A Fuzzy Logic for Parameter Adaptation in Ant Colony Optimization Approach

Authors : Sawsan A. Al-Agamy; Fadl Mutaher Ba-Alwi; Abdulqader M. Mohsen

Volume/Issue : Volume 7 - 2022, Issue 5 - May

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3a3PtBR

DOI : https://doi.org/10.5281/zenodo.6774879

The purpose of this study is to produce an ”adaptive Ant Colony System” in order to establish a balance between exploitation and exploration in terms of solving the Travel salesman problem. First we do a detailed investigation of several Ant Colony System Algorithm’s parameters. Second we will incorporate into the algorithm a Fuzzy Logic Controller, which will be utilized to alter the settings based on the algorithm’s reliable performance metrics. The parameter customization will proceed throughout the execution of the algorithm, providing for a dynamic parameter settings depending on the algorithm’s current performance. The adaptive algorithm will be examined on a set of TSP problems of varying sizes, and the results will be compared to those obtained using the standard algorithm and other studies in the same manner.

Keywords : Travel Salesman Problem(TSP),Meta-heusitic Algorithms, Ant Colony Optimization(ACO),Parameter tuning, Fuzzy Logic Controller(FLC), Fuzzy Ant Colony System (FACS).


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