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Journals / International Journal of Engineering Science and Application / 2026 / Volume: 1 Issue: 3

A Hybrid Genetic-Ant Colony Algorithm for Travelling Salesman Problem

Emel Soylu(Karabük University)
Ali Uysal(Karabük University)
Pages
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Publication Date
2017-09-30
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In this way, the success rate of ant colony algorithm is maximized.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Travelling salesman problem is a well-known problem in optimization algorithms.
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Key Findings & Data:In this study, we propose a hybrid genetic-ant colony algorithm to solve this problem.
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Conclusion & Impact:In this way, the success rate of ant colony algorithm is maximized.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Ant colony algorithm · Genetic algorithm · Path planning

Abstract

Travelling salesman problem is a well-known problem in optimization algorithms. In this study, we propose a hybrid genetic-ant colony algorithm to solve this problem. There are no certain formulas to determine the parameters of ant colony algorithm. Usually, programmers use the trial and error method to find best values. We use the genetic algorithm to optimize best parameter values of ant colony algorithm. In this way, the success rate of ant colony algorithm is maximized.

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Cite This Article

Soylu, E., Uysal, A. (2017). A Hybrid Genetic-Ant Colony Algorithm for Travelling Salesman Problem. International Journal of Engineering Science and Application, Volume: 1 Issue: 3. https://ajindex.com/articles/1588814

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