Advanced Bacterial Foraging and Its Application Using Fuzzy Logic Based Variable step Size and Clonal Selection of Immune Algorithm

摘要

This paper suggests advanced bacterial foraging strategy using membership function of fuzzy logic and clonal selection of immune system. Bacteria foraging based optimal solution is defined by the positions of each member in the population of the S bacteria at the jth chemotactic step, kth reproduction step, and lth elimination-dispersal event. Therefore, chemotactic step is important to have an optimal solution in system. Up to now, a foraging strategy uses fixed chemotactic step. This paper introduces clonal selection of immune algorithm and fuzzy logic into bacterial foraging to enhance running speed and patch of optimal condition (e.g., group of objective with conditions). This approach provides us with novel hybrid model based on foraging behavior and clonal selection for a higher running time and optimal solution.