Optimization algorithms are an approach to solving many problems in everyday life and usually to find the optimal solution for problems with a large solution space. In this study, an optimal route detection approach was developed using the clonal selection algorithm which is a sub-method of the artificial immune system. For this purpose, the road passenger transport network obtained from Erzurum Metropolitan Municipality has been modeled and a bus line which is selected and used from this network has been examined by clonal selection algorithm. The optimization method developed for the proposed approach was implemented in the MATLAB environment and the results obtained are plotted comparatively on Google Maps. The performance of the proposed method was tested and a performance improvement of about 10% was achieved according to the results obtained.
Günümüzde genellikle belediyeler küçük şehirlere nazaran büyükşehirlerde sağlamış olduğu toplu taşıma hizmetleri ile o şehirlerde yaşayan insanlara daha hızlı daha kaliteli ve daha düzenli bir ulaşım olanağı sağlamaktadır. Ayrıca yine belediyeler tarafından insanlara sunulan toplu taşıma hizmetleri o şehirlerdeki mevcut yol durumları ve değişen yol güzergâhları ile sürekli olarak güncellemekte ve buna bağlı olarak da gelişmektedir. Bu çalışmada ise Erzurum Büyükşehir Belediyesi tarafından aktif olarak kullanılan bir otobüs güzergâhı, optimize edilmeye çalışılmış ve sonuçlar paylaşılmıştır. Bu amaçla elde edilen gerçek veriler, optimizasyon problemi türü olan gezgin satıcı problemi kullanılarak modellenmiş ve DNA Hesaplama Algoritması kullanılarak kullanılan mevcut güzergah kısaltılmaya çalışılmıştır.
This study aims to examine, regulate, and update the land transportation of the Erzurum Metropolitan Municipality (EMM), Turkey using computerized calculation techniques. In line with these targets, some critical information has been obtained for study: the number of buses, the number of expeditions, the number of bus lines, and the number and maps of existing routes belonging to EMM. By using the information that has been obtained, this study aims at outlining specific outputs according to the input parameters, such as determining the optimal routes, the average travel, and the journey time. Once all of these situations were considered, various optimization algorithms were used to get the targeted outputs in response to the determined input parameters. In addition, the study found that the problem involved in modeling the land transport network of the EMM is in line with the so-called "traveling salesman problem," which is a scenario about optimization often discussed in the literature. This study tried to solve this problem by using the genetic algorithm, the clonal selection algorithm, and the DNA computing algorithm. The location data for each bus stops on the bus lines selected for the study were obtained from the EMM, and the distances between these coordinates were obtained by using Google Maps via a Google API. These distances were stored in a distance matrix file and used as input parameters in the application and then were put through optimization algorithms developed initially on the MATLAB platform. The study's results show that the algorithms developed for the proposed approaches work efficiently and that the distances for the selected bus lines can be shortened.
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