Hybrid Particle Swarm Optimization with Artificial Bee Colony Optimization for Topology Control Scheme in Wireless Sensor Networks

Abstract

Easy convergence to a local optimum, rather than global optimum, could unexpectedly happen in both multimodal optimization problems and complex constrained optimization problems. The enhanced diversity agent in optimal algorithms is one of the solutions to this issue. In this paper, a novel optimization algorithm based on hybrid Particle Swarm Optimization (PSO) with Artificial Bee Colony optimization (ABC) is proposed to solve the complex constrained optimization problems of topology control in wireless sensor networks (WSN). A new communication strategy for hybrid PSO with ABC (HPAO) is to take advantages of the strength points of each side type of algorithms to explore and exploit the algorithm diversity. Six benchmark functions are used to verify the convergence behavior, the accuracy, and the speed of the proposed algorithm. Experimental results show that the proposal increases the accuracy more than 42.1% and 16.3% with respect to PSO and ABC.