An Enhanced Opposition-based Firefly Algorithm for Solving Complex Optimization Problems
Ling Ai Wong, Hussain Shareef, Azah Mohamed, Ahmad Asrul Ibrahim
Corresponding author (email) : ling_ai89@hotmail.com
Abstract
Firefly algorithm is one of the heuristic optimization algorithms which mainly based on the light intensity and the attractiveness of firefly. However, firefly algorithm has the problem of being trapped in local optimum and slow convergencerates due to its random searching process. This study introduces some methods to enhance the performance of original firefly algorithm. The proposed enhanced opposition firefly algorithm (EOFA) utilizes opposition-based learning in population initialization and generation jumping while the idea of inertia weight is incorporated in the updating of firefly’s position. Fifteen benchmark test functions have been employed to evaluate the performance of EOFA. Besides, comparison has been made with another existing optimization algorithm namely gravitational search algorithm (GSA). Results show that EOFA has the best performance comparatively in terms of convergence rate and the ability of escaping from local optimum point.
Keywords : Enhanced opposition-based firefly algorithm; heuristic optimization
Abstrak
Algoritma kelip adalah salah satu algoritma pengoptimuman heuristik berdasarkan keamatan cahaya dan daya tarikan kelip-kelip. Walau bagaimanapun, algoritma kelip mempunyai masalah terperangkap pada optimum setempat dan kadar penumpuan yang perlahan dalam proses capaian rawak. Kajian ini memperkenalkan beberapa kaedah bagi meningkatkan prestasi asal algoritma kelip. Algoritma kelip berasaskan teori tentangan (EOFA) yang dicadangkan adalah berasaskan teori tentangan dan fungsi berat inersia. Lima belas fungsi ukur rujuk telah digunakan bagi menilai prestasi EOFA. Disamping itu, perbandingan juga dilakukan di antara algoritma pengoptimuman sedia ada seperti algoritma pencarian graviti. Keputusan menunjukkan bahawa EOFA mempunyai prestasi yang terbaik dari segi kadar penumpuan dan keupayaan melepaskan diri daripada titik optimum setempat.
Kata kunci: Algoritma kelip berasaskan teori tentangan; pengoptimuman heuristik