A new blend of DE and PSO algorithms for global optimization problems

Abstract

Differential Evolution (DE) and Particle Swarm Optimization (PSO) algorithms have gained a lot of popularity in the last few years for solving complex optimization problems. Several variants of both the algorithms are available in literature. One such variation is combining the two algorithms in a manner so as to develop an algorithm having positive features of both the algorithms. In the present study we propose a hybrid of DE and PSO algorithm called Mixed Particle Swarm Differential Evolution Algorithm (MPDE) for solving global optimization algorithms. The numerical and statistical results evaluated on a set of benchmark functions show the competence of the proposed algorithm. Further, the proposed algorithm is applied to a practical problem of determining the location of the earthquakes in the Northern Himalayan and Hindu Kush regions of India. © 2011 Springer-Verlag.