IEICE TRANSACTIONS on Information
An Efficient Algorithm of Discrete Particle Swarm Optimization for Multi-Objective Task Assignment
Summary :
In this paper, a discrete particle swarm optimization method is proposed to solve the multi-objective task assignment problem in distributed environment. The objectives of optimization include the makespan for task execution and the budget caused by resource occupation. A two-stage approach is designed as follows. In the first stage, several artificial particles are added into the initialized swarm to guide the search direction. In the second stage, we redefine the operators of the discrete PSO to implement addition, subtraction and multiplication. Besides, a fuzzy-cost-based elite selection is used to improve the computational efficiency. Evaluation shows that the proposed algorithm achieves Pareto improvement in comparison to the state-of-the-art algorithms.
- Publication
- IEICE TRANSACTIONS on Information Vol.E99-D No.12 pp.2968-2977
- Publication Date
- 2016/12/01
- Publicized
- 2016/08/24
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2016PAP0032
- Type of Manuscript
- Special Section PAPER (Special Section on Parallel and Distributed Computing and Networking)
- Category
- Distributed system
Authors
Nannan QIAO
Chinese Academy of Sciences
Jiali YOU
Chinese Academy of Sciences
Yiqiang SHENG
Chinese Academy of Sciences
Jinlin WANG
Chinese Academy of Sciences
Haojiang DENG
Chinese Academy of Sciences
Keyword
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Nannan QIAO, Jiali YOU, Yiqiang SHENG, Jinlin WANG, Haojiang DENG, "An Efficient Algorithm of Discrete Particle Swarm Optimization for Multi-Objective Task Assignment" in IEICE TRANSACTIONS on Information,
vol. E99-D, no. 12, pp. 2968-2977, December 2016, doi: 10.1587/transinf.2016PAP0032.
Abstract: In this paper, a discrete particle swarm optimization method is proposed to solve the multi-objective task assignment problem in distributed environment. The objectives of optimization include the makespan for task execution and the budget caused by resource occupation. A two-stage approach is designed as follows. In the first stage, several artificial particles are added into the initialized swarm to guide the search direction. In the second stage, we redefine the operators of the discrete PSO to implement addition, subtraction and multiplication. Besides, a fuzzy-cost-based elite selection is used to improve the computational efficiency. Evaluation shows that the proposed algorithm achieves Pareto improvement in comparison to the state-of-the-art algorithms.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2016PAP0032/_p
Copy
@ARTICLE{e99-d_12_2968,
author={Nannan QIAO, Jiali YOU, Yiqiang SHENG, Jinlin WANG, Haojiang DENG, },
journal={IEICE TRANSACTIONS on Information},
title={An Efficient Algorithm of Discrete Particle Swarm Optimization for Multi-Objective Task Assignment},
year={2016},
volume={E99-D},
number={12},
pages={2968-2977},
abstract={In this paper, a discrete particle swarm optimization method is proposed to solve the multi-objective task assignment problem in distributed environment. The objectives of optimization include the makespan for task execution and the budget caused by resource occupation. A two-stage approach is designed as follows. In the first stage, several artificial particles are added into the initialized swarm to guide the search direction. In the second stage, we redefine the operators of the discrete PSO to implement addition, subtraction and multiplication. Besides, a fuzzy-cost-based elite selection is used to improve the computational efficiency. Evaluation shows that the proposed algorithm achieves Pareto improvement in comparison to the state-of-the-art algorithms.},
keywords={},
doi={10.1587/transinf.2016PAP0032},
ISSN={1745-1361},
month={December},}
Copy
TY - JOUR
TI - An Efficient Algorithm of Discrete Particle Swarm Optimization for Multi-Objective Task Assignment
T2 - IEICE TRANSACTIONS on Information
SP - 2968
EP - 2977
AU - Nannan QIAO
AU - Jiali YOU
AU - Yiqiang SHENG
AU - Jinlin WANG
AU - Haojiang DENG
PY - 2016
DO - 10.1587/transinf.2016PAP0032
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E99-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2016
AB - In this paper, a discrete particle swarm optimization method is proposed to solve the multi-objective task assignment problem in distributed environment. The objectives of optimization include the makespan for task execution and the budget caused by resource occupation. A two-stage approach is designed as follows. In the first stage, several artificial particles are added into the initialized swarm to guide the search direction. In the second stage, we redefine the operators of the discrete PSO to implement addition, subtraction and multiplication. Besides, a fuzzy-cost-based elite selection is used to improve the computational efficiency. Evaluation shows that the proposed algorithm achieves Pareto improvement in comparison to the state-of-the-art algorithms.
ER -
English
