An Novel Estimation of Distribution Algorithm for TSP

被引：0

作者：

Yu, Fahong ^{[1
]}

Liao, Weizhi ^{[1
,2
,4
]}

Chen, Meijia ^{[3
]}

机构：

[1] Jiaxing Univ, Coll Math & Informat Engn, Jiaxing, Peoples R China

[2] Guangxi Univ, Guangxi Experiment Ctr Sci & Technol, Nanning 530004, Peoples R China

[3] Jiaxing Univ, Ctr Econom Managing Experiment, Jiaxing, Peoples R China

[4] Guangxi Teachers Educ Univ, Coll Comp & Informat Engn, Nanning, Peoples R China

来源：

MECHATRONICS, ROBOTICS AND AUTOMATION, PTS 1-3 | 2013年 / 373-375卷

关键词：

traveling salesman problem; estimation of distribution algorithms; probabilistic model;

D O I：

10.4028/www.scientific.net/AMM.373-375.1089

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Estimation of distribution algorithms (EDAs) is a method for solving NP-hard problem. But it is hard to find global optimization quickly for some problems, especially for traveling salesman problem (TSP) that is a classical NP-hard combinatorial optimization problem. To solve TSP effectively, a novel estimation of distribution algorithm (NEDA) is provided, which can solve the conflict between population diversity and algorithm convergence. The experimental results show that the performance of NEDA is effective.

引用

页码：1089 / +

页数：2