Probability distribution based recombination operator to solve unimodal and multi-modal problems

被引：2

作者：

Raghuwanshi, M. ^{[1
]}

Kakde, O. ^{[2
]}

机构：

[1] Rajiv Gandhi Coll Engn Res & Technol, Chandrapur, Maharashtra, India

[2] Visvesvaraya Natl Inst Technol, Nagpur, Maharashtra, India

来源：

INTERNATIONAL JOURNAL OF KNOWLEDGE-BASED AND INTELLIGENT ENGINEERING SYSTEMS | 2006年 / 10卷 / 03期

关键词：

D O I：

10.3233/KES-2006-10306

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The neighborhood-based crossover operators used in real coded genetic algorithm (RCGA) are based on some probability distribution. It is observed that each crossover operator directs the search towards a different zone in the neighborhood of the parents. The quality of the elements that belong to the visited region depends on the particular problems to be solved. Different crossover operators perform differently with respect to the problems, even at the different stages of the genetic process in the same problem. In this paper, the role of probability distribution is empirically investigated on unimodal and multi-modal test problems. It is observed that the operator based on polynomial distribution achieves superior performance on unimodal test problems. The lognormal distribution based operator is efficient in solving multi-modal problems.

引用

页码：247 / 255

页数：9