Süleyman ÖZER, Adil BAYKASOĞLU, Özcan KILINÇCI

Application Of Chicken Swarm Optimization to Travelling Salesman Problem And A Reviewing Of Similar Studies

This study focuses on an adapted application of the Chicken Swarm Optimization (CSO) Algorithm on a Travelling Salesman Problem (TSP). CSO Algorithm aims to search for optimal solution of a continuous function metaheuristically as a basis and it need some modifications to be coupled to a discontinuous problem like TSP. Some studies have been done before in the process of transforming a continuous metaheuristic method into discontinuous. However, as seen in reference studies, the algorithm needs also an additional decision-making mechanism after the transformation, and this would usually be the Greedy Search (GS) Algorithm when it comes to the CSO. Nevertheless, the aftermath of these decision-making mechanisms the customized novel CSO leaves the main logic of CSO and being Swarm Intelligence Algorithm and turn into a more colorful variation of the casual GS algorithm. The original part that distinguishes this work from others, it is focused on applying the CSO algorithm to a discontinuous TSP problem, while staying true to neutral phenomenon mimicked method and preserve the CSO’s logical context. The main quest of the paper is not to invent a method that gives better results for the example problem on any account, but to reveal how the CSO algorithm will give results to the example problem if it maintains its logic integrity. Therefore, an extension free bare adaptation of CSO is implemented for a TSP problem and results are observed.

Keywords:

Chicken Swarm Optimization, CSO, TSP Greedy Search, Metaheuristic, Discontinuous Transformation.,

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