Structural design with dynamic constraints using weighted chaos game optimization. Issue 6 (20th September 2022)

• Record Type: Journal Article
• Authors: Goodarzimehr, Vahid; Talatahari, Siamak; Shojaee, Saeed; Hamzehei-Javaran, Saleh; Sareh, Pooya
• Is Part Of: Journal of computational design and engineering. Volume 9:Issue 6(2022)
• Page Start: 2271
• Page End: 2296
• Publication Date: 2022-09-20
• Subjects: chaos game optimization -- dynamic constraint -- truss structure -- metaheuristic algorithm -- soft computing -- inertia weight; Engineering -- Data processing -- Periodicals; Computer-aided design -- Periodicals; Computer-aided design; Engineering -- Data processing; Electronic journals; Electronic journals; Periodicals; 620.0042
• DOI: 10.1093/jcde/qwac099
• Languages: English
• ISSNs: 2288-4300

Abstract

Abstract: The chaos game optimization (CGO) algorithm is a recently developed metaheuristic inspired by chaos theory and fractal configurations. In CGO, possible optimal solutions are defined as seeds and the searching process is performed using some simple equations. In this paper, weighted chaos game optimization (WCGO) is proposed and implemented to optimize engineering structures with dynamic constraints. In this method, an inertia weight coefficient based on the minimum and maximum values ​​of the objective function is introduced to create a better balance between exploration and exploitation during the searching process. By applying the inertia weight coefficient to the seeds, their positions can be controlled accurately. To evaluate the performance of WCGO, a wide range of mathematical benchmark functions, as well as several structural design optimization problems under dynamic constraints, are computationally investigated using the new algorithm. In order to demonstrate the efficiency and robustness of WCGO, its results have been compared with those obtained by some conventional methods from the literature. Additionally, a Friedman rank test is conducted to perform a statistical study on the performance of the considered algorithms. The findings indicate that WCGO performs better than its rivals in solving these structural optimization problems with dynamic constraints. Graphical Abstract: