Vector optimisation using fuzzy preference in evolutionary strategy based firefly algorithm (Q2627360)

Summary: 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.