An efficient multi-objective optimization approach based on the micro genetic algorithm and its application

• Published in: International journal of mechanics and materials in design Vol. 8; no. 1; pp. 37 - 49
• Main Authors: Liu, G. P., Han, X., Jiang, C.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.03.2012
• Subjects: Characterization and Evaluation of Materials; Classical Mechanics; Engineering; Engineering Design; Solid Mechanics; Laminated plates; Multi-objective optimization; Micro genetic algorithm; Non-dominated sorting
• ISSN: 1569-1713; 1573-8841
• DOI: 10.1007/s10999-011-9174-2

In this paper, an efficient multi-objective optimization approach based on the micro genetic algorithm is suggested to solving the multi-objective optimization problems. An external elite archive is used to store Pareto-optimal solutions found in the evolutionary process. A non-dominated sorting is employed to classify the combinational population of the evolutionary population and the external elite population into several different non-dominated levels. Once the evolutionary population converges, an exploratory operator will be performed to explore more non-dominated solutions, and a restart strategy will be subsequently adopted. Simulation results for several difficult test functions indicate that the present method has higher efficiency and better convergence near the globally Pareto-optimal set for all test functions, and a better spread of solutions for some test functions compared to NSGAII. Eventually, this approach is applied to the structural optimization of a composite laminated plate for maximum stiffness in thickness direction and minimum mass.