By Topic

A new hybrid heuristic technique for solving 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)
Cheng-Fa Tsai ; Dept. of Manage. Inf. Syst., Nat. Pingtung Univ. of Sci. & Technol., Taiwan ; Feng-Cheng Lin

We propose a new and efficient hybrid heuristic scheme for solving job-shop scheduling problems (JSP). A new and efficient population initialization and local search concept, based on genetic algorithms, is introduced to search the solution space and to determine the global minimum solution to the JSP problem. Simulated results imply that the proposed novel JSP method (called the PLGA algorithm) outperforms several currently used approaches. This investigation also considers a real-life job-shop scheduling system design, which optimizes the performance of the job-shop scheduling system subject to a required service level. Simulation results demonstrate that the proposed method is very efficient and potentially useful in solving job-shop scheduling problems

Published in:

Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2003. Proceedings of the Second IEEE International Workshop on

Date of Conference:

8-10 Sept. 2003