Differential gradient evolution plus algorithm for constraint optimization problems: A hybrid approach

被引:10
|
作者
Tabassum, Muhammad Farhan [1 ]
Akram, Sana [1 ]
Hassan, Saadia [2 ]
Karim, Rabia [2 ]
Naik, Parvaiz Ahmad [3 ]
Farman, Muhammad [4 ]
Yavuz, Mehmet [5 ]
Naik, Mehraj-ud-din [6 ]
Ahmad, Hijaz [7 ,8 ]
机构
[1] Univ Management & Technol, Dept Math, Lahore 54000, Pakistan
[2] Univ Lahore, Fac Allied Hlth Sci, Dept Sports Sci, Lahore 54000, Pakistan
[3] Xi An Jiao Tong Univ, Sch Math & Stat, Xian 710049, Shaanix, Peoples R China
[4] Univ Lahore, Dept Math & Stat, Lahore 54000, Pakistan
[5] Necmettin Erbakan Univ, Fac Sci, Dept Math & Comp Sci, TR-42090 Konya, Turkey
[6] Jazan Univ, Coll Engn, Dept Chem Engn, Jazan 45142, Saudi Arabia
[7] Int Telemat Univ Uninettuno, Sect Math, Corso Vittorio Emanuele II 39, I-00186 Rome, Italy
[8] Univ Engn & Technol, Dept Basic Sci, Peshawar, Pakistan
基金
中国博士后科学基金;
关键词
Meta-heuristic algorithms; Hybridization; Differential evolution; Gradient evolution; Constraint optimization problems; PARTICLE SWARM OPTIMIZATION; ENGINEERING OPTIMIZATION; ECONOMIC-DISPATCH; DESIGN OPTIMIZATION; GENETIC ALGORITHMS; SEARCH; EXPLORATION/EXPLOITATION; GENERATION;
D O I
10.11121/ijocta.01.2021.001077
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Optimization for all disciplines is very important and applicable. Optimization has played a key role in practical engineering problems. A novel hybrid meta-heuristic optimization algorithm that is based on Differential Evolution (DE), Gradient Evolution (GE) and Jumping Technique named Differential Gradient Evolution Plus (DGE+) are presented in this paper. The proposed algorithm hybridizes the above-mentioned algorithms with the help of an improvised dynamic probability distribution, additionally provides a new shake off method to avoid premature convergence towards local minima. To evaluate the efficiency, robustness, and reliability of DGE+ it has been applied on seven benchmark constraint problems, the results of comparison revealed that the proposed algorithm can provide very compact, competitive and promising performance.
引用
收藏
页码:158 / 177
页数:20
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