By Topic

Using genetic algorithm for job-shop scheduling problems with reentrant product flows

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)
Nose, K. ; Osaka Sangyo Univ., Hyogo, Japan ; Hiramatsu, A. ; Konishi, M.

We describe a job-shop scheduling method using a genetic algorithm for a production system with reentrant product flows. Fundamentally, the scheduling problem is a sequencing problem of operating order for lots on each process or machine. The difficulty in job-shop scheduling problems with reentrant product flows are these two points. The first point is that there are a large number of processes in spite of several process types. The second point is a complex material flow. The problem which we consider is that order restrictions with operating sequences are complicated and enormous. To cope with these problems, we propose coding and decoding methods which include order restrictions easily. To examine the performance of the proposed methods, numerical examples are presented

Published in:

Emerging Technologies and Factory Automation, 1999. Proceedings. ETFA '99. 1999 7th IEEE International Conference on  (Volume:2 )

Date of Conference:

1999