Fuzzy Krill Herd optimization algorithm
Edris Fattahi, Mahdi Bidar, Hamidreza Rashidy Kanan · 2014
The Standard Krill Herd(SKH) optimization algorithm is one of the meta-heuristic algorithms which is proposed based on herding behavior of krill individuals in the nature for solving optimization problems. Considering that SKH is a meta-heuristic algorithm, two main properties of this algorithm is using mixture of random search or exploration and local search or exploitation. Keeping the exploration and exploitation of algorithm balanced plays crucial role in SKH to gain highest performance in solving optimization tasks. So, in this paper we have proposed fuzzy KH which is utilizing a fuzzy system as a parameter tuner for setting the participation amount of exploration and exploitation considering different conditions which may happen during solving the problems. We have tested the fuzzy KH algorithm on different benchmarks and the obtained results show the higher performance of proposed method.