DocumentCode :
419011
Title :
Insights on properties of multiobjective MNK-landscapes
Author :
Aguirre, Hernán E. ; Tanaka, Kiyoshi
Author_Institution :
Fac. of Eng., Shinshu Univ., Nagano, Japan
Volume :
1
fYear :
2004
fDate :
19-23 June 2004
Firstpage :
196
Abstract :
The influence of epistasis on the performance of evolutionary algorithms (EAs) is being increasingly investigated for single objective combinatorial optimization problem. Kauffman´s NK-landscapes model of epistatic interactions, particularly, has been the center of several studies and is considered as a good test problem generator. However, epistasis and NK-landscapes in the context of multiobjective evolutionary algorithm (MOEAs) are almost unexplored subjects. In this work we present an extension of Kauffman´s NK-landscapes model of epistatic interactions to multiobjective MNK-landscapes. MNK-landscapes present several desirable features and hold the potential of becoming an important class of scalable test problems generator for multiobjective combinatorial optimization. In order to meaningfully use MNK-landscapes as a benchmark tool we first need to understand how the parameters of the landscapes relate to multiobjective concepts. This paper is a first step towards understanding the properties of MNK-landscapes from a multiobjective standpoint.
Keywords :
automatic test pattern generation; combinatorial mathematics; computational complexity; evolutionary computation; Kauffman NK-landscapes; benchmark tool; epistatic interactions; evolutionary algorithms; multiobjective MNK-landscapes; multiobjective combinatorial optimization; multiobjective evolutionary algorithm; scalable test problems generator; test problem generator; Benchmark testing; Evolution (biology); Evolutionary computation; Genetic algorithms; Genetic mutations; Shape; Simulated annealing; Terminology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2004. CEC2004. Congress on
Print_ISBN :
0-7803-8515-2
Type :
conf
DOI :
10.1109/CEC.2004.1330857
Filename :
1330857
Link To Document :
بازگشت