IEICE TRANSACTIONS on Information
Multi-Objective Ant Lion Optimizer Based on Time Weight
Summary :
Multi-objective evolutionary algorithms are widely used in many engineering optimization problems and artificial intelligence applications. Ant lion optimizer is an outstanding evolutionary method, but two issues need to be solved to extend it to the multi-objective optimization field, one is how to update the Pareto archive, and the other is how to choose elite and ant lions from archive. We develop a novel multi-objective variant of ant lion optimizer in this paper. A new measure combining Pareto dominance relation and distance information of individuals is put forward and used to tackle the first issue. The concept of time weight is developed to handle the second problem. Besides, mutation operation is adopted on solutions in middle part of archive to further improve its performance. Eleven functions, other four algorithms and four indicators are taken to evaluate the new method. The results show that proposed algorithm has better performance and lower time complexity.
- Publication
- IEICE TRANSACTIONS on Information Vol.E104-D No.6 pp.901-904
- Publication Date
- 2021/06/01
- Publicized
- 2021/03/11
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2021EDL8009
- Type of Manuscript
- LETTER
- Category
- Artificial Intelligence, Data Mining
Authors
Yi LIU
Defense Innovation Institute
Wei QIN
Defense Innovation Institute
Jinhui ZHANG
Logistic Support Center of Chinese PLA General Hospital
Mengmeng LI
Defense Innovation Institute,Tianjin Artificial Intelligence Innovation Center
Qibin ZHENG
Academy of Military Science
Jichuan WANG
Defense Innovation Institute,Tianjin Artificial Intelligence Innovation Center
Keyword
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Yi LIU, Wei QIN, Jinhui ZHANG, Mengmeng LI, Qibin ZHENG, Jichuan WANG, "Multi-Objective Ant Lion Optimizer Based on Time Weight" in IEICE TRANSACTIONS on Information,
vol. E104-D, no. 6, pp. 901-904, June 2021, doi: 10.1587/transinf.2021EDL8009.
Abstract: Multi-objective evolutionary algorithms are widely used in many engineering optimization problems and artificial intelligence applications. Ant lion optimizer is an outstanding evolutionary method, but two issues need to be solved to extend it to the multi-objective optimization field, one is how to update the Pareto archive, and the other is how to choose elite and ant lions from archive. We develop a novel multi-objective variant of ant lion optimizer in this paper. A new measure combining Pareto dominance relation and distance information of individuals is put forward and used to tackle the first issue. The concept of time weight is developed to handle the second problem. Besides, mutation operation is adopted on solutions in middle part of archive to further improve its performance. Eleven functions, other four algorithms and four indicators are taken to evaluate the new method. The results show that proposed algorithm has better performance and lower time complexity.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2021EDL8009/_p
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@ARTICLE{e104-d_6_901,
author={Yi LIU, Wei QIN, Jinhui ZHANG, Mengmeng LI, Qibin ZHENG, Jichuan WANG, },
journal={IEICE TRANSACTIONS on Information},
title={Multi-Objective Ant Lion Optimizer Based on Time Weight},
year={2021},
volume={E104-D},
number={6},
pages={901-904},
abstract={Multi-objective evolutionary algorithms are widely used in many engineering optimization problems and artificial intelligence applications. Ant lion optimizer is an outstanding evolutionary method, but two issues need to be solved to extend it to the multi-objective optimization field, one is how to update the Pareto archive, and the other is how to choose elite and ant lions from archive. We develop a novel multi-objective variant of ant lion optimizer in this paper. A new measure combining Pareto dominance relation and distance information of individuals is put forward and used to tackle the first issue. The concept of time weight is developed to handle the second problem. Besides, mutation operation is adopted on solutions in middle part of archive to further improve its performance. Eleven functions, other four algorithms and four indicators are taken to evaluate the new method. The results show that proposed algorithm has better performance and lower time complexity.},
keywords={},
doi={10.1587/transinf.2021EDL8009},
ISSN={1745-1361},
month={June},}
Copy
TY - JOUR
TI - Multi-Objective Ant Lion Optimizer Based on Time Weight
T2 - IEICE TRANSACTIONS on Information
SP - 901
EP - 904
AU - Yi LIU
AU - Wei QIN
AU - Jinhui ZHANG
AU - Mengmeng LI
AU - Qibin ZHENG
AU - Jichuan WANG
PY - 2021
DO - 10.1587/transinf.2021EDL8009
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E104-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2021
AB - Multi-objective evolutionary algorithms are widely used in many engineering optimization problems and artificial intelligence applications. Ant lion optimizer is an outstanding evolutionary method, but two issues need to be solved to extend it to the multi-objective optimization field, one is how to update the Pareto archive, and the other is how to choose elite and ant lions from archive. We develop a novel multi-objective variant of ant lion optimizer in this paper. A new measure combining Pareto dominance relation and distance information of individuals is put forward and used to tackle the first issue. The concept of time weight is developed to handle the second problem. Besides, mutation operation is adopted on solutions in middle part of archive to further improve its performance. Eleven functions, other four algorithms and four indicators are taken to evaluate the new method. The results show that proposed algorithm has better performance and lower time complexity.
ER -
English
