Hyper-heuristics have emerged as a way to raise the level of generality of search techniques
for computational search problems. This is in contrast to many approaches, which represent …

Hyper-heuristics introduce novel approaches for solving challenging combinatorial
optimization problems by operating over a set of low level (meta)-heuristics. This is achieved …

To classify high‐dimensional data, feature selection plays a key role to eliminate irrelevant
attributes and enhance the classification accuracy and efficiency. Since feature selection is …

Continuous optimization is a central task in computer science. Hyperheuristics prove to be
an effective mechanism for intelligent operator selection and generation for optimization …

[EN] In today's competitive markets, the role of human resources as a sustainable
competitive advantage is undeniable. Reliable hiring decisions for personnel assignation …

Dans la plupart des problèmes réels que ce soit technologiques, économiques ou autres,
une compétence du point de vue choix de décisions à faire est indispensable. Un décideur …

Hyper-heuristics are high-level methods, used to solve various optimization problems. Some
of them are capable of learning and adapting their behavior throughout the solving process …

To comply with the continually growing demand for multimedia content and higher
throughputs, the telecom-munication industry has to keep improving the use of the …

Real-world combinatorial optimisation problems (COPs) faced in ports are often subject to
dynamics and uncertainties, ie the problem instance is not completely known in advance …

A hyper-heuristic is a high-level method that manages a set of low-level heuristics to solve
various problems in a problem-independent manner. In this paper, we propose a new …