Application of cohort intelligence algorithm for goal programming problems with improved constraint handling method
by Aniket Nargundkar; Anand J. Kulkarni
International Journal of Bio-Inspired Computation (IJBIC), Vol. 21, No. 2, 2023

Abstract: Goal programming (GP) is a satisficing-based mathematical modelling technique. In this paper, cohort intelligence (CI) algorithm and its variations are applied to solve a variety of GP problems. The penalty function-based and probability-based constrained handling approaches are applied. Furthermore, a hybridisation of PF and prob-based approaches is developed to handle hard constraints effectively. The proposed approach is validated by solving five benchmark problems as well as practically important real-world truss design, welding beam design, metal cutting, supplier selection, capital budgeting, and staff scheduling problems. The solutions are compared with evolutionary algorithms and LINGO. The results obtained are exceedingly better in terms of satisfying the hard constraints as well as minimising the deviations from the set goals. It is important to note that for truss design, metal cutting and supplier selection problems, all the hard constraints are satisfied using the proposed technique as against with the SA, PSO & Tabu Search.

Online publication date: Thu, 27-Apr-2023

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 Bio-Inspired Computation (IJBIC):
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