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An Exploratory Study on Machine-Learning-Based Hyper-heuristics for the Knapsack Problem
Hyper-heuristics have risen as a recurrent method to solve combinatorial optimization problems since they use a set of heuristics selectively...
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Online Learning Hyper-Heuristics in Multi-Objective Evolutionary Algorithms
Well-defined Hyper-Heuristics enhance the generalization of MOEAs and the blind usability on complex and even dynamic real-world application....
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Test Case Features as Hyper-heuristics for Inductive Programming
Instruction subsets are heuristics that can reduce the size of the inductive programming search space by tens of orders of magnitude. Comprising many...
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Automated Design of Dynamic Heuristic Set Selection for Cross-Domain Selection Hyper-Heuristics
Selection hyper-heuristics have been used successfully to solve hard optimization problems. These techniques choose a heuristic or a group of...
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Wireless edge device intelligent task offloading in mobile edge computing using hyper-heuristics
To overcome with the computation limitation of resource-constrained wireless IoT edge devices, providing an efficient task computation offloading and...
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Metaheuristics and Hyper-heuristics Based on Evolutionary Algorithms for Software Integration Testing
Hyper-heuristics have been identified as optimisation algorithms that would have better generalisation capabilities than metaheuristics. In this...
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Rigorous Performance Analysis of Hyper-heuristics
We provide an overview of the state-of-the-art in the time complexity analysis of selection hyper-heuristics for combinatorial optimisation. These...
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Hyper-heuristics: Autonomous Problem Solvers
Algorithm design is a general task for any problem-solving scenario. For Search and Optimization, this task becomes rather challenging due to the...
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Dynamic Heuristic Set Selection for Cross-Domain Selection Hyper-heuristics
Selection hyper-heuristics have proven to be effective in solving various real-world problems. Hyper-heuristics differ from traditional heuristic...
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Public transport network optimisation in PTV Visum using selection hyper-heuristics
Despite the progress in the field of automatic public transport route optimisation in recent years, there exists a clear gap between the development...
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Ant-Based Hyper-Heuristics for the Movie Scene Scheduling Problem
The paper provides a study of the use of hyper-heuristics on the movie scene scheduling problem. In particular, the paper extends the definition of...
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Dynamic Learning in Hyper-Heuristics to Solve Flowshop Problems
Hyper-heuristics (HHs) are algorithms suitable for designing heuristics. HHs perform the search divided in two levels: they look for heuristic...
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Knowledge Transfer in Genetic Programming Hyper-heuristics
Genetic Programming Hyper-heuristics (GPHHs) have been successfully applied in various problem domains for automatically designing heuristics such as...
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A Study on the Use of Hyper-heuristics Based on Meta-Heuristics for Dynamic Optimization
The study of dynamic multi-objective optimization problems (DMOP) is an area that has recently been receiving increased attention from researchers....
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Ant-Based Generation Constructive Hyper-heuristics for the Movie Scene Scheduling Problem
The task of generation constructive hyper-heuristics concerns itself with generating new heuristics for problem domains via some kind of mechanism...
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Stochastic online decisioning hyper-heuristic for high dimensional optimization
Most existing heuristic optimizers are found to be restricted to problems of moderate dimensionality, and their performance suffers when solving...
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Hypervolume Indicator as an Estimator for Adaptive Operator Selection in an On-Line Multi-objective Hyper-heuristic
Online hyper-heuristics are algorithms capable of solving complex real-world problems. This approach dynamically selects, based on the quality of a...
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Hypervolume Indicator as an Estimator for Adaptive Operator Selection in an On-Line Multi-objective Hyper-heuristic
Online Hyper-heuristics is a powerful approach when solving complex real-world problems. This approach dynamically selects, based on the quality of a...
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A novel evolutionary status guided hyper-heuristic algorithm for continuous optimization
This paper proposes a novel evolutionary status guided hyper-heuristic algorithm named ES-HHA for continuous optimization. A representative...
