Routing optimization method of waste transportation vehicle using biological evolutionary algorithm under the perspective of low carbon and environmental protection

Abstract

Reasonably and effectively formulating the best route for urban waste transportation vehicle is particularly important for realizing low carbon and environmental protection of Green China construction concept. However, the current path planning method has shortcomings such as local optimization. In order to solve this problem, this paper aims at low carbon and environmental protection construction needs and proposes a routing optimization method of waste transportation vehicles based on improved ant colony algorithm. Firstly, the mathematical model of Vehicle Routing Problem (VRP) is constructed by considering transportation distance and carbon emissions cost. Then, network parameters in traditional ant colony algorithm are combined and optimized to realize self-adaptive update in the whole cycle. Furthermore, the neighborhood algorithm is used to iteratively optimize improved algorithm to avoid the defects of local optimization when solving VRP problem. Finally, the simulation results based on an actual dataset in North China show that the proposed method can achieve efficient and accurate optimal routing optimization for complex samples, and its solution stability index is 0.87 and the average deviation is 0.011, the lowest distribution cost after optimization is about 3,080 yuan, which are better than the comparison methods.