Affiliations: [a] School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai, China | [b] School of Mathematics, Southeast University, Nanjing, Jiangsu, China | [c] Data61 in CSIRO, Sandy Bay, Hobart, Tasmania, Australia | [d] School of Science, Donghua University, Shanghai, China
Correspondence:
[*]
Corresponding author: Xiu Kan, School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China. Tel.: +86 21 67791126; E-mail: [email protected].
Abstract: In this paper, the Capacitated Vehicle Routing Problem (CVRP) of multi-depot express delivery is investigated based on the actual express delivery business in Beijing and driving intention-based road network. An Adaptive Simulated Annealing and Artificial Fish Swarm Algorithm (A-SAAFSA) is proposed to solve the CVRP. The basic ideas are use a “certainty” probability to accept the worst solution through the Metropolis criterion in the search process, and a strategy of adjusting the swimming direction to avoid falling into the local optimal solution. Moreover, an adaptive visual strategy, which adjusts the visual range adaptively in real time according to the current solution quality, is used to ensure the efficient searching and accuracy of the algorithm. Experimental results show that the A-SAAFSA algorithm outperforms four well-known algorithms, namely simulated annealing and artificial fish swarm algorithm, artificial fish swarm algorithm, simulated annealing algorithm, and genetic algorithm.
