Length scale for characterising continuous optimization problems

Morgan, Rachael and Gallagher, Marcus (2012). Length scale for characterising continuous optimization problems. In: Carlos A.Coello Coello, Vincenzo Cutello, Kalyanmoy Deb, Stephanie Forrest, Giuseppe Nicosia and Mario Pavone, Parallel Problem Solving from Nature - PPSN XII 12th International Conference, Proceedings, Part II. Parallel Problem Solving from Nature - PPSN XII 12th International Conference, Taormina, Italy, (407-416). 1 - 5 September 2012. doi:10.1007/978-3-642-32937-1_41


Author Morgan, Rachael
Gallagher, Marcus
Title of paper Length scale for characterising continuous optimization problems
Conference name Parallel Problem Solving from Nature - PPSN XII 12th International Conference
Conference location Taormina, Italy
Conference dates 1 - 5 September 2012
Proceedings title Parallel Problem Solving from Nature - PPSN XII 12th International Conference, Proceedings, Part II   Check publisher's open access policy
Journal name Lecture Notes in Computer Science   Check publisher's open access policy
Place of Publication Heidelberg, Germany
Publisher Springer
Publication Year 2012
Sub-type Fully published paper
DOI 10.1007/978-3-642-32937-1_41
ISBN 9783642329630
9783642329647
ISSN 0302-9743
1611-3349
Editor Carlos A.Coello Coello
Vincenzo Cutello
Kalyanmoy Deb
Stephanie Forrest
Giuseppe Nicosia
Mario Pavone
Volume 7492
Start page 407
End page 416
Total pages 10
Collection year 2013
Language eng
Abstract/Summary In metaheuristic optimization, understanding the relationship between problems and algorithms is important but non-trivial. There has been a growing interest in the literature on techniques for analysing problems, however previous work has mainly been developed for discrete problems. In this paper, we develop a novel framework for characterising continuous optimization problems based on the concept of length scale. We argue that length scale is an important property for the characterisation of continuous problems that is not captured by existing techniques. Intuitively, length scale measures the ratio of changes in the objective function value to steps between points in the search space. The concept is simple, makes few assumptions and can be calculated or estimated based only on the information available in black-box optimization (objective function values and search points). Some fundamental properties of length scale and its distribution are described. Experimental results show the potential use of length scale and directions to develop the framework further are discussed.
Keyword Estimation of distribution algorithms
Circles in a square packing problems
Parameter settings
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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Created: Thu, 27 Sep 2012, 00:01:42 EST by Ms Ramona Hooyer on behalf of School of Information Technol and Elec Engineering