Truss topology, shape and sizing optimization by fully stressed design based on hybrid grey wolf optimization and adaptive differential evolution. Issue 10 (3rd October 2018)

• Record Type: Journal Article
• Authors: Panagant, Natee; Bureerat, Sujin
• Is Part Of: Engineering optimization. Volume 50:Issue 10(2018)
• Page Start: 1645
• Page End: 1661
• Publication Date: 2018-10-03
• Subjects: Truss optimization -- differential evolution -- grey wolf optimization -- hybrid evolutionary algorithms -- adaptive evolutionary algorithms -- fully stressed design; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2017.1417400
• Languages: English
• ISSNs: 0305-215X

Abstract

ABSTRACT: A hybrid adaptive optimization algorithm based on integrating grey wolf optimization into adaptive differential evolution with fully stressed design (FSD) local search is presented in this article. Hybrid reproduction and control parameter adaptation strategies are employed to increase the performance of the algorithm. The proposed algorithm, called fully stressed design–grey wolf–adaptive differential evolution (FSD-GWADE), is demonstrated to tackle a variety of truss optimization problems. The problems have mixed continuous/discrete design variables that are assigned as simultaneous topology, shape and sizing design variables. FSD-GWADE provides competitive results and gives superior results at a higher success rate than the previous FSD-based algorithm.