Improved Particle Swarm Optimization Based on Cuckoo Search Operations and Its Application

This paper investigates Cuckoo Search Algorithm and find how to apply its operations to improve the optimization performance of Particle Swarm Optimization. It studies the effects of levy flight and random search, which are two important operations of Cuckoo search algorithm. An improved particle swarm optimization is proposed based on levy flight and rand search. To validate the optimization performance of the proposed technique some simulations have been done based on 10 benchmark functions and the results analysed. Moreover, the improved particle swarm optimization is applied to solve five different cases of economic dispatch problems comprising 6, 13, 15, 40, and 140 generating units, which involve different types of equality and inequality constraints. The results obtained with the new algorithm shows a remarkable improvement compared to the original one.