FLC control for tuning exploration phase in bio-inspired metaheuristic

Kazimierz Kiełkowicz, Damian Grela


Growing popularity of the Bat Algorithm has encouraged researchers to focus their work on its further improvements. Most work has been done within the area of hybridization of Bat Algorithm with other metaheuristics or local search methods. Unfortunately, most of these modifications not only improves the quality of obtained solutions, but also increases the number of control parameters that are needed to be set in order to obtain solutions of expected quality. This makes such solutions quite impractical. What more, there is no clear indication what these parameters do in term of a search process. In this paper authors are trying to incorporate Mamdani type Fuzzy Logic Controller (FLC) to tackle some of these mentioned shortcomings by using the FLC to control the exploration phase of a bio-inspired metaheuristic. FLC also allows us to incorporate expert knowledge about the problem at hand and define expected behaviors of system – here process of searching in multidimensional search space by modeling the process of bats hunting for their prey.


Bat algorithm, swarm intelligence, metaheuristics, optimization, fuzzy logic, Mamdami-Type inference system

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DOI: http://dx.doi.org/10.17951/ai.2016.16.2.32
Data publikacji: 2017-12-22 09:38:07
Data złożenia artykułu: 2017-12-22 09:25:34


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