By Topic

A Cooperative Coevolutionary Algorithm with Application to Job Shop Scheduling Problem

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

2 Author(s)
Zhou Hong ; School of Economics and Management, Beihang University, Beijing, P.R. China. phone: 086-010-82339458; e-mail: h ; Wang Jian

An improved cooperative coevolutionary algorithm, which aims at solving job shop scheduling problem, is proposed in this paper. According to the number of machines, population is naturally divided into some subpopulations whose individuals encode the preference list of jobs. The proposed algorithm introduces steady-state reproduction to crossover and mutation operators, and inserts some new individuals to the subpopulation at some other generations, and uses the improved preference-list-based G&T algorithm to decode the whole solutions to calculate fitness by three types of cooperative partners, and adopts an innovative updating technique to speed up the convergence. The optimization results of numerical experiments have shown that, the proposed algorithm has outperformed traditional genetic algorithms and showed strong competition with other heuristics

Published in:

2006 IEEE International Conference on Service Operations and Logistics, and Informatics

Date of Conference:

21-23 June 2006