Learner Performance-Based Behavior Optimization Algorithm: A Functional Case Study

被引：0
|
作者：
Salih, Shahad A. [1 ,2 ]
Rashid, Tarik A. [3 ]
机构：
[1] Univ Duhok, Comp Sci Dept, Duhok, Iraq
[2] Da Vinci Studio Sch, Duhok, Iraq
[3] Univ Kurdistan Hewler, Comp Sci & Engn Dept, Erbil, Iraq
来源：
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INNOVATIONS IN COMPUTING RESEARCH (ICR'22) | 2022年 / 1431卷
关键词：
Metaheuristic; Learner performance-based behavior; Optimization algorithm;
D O I：
10.1007/978-3-031-14054-9_43
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel algorithm called learner performance-based behavior algorithm (LPB) was proposed for single and multi-objective by Chnoor M. Rahman and Tarik A. Rashid in 2021. LPB proved its ability to deal with complex optimization problems compared to the dragonfly algorithm (DA), genetic algorithm (GA), and particle swarm optimization (PSO). This paper presents and explains the implementation of the LPB algorithm, and it applies it as a model in a case study to maximize a fitness function. As a result, the LPB algorithm is successfully improved the initial population and achieved the optimal solution.
引用
收藏
页码：467 / 482
页数：16
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