Optimization of vehicle routing based on the combination of ant colony and particle swarm algorithms with the heuristic function of the cosine of angles
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%.
Shafiei, H., Rafe, V., & Amiri, M. (2023). Optimization of vehicle routing based on the combination of ant colony and particle swarm algorithms with the heuristic function of the cosine of angles. Soft Computing Journal, (), -. doi: 10.22052/scj.2023.248702.1118
MLA
HamidReza Shafiei; Vahid Rafe; Maryam Amiri. "Optimization of vehicle routing based on the combination of ant colony and particle swarm algorithms with the heuristic function of the cosine of angles". Soft Computing Journal, , , 2023, -. doi: 10.22052/scj.2023.248702.1118
HARVARD
Shafiei, H., Rafe, V., Amiri, M. (2023). 'Optimization of vehicle routing based on the combination of ant colony and particle swarm algorithms with the heuristic function of the cosine of angles', Soft Computing Journal, (), pp. -. doi: 10.22052/scj.2023.248702.1118
VANCOUVER
Shafiei, H., Rafe, V., Amiri, M. Optimization of vehicle routing based on the combination of ant colony and particle swarm algorithms with the heuristic function of the cosine of angles. Soft Computing Journal, 2023; (): -. doi: 10.22052/scj.2023.248702.1118
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