Recent years have witnessed a growing interest in automatic learning mechanisms and
applications. The concept of hyper-heuristics, algorithms that either select among existing …

This paper expands on the concept of heuristic space diversity and investigates various
strategies for the management of heuristic space diversity within the context of a meta-hyper …

A selection hyper-heuristic is used to optimise a number of well-known benchmark
problems. The resulting sequences of heuristics and objective function values are used to …

Hyper-heuristics represent an innovative method for solving hard combinatorial problems
such as the Bin Packing Problem. In this work, we propose a solution model that …

Recent years have witnessed an escalating interest for methods that automatically adapt to
different types of problems. In this regard, the term hyper-heuristics-heuristics that either …

Hyper-heuristics have emerged as an important strategy for combining the strengths of
different heuristics into a single method. Although hyper-heuristics have been found to be …

For a better treatment of Dynamic Constraint Satisfaction Problems (DCSPs), several
techniques have been developed to be used in repair algorithms. We cite, for example, the …

Recent years have witnessed a growing interest in automatic learning mechanisms and
applications. The concept of hyper-heuristics, algorithms that either select among existing …

This thesis is concerned with finding solutions to discrete NP-hard problems. Such problems
occur in a wide range of real-world applications, such as bin packing, industrial flow shop …

This dissertation is submitted to the Graduate Programs in Engineering and Information
Technologies in partial fulfillment of the requirements for the degree of Master of Science …