model is established and the adaptive genetic algorithm is used to solve it. According to the features of the model (machines are optional), three factors: the processing time, the completion time of previous operation and the idle time of current machine are synthetically considered for choosing a suitable machine in the decoding process of the chromosomes. The simulating experiments demonstrate that the proposed scheduling algorithm can get better solutions than previous algorithms in large scale FJSSP.
Keywords :
decoding; genetic algorithms; job shop scheduling; adaptive genetic algorithm; chromosomes; completion time; decoding process; flexible job shop scheduling problem; idle time; processing time; Application software; Biological cells; Computer applications; Decoding; Engineering management; Equations; Genetic algorithms; Job shop scheduling; Large-scale systems; Scheduling algorithm; Adaptive Genetic Algorithm; Flexible; Job Shop Scheduling Problem; Machine;
Conference_Titel :
Computer Science-Technology and Applications, 2009. IFCSTA '09. International Forum on
Conference_Location :
Chongqing
Print_ISBN :
978-0-7695-3930-0
Electronic_ISBN :
978-1-4244-5423-5
DOI :
10.1109/IFCSTA.2009.30
