2026-06-07T07:47:49Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/81472026-02-03T11:08:10Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc Chicano-García, José-Francisco author Alba-Torres, Enrique author 2014-10-01 Landscapes’ theory provides a formal framework in which combinatorial optimization problems can be theoretically characterized as a sum of an especial kind of landscape called elementary landscape. The elementary landscape decomposition of a combinatorial optimization problem is a useful tool for understanding the problem. Such decomposition provides an additional knowledge on the problem that can be exploited to explain the behavior of some existing algorithms when they are applied to the problem or to create new search methods for the problem. In this paper we analyze the 0-1 Unconstrained Quadratic Optimization from the point of view of landscapes’ theory. We prove that the problem can be written as the sum of two elementary components and we give the exact expressions for these components. We use the landscape decomposition to compute autocorrelation measures of the problem, and show some practical applications of the decomposition. doi: 10.1007/s10732-011-9170-6 http://hdl.handle.net/10630/8147 Autocorrelación (Estadística) Elementary landscape decomposition of the 0-1 unconstrained quadratic optimization