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Towards the Design of Heuristics by Means of Self-Assembly [PDF]
Electronic Proceedings in Theoretical Computer Science, 2010 The current investigations on hyper-heuristics design have sprung up in two different flavours: heuristics that choose heuristics and heuristics that generate heuristics.
Natalio Krasnogor +2 more
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A review of reinforcement learning based hyper-heuristics [PDF]
PeerJ Computer ScienceThe reinforcement learning based hyper-heuristics (RL-HH) is a popular trend in the field of optimization. RL-HH combines the global search ability of hyper-heuristics (HH) with the learning ability of reinforcement learning (RL). This synergy allows the
Cuixia Li +4 more
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Applied Sciences (Switzerland), 2021 As exact algorithms are unfeasible to solve real optimization problems, due to their computational complexity, meta-heuristics are usually used to solve them.
Vinicius Renan de Carvalho +2 more
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A Systematic Review of Hyper-Heuristics on Combinatorial Optimization Problems
IEEE Access, 2020 Hyper-heuristics aim at interchanging different solvers while solving a problem. The idea is to determine the best approach for solving a problem at its current state. This way, every time we make a move it gets us closer to a solution.
Melissa Sanchez +2 more
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Choice Function-Based Hyper-Heuristics for Causal Discovery under Linear Structural Equation Models [PDF]
BiomimeticsCausal discovery is central to human cognition, and learning directed acyclic graphs (DAGs) is its foundation. Recently, many nature-inspired meta-heuristic optimization algorithms have been proposed to serve as the basis for DAG learning.
Yinglong Dang +2 more
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Hyper-heuristics: A survey and taxonomy
Computers and 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.
Tansel Dökeroğlu +2 more
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Beyond Hyper-Heuristics: A Squared Hyper-Heuristic Model for Solving Job Shop Scheduling Problems
IEEE Access, 2022 Hyper-heuristics (HHs) stand as a relatively recent approach to solving optimization problems. There are different kinds of HHs. One of them deals with how low-level heuristics must be combined to deliver an improved solution to a set of problem ...
Alonso Vela +3 more
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Recent advances in selection hyper-heuristics
European Journal of Operational Research, 2020 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ahmed Kheiri +2 more
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A Hyper-Heuristic for the Orienteering Problem With Hotel Selection [PDF]
IEEE Access, 2020 We present a hyper-heuristic approach to solve Orienteering Problem with Hotel Selection (OPHS). In practical applications, OPHS appears when a tourist is planning to visit various attractions and there is not enough time to reach all of them in a single
Alan Toledo +2 more
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A Novel Hyper-Heuristic Algorithm with Soft and Hard Constraints for Causal Discovery Using a Linear Structural Equation Model [PDF]
EntropyArtificial intelligence plays an indispensable role in improving productivity and promoting social development, and causal discovery is one of the extremely important research directions in this field. Acyclic directed graphs (DAGs) are the most commonly
Yinglong Dang +2 more
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