Mechanical Engineering, Isfahan University of Technology
Abstract
Many engineering design problems involve a combination of both continuous anddiscrete variables. However, the number of studies scarcely exceeds a few on mixed-variableproblems. In this research Particle Swarm Optimization (PSO) algorithm is employed to solve mixedvariablenonlinear problems. PSO is an efficient method of dealing with nonlinear and non-convexoptimization problems. In this paper, it will be shown that PSO is one of the best optimizationalgorithms for solving mixed-variable nonlinear problems. Some changes are performed in theconvergence criterion of PSO to reduce computational costs. Two different types of PSO methods areemployed in order to find the one which is more suitable for using in this approach. Then, severalpractical mechanical design problems are solved by this method. Numerical results show noticeableimprovements in the results in different aspects.
Mohagheghian, I., & Nahvi, H. (2011). A Particle Swarm Optimization Algorithm for Mixed-Variable Nonlinear Problems. International Journal of Engineering, 24(1), 65-78.
MLA
Iman Mohagheghian; Hassan Nahvi. "A Particle Swarm Optimization Algorithm for Mixed-Variable Nonlinear Problems". International Journal of Engineering, 24, 1, 2011, 65-78.
HARVARD
Mohagheghian, I., Nahvi, H. (2011). 'A Particle Swarm Optimization Algorithm for Mixed-Variable Nonlinear Problems', International Journal of Engineering, 24(1), pp. 65-78.
VANCOUVER
Mohagheghian, I., Nahvi, H. A Particle Swarm Optimization Algorithm for Mixed-Variable Nonlinear Problems. International Journal of Engineering, 2011; 24(1): 65-78.
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