By Topic

Mixed-Model Assembly Line Balancing Using the Hybrid Genetic Algorithm

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
$31 $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)
Bai Ying ; Dept. of Electr. Eng., Changzhou Inst. of Machatronic Technol., Changzhou, China ; Zhao Hongshun ; Zhu Liao

In view of the existing problem of mixed-model assembly line balancing, a mathematical model is proposed based on two factors, which are integrated including the workstation number and the assembly line efficiency. Then a new hybrid genetic algorithm is developed for finding optimal solution of the problems. To prevent the premature convergence problem and enhance the globe-optimization capability, GA (genetic algorithms) is combined with SA (simulated annealing algorithms). The results of the simulation indicated that the hybrid algorithm has better efficiency an optimization performance.

Published in:

Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on  (Volume:3 )

Date of Conference:

11-12 April 2009