A goal programming embedded genetic algorithm for multi-objective manufacturing cell design Online publication date: Wed, 05-Dec-2018
by Barnali Chaudhuri; R.K. Jana; Dinesh K. Sharma; P.K. Dan
International Journal of Applied Decision Sciences (IJADS), Vol. 12, No. 1, 2019
Abstract: In this paper, a multi-objective manufacturing cell design problem is studied. A goal programming (GP) embedded real-coded genetic algorithm (GA) is designed for solving this problem. Initially, the GA is used to obtain the individual minimum of each objective. Thereafter, utilising the concepts of GP, an equivalent problem is derived, and the sum of deviation variables associated with the objectives are minimised. The GA is used further to obtain the optimal cell design. A software toolkit is developed based on the proposed technique using C Sharp.net to ensure its use in a larger scale. The effectiveness of the technique is judged based on a set of test problems of different sizes. The proposed technique is found to be better in terms of the performance measure over the existing ones.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
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 Applied Decision Sciences (IJADS):
Login with your Inderscience username and 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