Hongguang Wu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Hongguang Wu has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Wanting Wang
School of Mathematics and Information Science, North Minzu University, Yinchuan, China
2 shared publications - Yuelin Gao
School of Mathematics and Information Science, North Minzu University, Yinchuan, China
2 shared publications - Ziyu Zhang
School of Mathematics and Information Science, North Minzu University, Yinchuan, China
1 shared publication
Latest Publications
- 19 July 2022
- Published by Springer Nature in Applied Intelligence
- Vol. 53 (6) , 7326-7342
A hybrid ant colony optimization with fireworks algorithm to solve capacitated vehicle routing problem
- 19 July 2022
- Published by Springer Nature in Applied Intelligence
- Vol. 53 (6) , 7326-7342
A hybrid ant colony optimization with fireworks algorithm to solve capacitated vehicle routing problem
- Open Access
- 1 June 2021
- Published by Springer Nature in Complex & Intelligent Systems
- Vol. 9 (3) , 2491-2508
A hybrid ant colony algorithm based on multiple strategies for the vehicle routing problem with time windows
In this paper, we propose a vehicle routing problem with time windows (TWVRP). In this problem, we consider a hard time constraint that the fleet can only serve customers within a specific time window. To solve this problem, a hybrid ant colony (HACO) algorithm is proposed based on ant colony algorithm and mutation operation. The HACO algorithm proposed has three innovations: the first is to update pheromones with a new method; the second is the introduction of adaptive parameters; and the third is to add the mutation operation. A famous Solomon instance is used to evaluate the performance of the proposed algorithm. Experimental results show that HACO algorithm is effective against solving the problem of vehicle routing with time windows. Besides, the proposed algorithm also has practical implications for vehicle routing problem and the results show that it is applicable and effective in practical problems.
- 1 June 2021
- Published by Springer Nature in Complex & Intelligent Systems
- Vol. 9 (3) , 2491-2508
Open AccessA hybrid ant colony algorithm based on multiple strategies for the vehicle routing problem with time windows
In this paper, we propose a vehicle routing problem with time windows (TWVRP). In this problem, we consider a hard time constraint that the fleet can only serve customers within a specific time window. To solve this problem, a hybrid ant colony (HACO) algorithm is proposed based on ant colony algorithm and mutation operation. The HACO algorithm proposed has three innovations: the first is to update pheromones with a new method; the second is the introduction of adaptive parameters; and the third is to add the mutation operation. A famous Solomon instance is used to evaluate the performance of the proposed algorithm. Experimental results show that HACO algorithm is effective against solving the problem of vehicle routing with time windows. Besides, the proposed algorithm also has practical implications for vehicle routing problem and the results show that it is applicable and effective in practical problems.