Genetik Algoritmalar Yardımı ile Gezgin Satıcı Probleminin Çözümü Üzerine Bir Uygulama

Gezgin Seyyar Satıcı Problemi 8217;nde aralarındaki mesafeler bilinen n adet şehrin nokta düğüm yerleşim yeri müşteri şube vb her birine yalnız bir kez uğranarak başlangıç noktasına geri dönülmesi esnasında kat edilen toplam yolun en kısa olduğu şehir sırasının bulunması hedeflenir Dağıtım planlama lojistik gibi alanlar başta olmak üzere birçok sektörde geniş uygulama alanlarına sahip olan gezgin satıcı problemi optimizasyon alanında araştırmacı ve akademisyenler tarafından üzerinde uzun yıllardır yoğun olarak çalışılan çözümü zor NP hard bir problemdir Bu çalışmada meta sezgisel bir yöntem olan genetik algoritmalar yardımı ile gezgin satıcı problemine çözüm aranmış ve geliştirilen algoritmanın uygulaması Adana ilinde gıda sektöründe faaliyet gösteren bir firma üzerinde gerçekleştirilmiştir Firmanın güncel olarak kullandığı rotalar ile algoritma ile elde edilen rotalar karşılaştırılarak algoritmanın etkinliği gösterilmiştir Anahtar Kelimeler: Gezgin satıcı problemi genetik algoritmalar meta sezgisel yöntemler

Anahtar Kelimeler:

Gezgin satıcı problemi, genetik algoritmalar, meta sezgisel yöntemler

Genetik Algoritmalar Yardımı ile Gezgin Satıcı Probleminin Çözümü Üzerine Bir Uygulama

Traveling Salesman Problem aims to find the shortest route among n cities nodes customers branches etc with known distances between each city where the salesman leaves a city visits each of the cities exactly once and returns back to the starting point The traveling salesman problem one of the very important NP hard problems in optimization has wide application areas including distribution planning logistics and it has been studied by researchers and academicians for decades In this paper a genetic algorithm has been applied to solve the traveling salesman problem and a real world application of the study has been implemented on a food delivery firm in Adana The routes that the firm already uses and the routes that are found using genetic algorithms are compared to illustrate the efficiency of the algorithm Keywords: Traveling salesman problem genetic algorithms metaheuristic methods

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