Abstract. Machine learning can be utilized to build models that predict the runtime of search algorithms for hard combinatorial problems. Such empirical hardness models have previo...
Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevi...
First-order probabilistic models are recognized as efficient frameworks to represent several realworld problems: they combine the expressive power of first-order logic, which serv...
This paper presents preliminary work done on simulationbased optimization of a stochastic material-dispatching system in a retailer network. The problem we consider is one of dete...
Genetic algorithms (GAs) used in complex optimization domains usually need to perform a large number of fitness function evaluations in order to get near-optimal solutions. In rea...
-- The classical Wardrop System Optimum (SO) assignment model assumes that the users will cooperate with each other in order to minimize the overall travel costs. The importance of...
Frederico R. B. Cruz, Tom Van Woensel, James MacGr...