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Everything about Hyper-heuristic
A hyper-heuristic is a heuristic search method that seeks to automate, often by the incorporation of machine learning techniques, the process of selecting, combining, generating or adapting several simpler heuristics to efficiently solve computational search problems. One of the motivations for studying hyper-heuristics is to build systems which can handle classes of problems rather than solving just one problem. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Hyper-heuristicA 5-minute orientation
- Skim a recent paper: A deep reinforcement learning based hyper-heuristic for combinatorial optimisation with uncertaintiesInfluential work since 2022
- Pick up a classic book: Hyper-HeuristicsThe most-reprinted book on the subject
- Read the landmark paper: Hyper-heuristics: a survey of the state of the artCited 1,068 times
- Go sideways: MetaheuristicA closely related topic
- Go sideways: Memetic algorithmA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Hyper-heuristics: a survey of the state of the art
A graph-based hyper-heuristic for educational timetabling problems
A Hyper-Heuristic Scheduling Algorithm for Cloud
Automatic design of hyper-heuristic based on reinforcement learning
Grammatical Evolution Hyper-Heuristic for Combinatorial Optimization Problems
A multi-objective hyper-heuristic based on choice function
Hyper-heuristic approach for multi-objective software module clustering
Hyper-heuristic approaches for strategic mine planning under uncertainty
🆕 Influential since 2022
A deep reinforcement learning based hyper-heuristic for combinatorial optimisation with uncertainties
A Q-learning-based hyper-heuristic evolutionary algorithm for the distributed flexible job-shop scheduling problem with crane transportation
Semiconductor final testing scheduling using Q-learning based hyper-heuristic
A Cooperative Coevolution Hyper-Heuristic Framework for Workflow Scheduling Problem
LLMOA: A novel large language model assisted hyper-heuristic optimization algorithm
📚 Books worth reading
Hyper-HeuristicsNelishia Pillay, Rong Qu · 2018
Learning and Intelligent OptimizationYoussef Hamadi · 2012
Evolutionary Computation in Combinatorial OptimizationMartin Middendorf · 2013- 📕Advances in Hyper-HeuristicsNelishia Pillay, Rong Qu · 2025
Applications of Evolutionary ComputationAnna Isabel Esparcia-Alcázar · 2013
A field guide to genetic programmingRiccardo Poli · 2008
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Metaheuristic In computer science and mathematical optimization, a metaheuristic is a higher-level procedure or heuristic designed to find, generate, tune, or select…
- Memetic algorithm In computer science and operations research, a memetic algorithm (MA) is an extension of an evolutionary algorithm (EA) that aims to accelerate the evolutionary…
- Meta-optimization Meta-optimization from numerical optimization is the use of one optimization method to tune another optimization method. Meta-optimization is reported…
- List of metaphor-based metaheuristics This is a chronologically ordered list of metaphor-based metaheuristics and swarm intelligence algorithms, sorted by decade of proposal. Simulated annealing…
- Constructive cooperative coevolution The constructive cooperative coevolutionary algorithm (also called C3) is a global optimisation algorithm in artificial intelligence based on the multi-start…
- Memetic computing Memetic computing is a novel computational paradigm that incorporates the notion of meme(s) as basic units of transferable information encoded in computational…
- Evolutionary computation Evolutionary computation (EC) from computer science is a family of algorithms for global optimization inspired by biological evolution, and a subfield…
- Evolutionary algorithm Evolutionary algorithms (EA) reproduce essential elements of biological evolution in a computer algorithm in order to solve "difficult" problems, at least…