Abstract
in the present study we propose a new hybrid version of Differential Evolution (DE) and Particle Swarm Optimization (PSO) algorithms. In the proposed algorithm named as Hybrid Differential Evolution (HDE) a ‘switchover constant’ called α is defined. HDE starts as the basic DE algorithm which switches over to PSO when α is activated. The constant α on the other hand is activated at a point where the DE procedure usually slows down which is usually in the proximity of global optimal i.e. to say when the search domain is contracted around the global optimal. Experimenting with a test bed of 12 benchmark functions, we show the promising nature of the proposed HDE algorithm.
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