Simulated annealing approach to minimise total weighted tardiness of non-identical parallel batch processing machines
by Rajani Kakkunuri; Christine Nguyen; Purushothaman Damodaran
International Journal of Industrial and Systems Engineering (IJISE), Vol. 34, No. 3, 2020

Abstract: A variety of industries use batch processing machines (BPMs) that can process multiple jobs simultaneously per machine. This research considers the scheduling of multiple jobs onto non-identical parallel BPMs while minimising the total weighted tardiness. The problem under study is NP-hard and solving it to optimality using a commercial solver requires long run times when the size of the problem increases. A simulated annealing (SA) approach is proposed to find good solutions for large problem instances within short run times. The results obtained are compared to two metaheuristics, particle swarm optimisation (PSO) and differential evolution (DE), proposed in the literature and a commercial solver (CPLEX). An experimental study is conducted to evaluate the different solution approaches on a set of problem instances. Based on results, the authors conclude that SA is highly effective in solving large problem instances within reasonable run times when compared to CPLEX, PSO and DE.

Online publication date: Wed, 11-Mar-2020

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 Industrial and Systems Engineering (IJISE):
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