A modified firefly algorithm based on neighborhood search
Gan Yu · Concurrency and Computation Practice and Experience · 2020
Summary Firefly algorithm (FA) is a new member of intelligent optimization algorithms. Several studies demonstrated that FA could successfully deal with several engineering and theoretical optimization problems. Nevertheless, there are some weak points in FA, such as parameter dependence and high computational complexity. To overcome the above issues, this paper proposes a modified FA based on neighborhood search (MFANS). In MFANS, there are three modifications. First, a modified attraction strategy is employed to reduce the complexity. Then, a neighborhood search method is used to search around the best neighborhood solutions. Third, the step parameter is dynamically adjusted. Performance of MFANS is compared with two improved FAs. Results show the effectiveness of MFANS.