Research progress of hardness theories on evolutionary algorithm

被引：0
|
作者：
机构：
[1] College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing
[2] School of Information Engineering, Nanchang Hangkong University, Nanchang
来源：
Li, M. (limingniat@hotmail.com) | 1600年 / Chinese Institute of Electronics卷 / 42期
关键词：
Epistasis measure; Fitness landscape; Landscape state machine; Optimal contraction theorem; Optimization hardness; Spatial correlation;
D O I：
10.3969/j.issn.0372-2112.2014.02.026
中图分类号：
学科分类号：
摘要：
The research work of hardness on evolutionary algorithm is an important branch of evolutionary computation. It aims to study the relationship between the performance of evolutionary algorithm and the characters of the optimization problem. And, the goal of the hardness research is estimating the performance of an evolutionary algorithm deployed in one optimization problem by using limited information. This paper summarizes six kinds of hardness theories on evolutionary algorithm, such as fitness-distance correlation model, fitness landscape methods, landscape state machine, optimal contraction theorem, epistasis methods, etc. and eight hardness indicators with them. Furthermore, this paper discusses the advantages and disadvantages of these methods, and prospects the trends of this research field.
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页码：383 / 390
页数：7
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