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Optimizing and comparison of market chain product distribution problem with different genetic algorithm versions

   Gülmez, Burak

In this study, it is aimed to carry out product distributions with the lowest distance and lowest cost for a market chain in Kayseri. Since there are too many market branches, the distribution of products in different orders affects the result quite a lot. This problem has been defined as the traveling salesman problem. When the traveling salesman problem is large, it cannot be solved by integer linear programming in polynomial time. It is therefore an NP-hard problem type. Therefore, a genetic algorithm was used for the solution. The genetic algorithm does not guarantee the optimum solution, but it can obtain acceptable solutions. It also obtains these solutions in a short time. The solution obtained is at an acceptable level, even if it is not optimal. In this study, a route was created with a genetic algorithm for 61 markets in Kayseri. In addition to the classical genetic algorithm, genetic algorithm variations that have emerged in recent years have been used As a result of all these algorithms, approximately 80 kilometers has been obtained to visit all the markets. When the solution obtained was examined, it was observed that it was a very good route.

Keywords

Traveling salesman problem, Genetic algorithm, Product distribution

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10.47495-okufbed.1117220-2430121 (2).pdf
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Alıntı yap

Gülmez, B. (2023). Optimizing and comparison of market chain product distribution problem with different genetic algorithm versions. Osmaniye Korkut Ata University Journal of the Institute of Science and Technology, 6(1), 180–196. doi:10.47495/okufbed.1117220

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