A PSO-based procedure for a bi-level multi-objective TOC-based job-shop scheduling problem
by Chompoonoot Kasemset; Voratas Kachitvichyanukul
International Journal of Operational Research (IJOR), Vol. 14, No. 1, 2012

Abstract: This study presents an application of particle swarm optimisation (PSO) algorithm for a bi-level multi-objective job-shop scheduling problem. The bi-level decision-making requirement stems from the concept of theory of constraints. At the first level, the decision is made by concentrating on minimising idle time on the system bottleneck. The second-level decision is made to plan other machines while maintaining the maximum use of the bottleneck and gaining improvements in other performance measures. This paper proposed a PSO-based procedure for solving the bi-level programming problem. The proposed procedure simplifies the solution method by simultaneously providing solutions for the objective of both levels. In addition, during the schedule generation process, the job-shop case applied in this study also considers the machine set-up time, transfer lot size and product demands to make the model more realistic. The numerical examples are given to demonstrate how this approach works. The results from this procedure are compared with the solutions obtained by a commercial optimiser, the LINGO 10 software package. This proposed PSO is implemented in C# programming language in order to obtain the final solution within the short computational time.

Online publication date: Sun, 11-Jan-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Operational Research (IJOR):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com