A Modified Teaching-Learning Optimization Algorithm for Economic Load Dispatch Problem

被引：0
|
作者：
Yu, Ge [1 ]
Liu, Jinhai [1 ]
机构：
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110004, Liaoning, Peoples R China
来源：
INTELLIGENT COMPUTING METHODOLOGIES, ICIC 2018, PT III | 2018年 / 10956卷
基金：
国家重点研发计划; 中国国家自然科学基金;
关键词：
Improved teaching-learning optimization; Economic load dispatch; Self-learning method; Reverse-solution; Chaotic mapping;
D O I：
10.1007/978-3-319-95957-3_8
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
For the original Teaching-learning algorithm, it is weak in global search and prone to local search when solving complex optimization problems of high dimension. A modified algorithm based on space reverse-solution is proposed in this paper. Improvement of teacher phrase is based on the chaotic mapping and that of student phrase is based on the multi learning strategy. Then Self-learning phrase is added. The modified algorithm is applied to the complex high-dimensional benchmark functions for simulation experiments. Finally, the modified algorithm is applied to two typical power load distribution problems including 13 units and 40 units. The validity of the algorithm is verified from the aspects of convergence speed, convergence accuracy and stability.
引用
收藏
页码：63 / 69
页数：7
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