Authors: Surafel Luleseged Tilahun; Hong Choon Ong
Addresses: School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM Penang, Malaysia. ' School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM Penang, Malaysia
Abstract: Solving vector optimisation entails the conflict among component objectives. The best solution depends on the preference of the decision-maker. Firefly algorithm is one of the recently proposed metaheuristic algorithms for optimisation problems. In this paper, the random movement of the brighter firefly is modified by using (1 + 1)-evolutionary strategy to identify the direction in which the brightness increases. We also show how to generate a dynamic weight for each component of the vector by using a fuzzy trade-off preference. This dynamic weight will be imbedded in computing the intensity of light of fireflies in the algorithm. From the simulation results, it is shown that using fuzzy preference is promising to obtain solutions according to the given fuzzy preference. Furthermore, simulation results show that the evolutionary strategy based firefly algorithm performs better than the ordinary firefly algorithm.
Keywords: vector optimisation; fuzzy preference; firefly algorithm; evolutionary strategy; light intensity; simulation.
International Journal of Operational Research, 2013 Vol.16 No.1, pp.81 - 95
Published online: 01 Nov 2012 *Full-text access for editors Access for subscribers Purchase this article Comment on this article