Finite-state processing is typically based on structures that allow for efficient indexing and sequential search. However, this “rigid” framework has several disadvantages when...
Alexander Troussov, Brian O'Donovan, Seppo Koskenn...
Learning Bayesian networks from data has been studied extensively in the evolutionary algorithm communities [Larranaga96, Wong99]. We have previously explored extending some of the...
Discovery of graphical models is NP-hard in general, which justifies using heuristics. We consider four commonly used heuristics. We summarize the underlying assumptions and anal...
— Ant-colony optimization (ACO) is a popular swarm intelligence metaheuristic scheme that can be applied to almost any optimization problem. In this paper, we address a performan...
This paper presents a hybrid metaheuristic approach (HMA) for solving the Unconstrained Binary Quadratic Programming (UBQP) problem. By incorporating a tabu search procedure into ...