Author(s)

Yu Chen

Affiliation(s)

College of Computer and Information Technology, China Three Gorges University, Yichang 443002, Hubei, China.

Corresponding Author

Yu Chen

ABSTRACT

With the acceleration of urbanization, China faces severe challenges in waste management. Currently, waste sorting and transportation have become a key aspect of urban environmental governance, influenced by factors such as vehicle capacity constraints and collection requirements for different types of waste. This paper addresses the issue of urban waste sorting and transportation by constructing and solving optimization models under different constraints, effectively reducing transportation costs and carbon emissions while enhancing transportation efficiency. This paper simplifies such problems into the capacitated vehicle routing problem(CVRP), aiming to minimize the total daily transportation distance while considering constraints such as vehicle capacity constraints and multiple round-trip deliveries. A single-type waste transportation route optimization model is constructed and solved using a hybrid heuristic algorithm. Further considering dedicated vehicles for different types of waste, as well as their load, volume, time, and transportation cost constraints, new constraints are introduced based on this model, and a divide-and-conquer strategy and hybrid heuristic algorithm(HHA) is adopted to solve the multi-type waste transportation route optimization problem. By iteratively optimizing the routes, the transportation routes for various types of waste are reasonably planned, effectively reducing the cost of urban waste transportation.

KEYWORDS

Capacitated Vehicle Routing Problem(CVRP); Route optimization; Divide-and-Conquer strategy; Hybrid heuristic algorithm

CITE THIS PAPER

Yu Chen. Optimization of vehicle route for urban classified waste transportation. World Journal of Engineering Research. 2025, 3(4): 1-7. DOI: https://doi.org/10.61784/wjer3043.

REFERENCES

[1] Shi Yanjun, Lv Lingling, Hu Fanyi, et al. A heuristic solution method for multi-depot vehicle routing-based waste collection problems. Applied Sciences, 2020, 10(7): 2403.

[2] Bouleft Yousra, Ahmed Elhilali Alaoui. Dynamic multi-compartment vehicle routing problem for smart waste collection. Applied System Innovation, 2023, 6(1): 30.

[3] Yu Haonan, Zhang JianHui, Ao Tiantian, et al. Overseas M&A, Research on Waste Collection Vehicle Routing Optimization Based on Ant Colony Algorithm. Value Engineering, 2025, 44(02): 152-154.

[4] Mou Nengye, Cheng Chiyao, Jiang Erwei, et al. Overseas M&A, Multi-type & Multi-trip Vehicle Routing Optimization for Municipal Solid Waste Classification and Transportation. Journal of Safety and Environment, 2022, 22(04): 2199-2208. DOI: 10.13637/j.issn.1009-6094.2021.0527.

[5] Shen Jiangang, Guo Zhiyi, Wang Xiao. Overseas M&A, GIS-based Routing Optimization Analysis of Waste Collection Vehicles Considering Resident Satisfaction. Traffic & Transportation, 2022, 38(02): 22-27.

[6] Zhou, Jian, Meixi Zhang, Sisi Wu. Multi-objective vehicle routing problem for waste classification and collection with sustainable concerns: the case of shanghai city. Sustainability, 2022, 14(18): 11498.

[7] Wu Hailin, Tao Fengming, Yang Bo. Optimization of vehicle routing for waste collection and transportation. International Journal of Environmental Research and Public Health, 2020, 17(14): 4963.

[8] Tang Kaiqiang, Fu Huiqiao, Liu Jiasheng, et al. Overseas M&A, Hierarchical Optimization for Capacitated Vehicle Routing Based on Deep Reinforcement Learning. Systems Engineering and Electronics, 2025, 47(03): 827-841.

[9] Alesiani Francesco, Gulcin Ermis, Konstantinos Gkiotsalitis. Constrained clustering for the capacitated vehicle routing problem (CC-CVRP). Applied artificial intelligence, 2022, 36(1): 1995658.

[10] Ge Bin, Tian Wenzhi, Xia Chenxing, et al. Overseas M&A, Solving capacitated vehicle routing problem using end-to-end deep reinforcement learning. Application Research of Computers, 2024, 41(11): 3245-3250.