By Topic

Minimizing makespan for parallel batch processing machines with non-identical job sizes using neural nets approach

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

7 Author(s)
Hao Shao ; Dept. of Inf. Manage. & Decision Sci., Univ. of Sci. & Technol. of China, Hefei ; Hua-Ping Chen ; Huang, G.Q. ; Rui Xu
more authors

This paper aims at minimizing the makespan for parallel batch processing machines with non-identical job sizes (NPBM) using neural nets (NN) approach. NN approach was proved effective to solve combinatorial optimization problems but no application to NPBM problems hitherto. This research provides new methods to code the NN with the introduction of Master Weight Matrix (MWM). Computational experiments show that the NN approach outperforms other algorithms in various circumstances.

Published in:

Industrial Electronics and Applications, 2008. ICIEA 2008. 3rd IEEE Conference on

Date of Conference:

3-5 June 2008