Inthisstudy, performance of Ant Colony and Genetic Algorithms that is map of Turkey is aimed to find. Performance of the sealgorithms in terms of route distance and route prediction time were investigated. A C#-based interface was designed for implementation of the application and monitoring of the experimental results. As a result of the application, it is observed that Ant Colony algorithm has more high performance than genetic algorithm in terms of both route distance and performance time.
Inthisstudy, performance of Ant Colony and Genetic Algorithms that is map of Turkey is aimed to find. Performance of the sealgorithms in terms of route distance and route prediction time were investigated. A C#-based interface was designed for implementation of the application and monitoring of the experimental results. As a result of the application, it is observed that Ant Colony algorithm has more high performance than genetic algorithm in terms of both route distance and performance time
Bu çalışmada, rota planlama problemlerinden olan gezgin satıcı probleminin (GSP) çözümünü gerçekleştirmek için yapay zeka tekniklerinden olan karınca kolonisi ve genetik algoritmaların performansları karşılaştırılmıştır. Türkiye haritası üzerinde gerçekleştirilen çalışmada en iyi rotanın planlanması hedeflenmiştir. Her iki algoritmanın rota mesafesi yönünden başarım performansı ve bu rotayı hesaplama süresi incelenmiştir. Uygulamanın gerçekleştirilmesi ve deneysel sonuçların gözlemlenmesi için C# tabanlı bir arayüz tasarlanmıştır. Uygulama sonucunda karınca kolonisi algoritmasının hem rota mesafesi hem de başarım süresi yönünden genetik algoritmalara göre daha üstün olduğu gözlemlenmiştir.
Primary Language | Turkish |
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Subjects | Engineering |
Journal Section | Makaleler |
Authors | |
Publication Date | June 6, 2014 |
Published in Issue | Year 2014 Volume: 18 Issue: 1 |
e-ISSN :1308-6529
Linking ISSN (ISSN-L): 1300-7688
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