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
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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
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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
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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
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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
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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
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
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Automated generation of constructive ordering heuristics for educational timetabling [PDF]
, 2017 Construction heuristics play an important role in solving combinatorial optimization problems. These heuristics are usually used to create an initial solution to the problem which is improved using optimization techniques such as metaheuristics.
B McCollum +12 more
core +2 more sources
Hyper-heuristic decision tree induction [PDF]
2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 2009 Hyper-heuristics are increasingly used in function and combinatorial optimization. Rather than attempt to solve a problem using a fixed heuristic, a hyper-heuristic approach attempts to find a combination of heuristics that solve a problem (and in turn may be directly suitable for a class of problem instances).
Alan Vella, David Corne, Chris Murphy
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