Multiobjective Multidepot Capacitated Arc Routing Optimization Based on Hybrid Algorithm

• Published in: Journal of advanced transportation Vol. 2022; pp. 1 - 13
• Main Author: Wu, Liang
• Format: Journal Article
• Language: English
• Published: London Hindawi 17.06.2022; John Wiley & Sons, Inc; Wiley
• Subjects: Algorithms; Carbon; Chromosomes; Cluster analysis; Clustering; Dijkstra's algorithm; Energy consumption; Genetic algorithms; Integer programming; Mathematical models; Mathematical optimization; Optimization; Roads & highways; Traffic; Transportation; Vehicles
• ISSN: 0197-6729; 2042-3195
• DOI: 10.1155/2022/1846681

The multidepot capacitated arc routing problem (CARP) is investigated with the hybrid optimization algorithm of the Dijkstra algorithm and genetic algorithm. The complex multidepot CARP is transformed into multiple single depot CARP by systematic clustering analysis. After completing the system clustering, the Dijkstra algorithm is used to adjust the boundary arc locally and merge it to a reasonable depot, while in the genetic algorithm, the structure of the chromosome is reset to use the path as the way of real coding, and the elite selection is used to decode to obtain the optimal path optimization scheme. Finally, Lanzhou road network data as experimental data, through Matlab to achieve the practicability of the algorithm in sprinkler applications. The results show that the improved genetic algorithm can successfully solve the multi-segment CARP with a certain road network scale, ensuring the correctness and feasibility of the algorithm. In addition, the efficiency of the algorithm in the later iteration is basically controlled at about 0.5 seconds, indicating that the efficiency of the algorithm is worth identifying.