A Hybrid BSO-ACO for Dynamic Vehicle Routing Problem On Real-World Road Networks

Liu，Mingde1; Song，Qi1; Zhao，Qi2; Li，Ling1; Yang，Zhiming1; Zhang，Yingbin1

2022

10.1109/ACCESS.2022.3221191

IEEE Access   Impact Factor & Quartile

2169-3536

2169-3536

The Dynamic Vehicle Routing Problem With Time Windows (DVRPTW) is an NP-hard problem, which has attracted a lot of attention in the past decades due to its many practical applications in logistics. In order to better describe the actual logistics distribution scenario, this paper studies the DVRPTW based on real road networks and proposes the hybrid BSO-ACO algorithm, which is a combination of Brain Storm Optimization (BSO), Ant Colony Optimization (ACO) and Neighborhood Search (2-opt, relocate, exchange). The algorithm 1) uses ACO to generate new individuals from the same cluster formed by BSO, and increases exploitation by ACO’s pheromone accumulation, 2) harnesses the 2-opt, relocate, and exchange to increase exploration to avoid the algorithm from falling into local optima. We construct a test set by extracting the real road networks in Panyu District, Guangzhou, China and compare the hybrid BSO-ACO algorithm with other algorithms on this test set. The computation experiments show the effectiveness and efficiency of the hybrid BSO-ACO algorithm.

Ant Colony Optimization Brain Storm Optimization Dynamic Vehicle Routing Problem with Time Windows Road Network

SCI ; EI

English

Others

Computer Science ; Engineering ; Telecommunications

Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications

WOS:000886142500001

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

20224613112473

Artificial intelligence ; Clustering algorithms ; Computational complexity ; Computational efficiency ; Roads and streets ; Storms ; Vehicle routing ; Vehicles

Roads and Streets:406.2 ; Precipitation:443.3 ; Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory:721.1 ; Artificial Intelligence:723.4 ; Information Sources and Analysis:903.1 ; Optimization Techniques:921.5

2-s2.0-85141603529

Scopus

1.China Telecom Research Institute, Guangzhou, China
2.Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China

Liu，Mingde,Song，Qi,Zhao，Qi,et al. A Hybrid BSO-ACO for Dynamic Vehicle Routing Problem On Real-World Road Networks[J]. IEEE Access,2022,10:1-1.

Liu，Mingde,Song，Qi,Zhao，Qi,Li，Ling,Yang，Zhiming,&Zhang，Yingbin.(2022).A Hybrid BSO-ACO for Dynamic Vehicle Routing Problem On Real-World Road Networks.IEEE Access,10,1-1.

Liu，Mingde,et al."A Hybrid BSO-ACO for Dynamic Vehicle Routing Problem On Real-World Road Networks".IEEE Access 10(2022):1-1.