Paper Info
Title
Mixed-Integer NK landscapes
Abstract
NK landscapes (NKL) are stochastically generated pseudo-boolean functions with N bits (genes) and K interactions between genes. By means of the parameter K ruggedness as well as the epistasis can be controlled. NKL are particularly useful to understand the dynamics of evolutionary search. We extend NKL from the traditional binary case to a mixed variable case with continuous, nominal discrete, and integer variables. The resulting test function generator is a suitable test model for mixed-integer evolutionary algorithms (MI-EA) – i. e. instantiations of evolution algorithms that can deal with the aforementioned variable types. We provide a comprehensive introduction to mixed-integer NKL and characteristics of the model (global/local optima, computation, etc.). Finally, a first study of the performance of mixed-integer evolution strategies on this problem family is provided, the results of which underpin its applicability for optimization algorithm design.
Year
DOI
Venue
2006
10.1007/11844297_5
PPSN
Keywords
Field
DocType
resulting test function generator,mixed-integer evolutionary algorithm,evolution algorithm,k interaction,mixed-integer nk landscape,mixed variable case,aforementioned variable type,integer variable,evolutionary search,parameter k ruggedness,mixed-integer evolution strategy,evolution strategy,evolutionary algorithm
Integer,Boolean function,k-means clustering,Mathematical optimization,Evolutionary algorithm,Parallel algorithm,Computer science,Local optimum,Test functions for optimization,Integer programming
Conference
Volume
ISSN
ISBN
4193
0302-9743
3-540-38990-3
Citations 
PageRank 
References 
13
0.88
4
Authors
7
Name
Order
Citations
PageRank
Rui Li1788.10
Michael T. M. Emmerich224722.74
Jeroen Eggermont321117.08
Ernst G. P. Bovenkamp4495.73
Thomas Bäck562986.94
Jouke Dijkstra612616.92
Johan H. C. Reiber71767286.53