Faculty of Engineering Science, College of Engineering, University of Tehran, P.O.Box 11365-4563, Tehran, Iran.
Department of Mathematical Sciences, Sharif University of Technology, Tehran, Iran.
Department of Electrical and Electronic Engineering, The University of Manchester, Manchester, U
This paper proposes a novel population-based meta-heuristic optimization algorithm, called Perfectionism Search
Algorithm (PSA), which is based on the psychological aspects of perfectionism. The PSA algorithm takes inspiration from one of the most popular model of perfectionism, which was proposed by Hewitt and Flett. During each iteration of the PSA algorithm, new solutions are generated by mimicking different types and aspects of perfectionistic behavior. In order to have a complete perspective on the performance of PSA, the proposed algorithm is tested with various nonlinear optimization problems, through selection of 35 benchmark functions from the literature. The generated solutions for these problems, were also compared with 11 well-known meta-heuristics which had been applied to many complex and
practical engineering optimization problems. The obtained results confirm the high performance of the proposed
algorithm in comparison to the other well-known algorithms.