Ukbe Usame UÇAR, Selçuk Kürşat İŞLEYEN, Hadi GÖKÇEN

Hareketli müşterili araç rotalama problemi için Meta-Sezgisel algoritmaların deneysel analizi

Silahlı İnsansız Hava Araçları, birçok ülkenin ulusal güvenliğini sağlamak adına askeri operasyonlarda yoğun bir şekilde kullandıkları yapay zekâya dayalı savunma sistemleridir. Bu sistemler sayesinde operasyon alanındaki hareketli ve hareketsiz hedefler, zorlu coğrafik koşullar altında pilot kullanılmaksızın kumanda merkezi yardımıyla imha edilebilmektedir. İnsansız hava aracı filosu tarafından, seyir süresi, mühimmat kapasitesi, yakıt maliyeti ve zaman penceresi kısıtlamaları dikkate alınarak sistemdeki hareketli hedeflerin başarılı bir şekilde imha edilmesi gereksinimi, Hareketli Müşterili Araç Rotalama Problemini ortaya çıkarmaktadır. Bu çalışmada Heterojen Filolu-Zaman Pencereli-Kapasite Kısıtlı Hareketli Müşterili Araç Rotalama Problemi, minimum görev süresi ve görev maliyeti amaçları doğrultusunda çözülmesi amaçlanmıştır. Problemin çözümü için sezgisel algoritmalar(ÇARA, RASA) geliştirilmiş ve metasezgisel algoritmalar (Genetik Algoritma, NSGA-II ve Tavlama Benzetimi Algoritması) kullanılmıştır. Önerilen algoritmaların etkinliği vurucu sayısının 5-10, hedef sayısının 10-35 arasında değiştiği 30 farklı deney seti üzerinde test edilmiştir. Algoritmalar için uygun parametre setinin belirlenmesinde Taguchi yönteminden yararlanılmıştır. Analiz sonucunda Genetik Algoritmanın diğer algoritmalara kıyasla daha başarılı sonuçlar ürettiği tespit edilmiştir.

Anahtar Kelimeler:

Hareketli müşterili araç rotalama problemi, Tavlama Benzetimi, Pareto Optimizasyonu, Genetik Algoritma, NSGA-II

Experimental Analysis of Meta-Heuristic Algorithms for Moving Customer Vehicle Routing Problem

Unmanned Combat Aerial Vehicles are defense systems based on artificial intelligence which is intensively used by many countries to provide national security on military operations. By means of these systems, moving or non-moving threat factors in the operation field could be destroyed under harsh and challenging geographical conditions without requiring a pilot with the help of a control center. In fleet operations, the necessity of destroying moving targets successfully under constraints of the endurance, munition capacity, time window and fuel cost of unmanned combat aerial vehicles brings out the moving customer-vehicle routing problem. In this study, Heterogeneous Fleet-Moving Customer Vehicle Routing Problem with Time Windows under constraint of vehicle capacity (endurance) has been aimed to be solved considering the minimum operation time and cost. In order to solve the problem, heuristic algorithms (ÇARA, RASA) were developed and metaheuristic algorithms (Genetic Algorithm, NSGA-II and Simulated Annealing) were used. The effectiveness of the proposed algorithms was tested on 30 different experimental sets with the number of pursuers ranging from 5-10 and the number of targets ranging from 10-35. Taguchi method was used to determine the appropriate parameter set for the algorithms. As a result of the analysis, it has been found that Genetic Algorithm produces much better results than other algorithms.

Keywords:

Moving Customer Vehicle Routing Problem, Simulated Annealing, Pareto Optimization, Genetic Algorithm, NSGA-II,

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