International Journal of Computational Intelligence Systems

Volume 14, Issue 1, 2021, Pages 79 - 87

Three-Dimensional Multi-Mission Planning of UAV Using Improved Ant Colony Optimization Algorithm Based on the Finite-Time Constraints

Authors
Weiheng Liu*, ORCID, Xin Zheng
School of Automation, Beijing Institute of Technology, Beijing, 100081, China
*Corresponding author. Email: veihenneliu@163.com
Corresponding Author
Weiheng Liu
Received 9 June 2020, Accepted 11 October 2020, Available Online 29 October 2020.
DOI
10.2991/ijcis.d.201021.001How to use a DOI?
Keywords
Improved ant colony optimization; Variable dimension vector coefficient; Three-dimensional missions planning; Time adaptive factor; Finite-time constraints
Abstract

An improved ant colony optimization (IACO) is proposed to solve three-dimensional multi-task programming under finite-time constraints. The algorithm introduces the artificial preemptive coefficient matrix into the transfer probability formula, which makes results convergence and also reduces the convergence time of the algorithm. Following the principle that there is no pheromone on the path where the ants are just beginning to forage in reality, the pheromone is initially zero, and the ant's self-guided ability is fully utilized, which enhances the random exploration ability of the ant algorithm for the entire solution space. By introducing the variable dimension vector coefficient and the time adaptive factor of transfer probability, the search probability in the inferior solution set is reduced and the convergence speed of the algorithm is increased. Finally, through the simulation on the random map and comparison with the traditional ant colony optimization, particle swarm optimization, and tabu search algorithm, the superiority of the IACO proposed in this paper is demonstrated.

Copyright
© 2021 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
14 - 1
Pages
79 - 87
Publication Date
2020/10/29
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.d.201021.001How to use a DOI?
Copyright
© 2021 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Weiheng Liu
AU  - Xin Zheng
PY  - 2020
DA  - 2020/10/29
TI  - Three-Dimensional Multi-Mission Planning of UAV Using Improved Ant Colony Optimization Algorithm Based on the Finite-Time Constraints
JO  - International Journal of Computational Intelligence Systems
SP  - 79
EP  - 87
VL  - 14
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.201021.001
DO  - 10.2991/ijcis.d.201021.001
ID  - Liu2020
ER  -