نوع مقاله : مقاله پژوهشی
نویسندگان
1 مهندسی کامپیوتر، دانشگاه اراک، اراک، ایران
2 گروه مهندسی کامپیوتر ، دانشگاه اراک ، اراک ، ایران
3 مهندسی کامپیوترـ دانشگاه اراک ـ اراک ـ ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
A lot of research has tried to solve the congestion of roads using meta-heuristic algorithms. In these algorithms, firstly, routing is done randomly over large areas. This will increase the search time. In addition, these algorithms only consider the physical distance between the vehicles. Since environmental factors such as traffic are very effective in routing, these factors should be considered in routing. In this paper, to solve the problems, a dynamic path programming method based on the combination of the ant colony algorithm and particle swarm optimization, along with a function of cosine angle has been proposed. This method takes into account various factors of roads such as the length of the urban road and the incoming and outgoing traffic at intersections. In the method, the points that are aligned with the navigation path towards the final destination are given more chances. Therefore, the overall goal of this paper is to reduce the diversion rate and the search time in finding the best route under road traffic conditions. The results of the proposed model on TSPLIB library, which is based on the physical distance between cars, show that the search time of the proposed method has decreased by 40.74% on average compared to the results of ten other methods used for evaluation. The highest and lowest rates of decrease are 98.01% and 6.02% respectively. The test of dynamic route planning under road traffic on some intersections of Beijing city also shows the proposed method only causes congestion of about 1.57%.
کلیدواژهها [English]
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