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Local Optima Networks, Landscape Autocorrelation and Heuristic Search Performance (1210.4021v1)
Published 15 Oct 2012 in cs.AI and cs.NE
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.