Cohort intelligence algorithm for discrete and mixed variable engineering problems. Issue 6 (2nd November 2018)

• Record Type: Journal Article
• Authors: Kale, Ishaan R.; Kulkarni, Anand J.
• Is Part Of: International journal of parallel, emergent and distributed systems. Volume 33:Issue 6(2018)
• Page Start: 627
• Page End: 662
• Publication Date: 2018-11-02
• Subjects: Cohort Intelligence -- discrete and mixed variable problems -- truss optimization -- mechanical engineering design problems -- metaheuristic algorithms -- nonlinear constrained optimization; Parallel computers -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; Computer algorithms -- Periodicals; 004.35
• DOI: 10.1080/17445760.2017.1331439
• Languages: English
• ISSNs: 1744-5760

Abstract

Abstract: In this study, the performance of an emerging socio inspired metaheuristic optimization technique referred to as Cohort Intelligence (CI) algorithm is evaluated on discrete and mixed variable nonlinear constrained optimization problems. The investigated problems are mainly adopted from discrete structural optimization and mixed variable mechanical engineering design domains. For handling the discrete solution variables, a round off integer sampling approach is proposed. Furthermore, in order to deal with the nonlinear constraints, a penalty function method is incorporated. The obtained results are promising and computationally more efficient when compared to the other existing optimization techniques including a Multi Random Start Local Search algorithm. The associated advantages and disadvantages of CI algorithm are also discussed evaluating the effect of its two parameters namely the number of candidates, and sampling space reduction factor. Abstract : Graphical representation of Cohort Intelligence Algorithm