Constrained Optimization of an I-beam Using Game Theory and Modified Particle Swarm

One of the most important applications of optimization is adjusting parameters of practical engineering problems in order to produce a more desirable outcome. This paper is aimed at promoting Particle Swarm Optimization (PSO) by three effective techniques: (1) assigning special inertia weight to each particle based on the position of particle within the swarm; (2) use of two operators for producing new positions to enhancediversity of solutions and (3) use of learning factors based on the random numbers. To evaluate the accuracy and convergence speed of the proposed method, some well-known PSO algorithms are used for comparison. The results demonstrate that the proposed algorithm is valid to improve PSO. Also, proposed method is used to design an optimal I-beam with two objectives and constraints. The game theory approach is employed to handle objectives. Ultimately, the feasibility and efficiency of the designed beam is assessed in results

کلیدواژه ها:

constrained particle swarm optimization (PSO) ، multi-objective optimization ، I-beam design