A software interface for supporting the application of data science to optimisation [PDF]
, 2015 Many real world problems can be solved effectively by metaheuristics in combination with neighbourhood search. However, implementing neighbourhood search for a particular problem domain can be time consuming and so it is important to get the most value ...
EK Burke +4 more
core +3 more sources
Hyper-Heuristic Based on ACO and Local Search for Dynamic Optimization Problems
Algorithms, 2021 Hyper-heuristics comprise a set of approaches that are motivated (at least in part) by the objective of intelligently combining heuristic methods to solve hard optimization problems.
Felipe Martins Müller +1 more
doaj +1 more source
Towards Many-objective Optimisation with Hyper-heuristics: Identifying Good Heuristics with Indicators [PDF]
, 2016 PPSN 2016: 14th International Conference on Parallel Problem Solving from Nature, 17-21 September 2016, Edinburgh, ScotlandThis is the author accepted manuscript.
EK Burke +6 more
core +2 more sources
How Much Is Too Much? Facing Practical Limitations in Hyper-Heuristic Design for Packing Problems
AlgorithmsHyper-heuristics, or simply heuristics to choose heuristics, represent a powerful approach to tackling complex optimization problems. These methods decide which heuristic to apply throughout the solving process, aiming to improve the solving process ...
José Carlos Ortiz-Bayliss +2 more
doaj +1 more source
A Classification of Hyper-heuristic Approaches [PDF]
, 2009 The current state of the art in hyper-heuristic research comprises a set of approaches that share the common goal of automating the design and adaptation of heuristic methods to solve hard computational search problems.
A.S. Fukunaga +29 more
core +3 more sources
Hybridizations within a graph based hyper-heuristic framework for university timetabling problems [PDF]
, 2008 A significant body of recent literature has explored various research directions in hyper-heuristics (which can be thought as heuristics to choose heuristics). In this paper, we extend our previous work to construct a unified graph-based hyper-heuristic (
Burke, Edmund, Qu, Rong
core +2 more sources
A Survey of the Nurse Rostering Solution Methodologies: The State-of-the-Art and Emerging Trends
IEEE Access, 2022 This paper presents an overview of recent advances for the Nurse Rostering Problem (NRP) based on methodological papers published between 2012 to 2021.
Chong Man Ngoo +5 more
doaj +1 more source
A case study of controlling crossover in a selection hyper-heuristic framework using the multidimensional knapsack problem [PDF]
, 2015 Hyper-heuristics are high-level methodologies for solving complex problems that operate on a search space of heuristics. In a selection hyper-heuristic framework, a heuristic is chosen from an existing set of low-level heuristics and applied to the ...
Battiti R. +25 more
core +6 more sources
Batched Mode Hyper-heuristics [PDF]
, 2013 A primary role for hyper-heuristics is to control search processes based on moves generated by neighbourhood operators. Studies have shown that such hyper-heuristics can be effectively used, without modification, for solving unseen problem instances not only from a particular domain, but also on different problem domains.
Shahriar Asta +2 more
openaire +1 more source
The Scientific Landscape of Hyper-Heuristics: A Bibliometric Analysis Based on Scopus
AlgorithmsHyper-heuristics emerged as a broader metaheuristic framework to address the limitations of traditional optimization heuristics. By abstracting the design of low-level heuristics, hyper-heuristics offer a flexible and adaptable approach to solving ...
Helen C. Peñate-Rodríguez +3 more
doaj +1 more source