Title :
Solving fuzzy job-shop scheduling problem by genetic algorithm
Author :
Li, Junqing ; Xie, Shengxian ; Sun, Tao ; Wang, Yuting ; Yang, Huaqing
Author_Institution :
Sch. of Comput., Liaocheng Univ., Liaocheng, China
Abstract :
In this study, we propose a genetic algorithm for solving the job-shop scheduling problem with fuzzy makespan. The solution in the proposed algorithm is represented by a string of discrete values. The crossover and mutation operators are designed to make the proposed algorithm with high quality exploration and exploitation capability. Experimental results on several random generated cases verified the efficiency and effectiveness of the proposed algorithm.
Keywords :
fuzzy set theory; genetic algorithms; job shop scheduling; crossover operator; discrete values string; exploitation capability; exploration capability; fuzzy job-shop scheduling problem; fuzzy makespan; genetic algorithm; mutation operator; Algorithm design and analysis; Computers; Educational institutions; Genetic algorithms; Job shop scheduling; Process control; Fuzzy processing time; Genetic algorithm; Job shop scheduling problem;
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
DOI :
10.1109/CCDC.2012.6244513
