By Topic

Hybrid particle swarm optimization for flexible job-shop scheduling problem and its implementation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Xiao-hong Xu ; College of Mechatronics and Automation, National University of Defense Technology, 410073, Changsha, China ; Ling-li Zeng ; Yue-wen Fu

In this paper, a hybrid integer programming model is proposed for flexible job-shop scheduling problem(FJSP). Using crossover operator and mutation operator, the hybrid particle swarm optimization(HPSO) algorithm with basic particle swarm optimization(BPSO) algorithm and genetic algorithm(GA) is employed to solve this problem. Compared with BPSO algorithm, HPSO algorithm has a potential to reach a better optimum. The simulation software for FJSP using HPSO algorithm is designed and implemented based on Object-oriented Programming Language, and the results of simulation indicate that, HPSO algorithm outperforms BPSO algorithm on searching speed for global optimum and avoiding prematurity in solving FJSP.

Published in:

Information and Automation (ICIA), 2010 IEEE International Conference on

Date of Conference:

20-23 June 2010