Negative Slope Coefficient is an indicator of problem hardness that has been introduced in 2004 and that has returned promising results on a large set of problems. It is based oil the concept of fitness cloud and works by partitioning the cloud into a number of bills representing as many different regions of the fitness landscape. The measure is calculated by joining the bills centroids by segments and summing all their negative slopes. In this paper, for the first time, we point out it potential problem of the Negative Slope Coefficient: We Study its value for different instances of the well known NK-landscapes and we show how this indicator is dramatically influenced by the minimum number of points contained in a bill. Successively, we formally justify this behavior of the Negative Slope Coefficient and we discuss pros and cons of this measure.
|Title of host publication||Applications of Evolutionary Computing, Proceedings|
|Editors||M Giacobini, A Brabazon, S Cagnoni, GA DiCaro, A Ekart, AI EsparciaAlcazar, M Farooq, A Fink, P Machado, J McCormack, M Oneill, F Neri, M Preuss, F Rothlauf, E Tarantino, S Yang|
|Place of Publication||Berlin|
|ISBN (Print)||0302-9743 978-3-642-01128-3|
|Publication status||Published - 1 Jan 2009|
|Name||Lecture Notes in Computer Science|