Seagull optimization algorithm for solving real-world design optimization problems
Natee Panagant, Nantiwat Pholdee, Sujin Bureerat, Khon Kaen, Ali Rıza Yıldız, Sadiq M. Sait
Abstract
Abstract In this research paper, a new surrogate-assisted metaheuristic for shape optimization is proposed. A seagull optimization algorithm (SOA) is used to solve the shape optimization of a vehicle bracket. The design problem is to find structural shape while minimizing structural mass and meeting a stress constraint. Function evaluations are carried out using finite element analysis and estimated by using a Kriging model. The results show that SOA has outstanding features just as the whale optimization algorithm and salp swarm optimization algorithm for designing optimal components in the industry.
Topics & Concepts
MetaheuristicMulti-swarm optimizationMathematical optimizationEngineering optimizationMultidisciplinary design optimizationComputer scienceOptimization problemDerivative-free optimizationOptimization algorithmMeta-optimizationContinuous optimizationShape optimizationTest functions for optimizationFunction optimizationFinite element methodMathematicsEngineeringGenetic algorithmStructural engineeringMultidisciplinary approachSocial scienceSociologyAdvanced Multi-Objective Optimization AlgorithmsMetaheuristic Optimization Algorithms ResearchTopology Optimization in Engineering