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Towards the Role of Heuristic Knowledge in EA.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Pandu Rangan, C.
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Lishan Kang
Yong Liu
Sanyou Zeng
Yingzhou Bi
Lixin Ding
Source :
Advances in Computation & Intelligence; 2007, p621-630, 10p
Publication Year :
2007

Abstract

Evolutionary Algorithm (EA) is a stochastic search algorithm and widely used in various real world problems. Classic EA uses little problem specific knowledge, so it is called lean knowledge approach. Because of the randomicity of crossover, mutation and selection, its' searching strategy is semi-blind, and the efficiency is usually low. In order to acquire an efficient and effective EA that suits difficult real-world problems, we try to best incorporate heuristic knowledge into an EA to guide the search focusing on the most promising area. By comparing different EAs for solving the traveling sales man problem (TSP) and auto-generating test paper problem, we investigate the role of heuristic knowledge in EA. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540745808
Database :
Complementary Index
Journal :
Advances in Computation & Intelligence
Publication Type :
Book
Accession number :
33088342
Full Text :
https://doi.org/10.1007/978-3-540-74581-5_68