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 …

Adaptive operator selection (AOS) is a high-level controller for an optimization algorithm that
monitors the performance of a set of operators with a credit assignment strategy and …

In this work we conduct a comparative study of several publicly available, state-of-the-art
hyper-heuristics for HyFlex in order to assess their generality across domains. To this …

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 …

Practitioners often need to solve real world problems for which no custom search algorithms
exist. In these cases they tend to use general-purpose solvers that have no guarantee to …

A framework called ParHyFlex and its underlying principle are presented. ParHyFlex is
based on the sequential HyFlex framework and supports the implementation of different …

A hyper-heuristic is a high level methodology which performs search over the space of
heuristics each operating on the space of solutions to solve hard computational problems …

Hyper-heuristics are a class of high-level search methodologies which operate over a
search space of heuristics rather than a search space of solutions. Hyper-heuristic research …

Selection hyper-heuristics have proven to be effective in solving various real-world
problems. Hyper-heuristics differ from traditional heuristic approaches in that they explore a …

Distributed spacecraft missions (DSM) are gaining traction in the space community for the
potential to deploy multiple simple and low-cost spacecraft to provide high temporal …