Artificial Plant Optimization Algorithm with Dynamic Local Search for Optimal Coverage Configuration

摘要

Artificial plant optimization algorithm (APOA) is a novel stochastic population-based evolutionary algorithm by simulating the plant growing process. However, the exploitation capability of APOA is not enough. Therefore, in this paper, a new dynamic local search strategy is designed and incorporated into methodology of APOA. To illustrate the efficiency, this new variant is applied to solve the optimal coverage configuration problem in wireless sensor networks, simulation results show the validity of this variant.