Title :
New particle swarm algorithm for job shop scheduling problems
Author :
Song, Xiaoyu ; Chang, Chunguang ; Cao, Yang
Author_Institution :
Sch. of Inf. & Control Eng., Shenyang Jianzhu Univ., Shenyang
Abstract :
A new particle swarm algorithm is proposed to make up for the drawback of conventional one on solving job shop scheduling problem, and improve the performance of searching solutions. In the new algorithm, the particle swarm algorithm is adopted to search in the solution space globally. According to the feature of job shop problem solutions, a critical operation-based selection method is proposed, and the TS algorithm based on it is adopted as the local algorithm to strengthen the capability of local search. The new particle swarm algorithm has been tested with 13 hard benchmark problems. The result demonstrates that the obtained best solution and the average value of ten times result are better than parallel genetic algorithm and taboo search algorithm. So the validity of the proposed new particle swarm algorithm is validated.
Keywords :
job shop scheduling; particle swarm optimisation; search problems; critical operation-based selection method; job shop scheduling problems; particle swarm algorithm; Automation; Benchmark testing; Constraint optimization; Control engineering; Genetic algorithms; Intelligent control; Job shop scheduling; Manufacturing systems; Particle swarm optimization; Scheduling algorithm; Hybrid algorithm; Job shop scheduling; Particle swarm algorithm; Taboo search;
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
DOI :
10.1109/WCICA.2008.4593568