Firefly algorithm with dynamic attractiveness model and its application on wireless sensor networks

Abstract

Firefly algorithm (FA) is a new population-based meta-heuristic algorithm which has outstanding performance on many optimisation problems. However, in standard FA, the attractiveness quickly approaches a constant in the middle period of the iterations. It may be very detrimental to the search ability of the algorithm. So we propose a new variant FA (DFA) with a dynamic attractiveness model which can linearly adjust the rate of change of attractiveness as the number of iterations grows. Thirteen well-known benchmark functions are used to verify the performance of our proposed method; the computational results show that DFA is more efficient than many other FA algorithms. We also successfully used DFA to solve the wireless sensor network node distribution optimisation problem; the results of the coverage statistics further validate the effectiveness of the proposed algorithm.