Bi-objective lion swarm optimization based on teaching and learning algorithm

被引:0
|
作者
Zhang, Qi [1 ]
Jiang, Mingyan [1 ]
机构
[1] Shandong Univ, Sch Informat Sci & Engn, Qingdao 266237, Peoples R China
来源
PROCEEDINGS OF 2022 THE 6TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND SOFT COMPUTING, ICMLSC 20222 | 2022年
关键词
teaching and learning; bi-objective; lion swarm optimization algorithm; uniform distribution;
D O I
10.1145/3523150.3523160
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
To address the problem that it is difficult to obtain a good quality and uniformly distributed Pareto optimal solution set for a complex biobjective system model, this paper proposes a Teaching-Learning-based Bi-objective Lion Swarm Optimization algorithm (TLBLSO) for solving the bi-objective system uniform Pareto solution set problem. The idea and mechanism of teaching and learning optimization algorithm are introduced into the Lion Swarm algorithm. That is, the knowledge level of the whole group is improved by the way of individual teachers imparting knowledge and students exchanging knowledge, which effectively improves the spatial searching ability of the lion swarm. By comparing with other optimization algorithms, the experimental results show that the proposed TLBLSO can obtain well-distributed optimization solutions, which verifies the superiority of the proposed algorithm in this paper.
引用
收藏
页码:61 / 65
页数:5
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