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Hyper-heuristics: A survey and taxonomy
Computers & Industrial EngineeringHyper-heuristics are search techniques for selecting, generating, and sequencing (meta)-heuristics to solve challenging optimization problems. They differ from traditional (meta)-heuristics methods, which primarily employ search space-based optimization strategies.
Dokeroglu, Tansel +2 more
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A Classification of Hyper-heuristic Approaches
, 2010 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.
Kendall, Graham +11 more
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A Dynamic Multi-Armed Bandit-Gene Expression Programming Hyper-Heuristic for Combinatorial Optimization Problems [PDF]
, 2014 Hyper-heuristics are search methodologies that aim to provide high quality solutions across a wide variety of problem domains, rather than developing tailor-made methodologies for each problem instance/domain.
Kendall, Graham +8 more
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IEEE AccessRobotic Mobile Fulfillment Systems (RMFS) are an example of warehouse automation. Nonetheless, the complexity of RMFS is such that tackling the entire problem at once is unfeasible. So, this work focuses on a component known as the Pod Allocation Problem
Maria Torcoroma Benavides-Robles +3 more
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A hyper-heuristic approach to sequencing by hybridization of DNA sequences
, 2013 In this paper we investigate the use of hyper-heuristic methodologies for predicting DNA sequences. In particular, we utilize Sequencing by Hybridization. We believe that this is the first time that hyper-heuristics have been investigated in this domain.
Kendall, Graham +5 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 Hyper-Heuristic for Descriptive Rule Induction [PDF]
International Journal of Data Warehousing and Mining, 2007 There are in general three approaches to rule induction: exhaustive search, divide-and conquer, and separate-and-conquer (or its extension as weighted covering). Among them, the third approach, according to different rule search heuristics, can avoid the problem of producing many redundant rules (limitation of the first approach) or non-overlapping ...
Tho Hoan Pham, Tu Bao Ho
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Adaptive Macroscopic Ensemble Allocation for Robot Teams Monitoring Spatiotemporal Processes
Advanced Intelligent Systems, EarlyView.We propose an online, environment feedback‐driven macroscopic ensemble approach to adapt robot team task allocation in spatiotemporal environments by controlling robot populations rather than assigning individual robots, all while maintaining robust team performance even for small teams. Our simulation and experimental results show better or comparable
Victoria Edwards +2 more
wiley +1 more source
Case-Based Reasoning as a Heuristic Selector in a Hyper-Heuristic for Course Timetabling Problems [PDF]
, 2002 This paper studies Knowledge Discovery (KD) using Tabu Search and Hill Climbing within Case-Based Reasoning (CBR) as a hyper-heuristic method for course timetabling problems.
Qu, Rong, Petrovic, Sanja
core
Advanced Intelligent Systems, EarlyView.Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source