Local optima networks, landscape autocorrelation and heuristic search performance

Authors:
Francisco Chicano;Fabio Daolio;Gabriela Ochoa;Sébastien Vérel;Marco Tomassini;Enrique Alba
Affiliations:
E.T.S. Ingeniería Informática, University of Málaga, Spain;Information Systems Department, University of Lausanne, Lausanne, Switzerland;Inst. of Computing Sciences and Mathematics, University of Stirling, Scotland, UK;INRIA Lille - Nord Europe and University of Nice Sophia-Antipolis, France;Information Systems Department, University of Lausanne, Lausanne, Switzerland;E.T.S. Ingeniería Informática, University of Málaga, Spain
Venue:
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Year:
2012

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Abstract

Recent developments in fitness landscape analysis include the study of Local Optima Networks (LON) and applications of the Elementary Landscapes theory. This paper represents a first step at combining these two tools to explore their ability to forecast the performance of search algorithms. We base our analysis on the Quadratic Assignment Problem (QAP) and conduct a large statistical study over 600 generated instances of different types. Our results reveal interesting links between the network measures, the autocorrelation measures and the performance of heuristic search algorithms.