A Genetic Approximation of Closest String via Rank Distance

被引：2

作者：

Dinu, Liviu P. ^{[1
]}

Ionescu, Radu ^{[1
]}

机构：

[1] Univ Bucharest, Fac Math & Comp Sci, Acad 14, RO-010014 Bucharest, Romania

来源：

13TH INTERNATIONAL SYMPOSIUM ON SYMBOLIC AND NUMERIC ALGORITHMS FOR SCIENTIFIC COMPUTING (SYNASC 2011) | 2012年

关键词：

AGGREGATION;

D O I：

10.1109/SYNASC.2011.31

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper aims to fully present a new genetic approach that uses rank distance for solving two known NP-complete problems: closest string and closest substring. We build a genetic algorithm for each of the two problems and we describe the genetic operations involved. The genetic algorithm adapted for the closest substring problem uses standard genetic operations, while the genetic operations for the closest string problem are only inspired from nature. Both genetic algorithms bring something new by using a fitness function based on rank distance. The tests for both problems show that our genetic approach via rank distance has good results.

引用

页码：207 / 214

页数：8

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