Aesthetic Differential Evolution Algorithm for Solving Computationally Expensive Optimization Problems

被引：1

作者：

Poonia, Ajeet Singh ^{[1
]}

Sharma, Tarun Kumar ^{[2
]}

Sharma, Shweta ^{[2
]}

Rajpurohit, Jitendra ^{[2
]}

机构：

[1] Govt Coll Engn & Technol, Bikaner, India

[2] Amity Univ Rajasthan, Noida, India

来源：

ADVANCES IN NATURE AND BIOLOGICALLY INSPIRED COMPUTING | 2016年 / 419卷

关键词：

Differential evolution; DE; Optimization; Computationally expensive optimization problems;

D O I：

10.1007/978-3-319-27400-3_8

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The applications of Differential Evolution (DE) and the attraction of researchers towards it, shows that it is a simple, powerful, efficient as well as reliable evolutionary algorithm to solve optimization problems. In this study an improved DE called aesthetic DE algorithm (ADEA) is introduced to solve Computationally Expensive Optimization (CEO) problems discussed in competition of congress of evolutionary computation (CEC) 2014. ADEA uses the concept of mirror images to produce new decorative positions. The mirror is placed near the most beautiful (global best) individual to accentuate its attractiveness (significance). Simulated statistical results demonstrate the efficiency and ability of the proposal to obtain good results.

引用

页码：87 / 96

页数：10

共 21 条

[1] Differential evolution algorithm for the selection of optimal scaling factors in image watermarking [J].