YAPAY ZEKA VE KÜMELEME TEKNİKLERİ KULLANILARAK GELİŞTİRİLEN YÖNTEM İLE OKUL SERVİSİ ROTALAMA PROBLEMİNİN OPTİMİZASYONU

Araç Rotalama Problemi (ARP) klasik yöntemler ile çözülmesi mümkün olmayan ve birçok alt dalı olan karmaşık bir problemdir. Bu çalışmada, ARP’nin bir alt dalı olan Okul Servisi Rotalama Probleminin (OSRP) optimizasyonu amaçlanmıştır. ARP ve OSRP incelenmiş, problemler ve geliştirilen çözüm yöntemleri ile ilgili literatüre yer verilmiştir. OSRP'nin optimizasyonu için kümeleme teknikleri ve yapay zeka yöntemleri kullanılarak, GPS, GIS araçları ve mobil uygulama desteği ile bir yazılım geliştirilmiştir. Geliştirilen yazılım Ankara ilinde hizmet veren servis firmalarından toplanan rota verileri üzerinde uygulanmıştır. Elde edilen deneysel sonuçlar, geliştirilen yöntemin, mesafe, zaman ve rakım değişimi parametreleri açısından rotaları başarılı bir şekilde iyileştirilebileceğini göstermiştir.

OPTIMIZATION OF SCHOOL BUS ROUTING PROBLEM BY USING A METHOD WITH ARTIFICIAL INTELLIGENCE AND CLUSTERING TECHNIQUES

Vehicle routing problems (VRP) are complicated problems, which can be encountered in a variety of different fields and are not possible to solve using classical methods. In this study, optimization of the School Bus Routing Problem(SBRP), which is a sub-branch of VRP, is aimed. VRP and SBRP have been studied, and the literature on the problems and developed solution methods have been given. For the optimization of SBRP, by using the clustering and artificial intelligence techniques a software has been developed with the support of the GPS, GIS tools and mobile application. The developed software has been applied on the route data collected from school service companies which are in the province of Ankara. The obtained experimental results have showed that the developed method can successfully optimize the school bus routes in terms of distance, time and altitude change parameters.

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