Hyper-heuristic is a class of methodologies which automates the process of selecting or
generating a set of heuristics to solve various optimization problems. A traditional hyper …

Hyper-heuristic frameworks have emerged out of the shadows of meta-heuristic techniques.
In this very active field, new frameworks are developed all the time. Shared common …

Metaheuristics, being tailored to each particular domain by experts, have been successfully
applied to many computationally hard optimization problems. However, once implemented …

Selection hyper-heuristics are optimisation methods that operate at the level above
traditional (meta-) heuristics. Their task is to evaluate low level heuristics and determine …

The present study proposes a new selection hyper-heuristic providing several adaptive
features to cope with the requirements of managing different heuristic sets. The approach …

There is a growing interest towards the design of reusable general purpose search methods
that are applicable to different problems instead of tailored solutions to a single particular …

The present study investigates the performance of heuristics while solving problems with
routing and rostering characteristics. The target problems include scheduling and routing …

The present study concentrates on the generality of selection hyper-heuristics across
various problem domains with a focus on different heuristic sets in addition to distinct …

The course timetabling problem is a well known constraint optimization problem which has
been of interest to researchers as well as practitioners. Due to the NP-hard nature of the …

An iterative selection hyper-heuristic passes a solution through a heuristic selection process
to decide on a heuristic to apply from a fixed set of low level heuristics and then a move …