Hyper-heuristics comprise a set of approaches that are motivated (at least in part) by the
goal of automating the design of heuristic methods to solve hard computational search …

We provide a descriptive review of the main approaches for carrying out simulation
optimization, and sample some recent algorithmic and theoretical developments in …

The interest in nonparametric statistical analysis has grown recently in the field of
computational intelligence. In many experimental studies, the lack of the required properties …

Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …

Faced with the challenge of solving hard optimization problems that abound in the real
world, classical methods often encounter great difficulty. Vitally important applications in …

Witten and Frank's textbook was one of two books that 1 used for a data mining class in the
Fall of 2001. The book covers all major methods of data mining that produce a knowledge …

Metaheuristics are widely recognized as efficient approaches for many hard optimization
problems. This paper provides a survey of some of the main metaheuristics. It outlines the …

Stochastic local search (SLS) algorithms are among the most successful techniques for
solving computationally hard problems from computing science, operations research and …

Data Mining Page 1 Data Mining Practical Machine Learning Tools and Techniques Third
Edition Ian H. Witten Eibe Frank Mark A. Hall ELSEVIER AMSTERDAM • BOSTON • …

The algorithm described here, called OptQuest/NLP or OQNLP, is a heuristic designed to
find global optima for pure and mixed integer nonlinear problems with many constraints and …