TSSIA: Türkiye'deki Gezgin Satıcı Problemi için Yeni Bir Tabu Arama Segment İyileştirme Algoritması

Öz

Gezgin satıcı probleminde, bir satıcının bir şehirden başlayarak her şehirden sadece bir kez geçilmesi ve aynı şehre geri dönmesi amaçlanır. Fakat, bu problem, toplamda en kısa rotanın bulunmasıyla çözülür. Şehir sayısı fazla olduğunda çözülmesi çok zor ve zaman alan problemlerdendir. Bu yüzden, genelde meta sezgisel metotlarla çözülmeye çalışılır. Bu çalışmada, Türkiye’nin şehirlerinin mesafeleri kullanılarak Karınca Kolonisi, Yapay Arı Kolonisi ve Tabu Arama algoritmaları ile gezgin satıcı problemi çözülmeye çalışılmıştır. Her metot için en kısa rotalar bulunmuş ve bu metotlar karşılaştırılmıştır. Bu çalışma sonucunda en başarılı metot Tabu Arama algoritması olduğu görülmüştür. Bunula birlikte, Tabu Arama algoritmasına segment iyileştirme eklenmesi suretiyle bilinen en iyi rota tespit edilmiştir. Türkiye şehirleriyle oluşturulan gezgin satıcı probleminin şimdiye kadarki en iyi rotası 9966 km iken bu çalışmada önerilen Tabu Arama Segment İyileştirme algoritmasıyla 60 km azaltılarak 9906 km ye kadar düşürülmüştür.

Anahtar Kelimeler

• Gezgin Satıcı Problemi
• Tabu Arama Algoritması
• Karınca Kolonisi Algoritması
• Yapay Arı Kolonisi Algoritması
• Türkiye şehirleri

TSSIA: A Novel Tabu Search Segment Improvement Algorithm for the Traveling Salesman Problem in Türkiye

Öz

In the traveling salesman problem, the aim is for a salesperson to start from one province, pass through each province only once, and come back to the same province. However, this problem can be reached by discovering the shortest possible route in total. When the number of provinces is large, it is a very difficult and time-consuming problem to solve. Therefore, it is generally attempted to be solved with metaheuristic methods. In this work, the traveling salesman problem was attempted to be solved using the distances between the provinces of Türkiye with Ant Colony, Artificial Bee Colony, and Tabu Search algorithms. The shortest routes were found for each method, and these methods have been compared with each other. As a result, it was seen that the most successful method was the Tabu Search algorithm. In addition, the best-known route has been determined by adding segment improvement to the Tabu Search algorithm. While the best-known route for the Traveling Salesman Problem involving Turkish cities was previously 9,966 km, it has been reduced to 9,906 km using the Tabu Search Segment Improvement algorithm proposed in this study, achieving a reduction of 60 km.

Anahtar Kelimeler

• Traveling Salesman Problem
• Tabu Search Algorithm
• Ant Colony Algorithm
• Artificial Bee Colony Algorithm
• Turkish provinces

Kaynakça

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