HPDE: A Novel Hybrid PSO-DE Algorithm for Global Optimization Problems

Pravesh Kumara, Millie Pant

Abstract


DE and PSO are population based heuristic search technique which can be used to solve the optimization problems modeled on the concept of Evolutionary Approach. In the present study we proposed a new algorithm based on hybridization of DE and PSO algorithm called Hybrid Particle Swarm Differential Evolution Algorithm (HPDE) for solving global optimization algorithms. The numerical and statistical results are examined on a set of six standard benchmark functions and results are compared with classical DE in term of number of function evaluations (NFE) and average fitness function values. The results show that the HPDE algorithm outperforms the classical DE in term of all considered performance measure.

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