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A generality analysis of multiobjective hyper-heuristics
Information Sciences, 2023 Wenwen Li +2 more
exaly +2 more sources
Assessing hyper-heuristic performance [PDF]
Journal of the Operational Research Society, 2020 Limited attention has been paid to assessing the generality performance of hyper-heuristics. The performance of hyper-heuristics has been predominately assessed in terms of optimality which is not ideal as the aim of hyper-heuristics is not to be competitive with state of the art approaches but rather to raise the level of generality, i.e.
Nelishia Pillay, Rong Qu
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A Feature-Independent Hyper-Heuristic Approach for Solving the Knapsack Problem
Applied Sciences, 2021 Recent years have witnessed a growing interest in automatic learning mechanisms and applications. The concept of hyper-heuristics, algorithms that either select among existing algorithms or generate new ones, holds high relevance in this matter.
Xavier Sánchez-Díaz +5 more
doaj +1 more source
Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, 2015 Practitioners often need to solve real world problems for which no custom search algorithms exist. In these cases they tend to use general-purpose solvers that have no guarantee to perform well on their specific problem. The relatively new field of hyper-heuristics provides an alternative to the potential pit-falls of general-purpose solvers, by ...
John R. Woodward, Daniel R. Tauritz
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Identifying Hyper-Heuristic Trends through a Text Mining Approach on the Current Literature
Applied Sciences, 2022 Hyper-heuristics have arisen as methods that increase the generality of existing solvers. They have proven helpful for dealing with complex problems, particularly those related to combinatorial optimization.
Anna Karen Gárate-Escamilla +4 more
doaj +1 more source
Algorithms, 2022 Hyper-heuristics are widely used for solving numerous complex computational search problems because of their intrinsic capability to generalize across problem domains.
Stephen A. Adubi +2 more
doaj +1 more source
PHH: Policy-Based Hyper-Heuristic With Reinforcement Learning
IEEE Access, 2023 Hyper-heuristics have a high level of generality and adaptability, allowing them to effectively solve a wide range of complex optimization problems.
Orachun Udomkasemsub +2 more
doaj +1 more source
Hyper-heuristics for personnel scheduling domains
Artificial Intelligence, 2022 In real-life applications problems can frequently change or require small adaptations. Manually creating and tuning algorithms for different problem domains or different versions of a problem can be cumbersome and time-consuming. In this paper we consider several important problems with high practical relevance, which are Bus Driver Scheduling ...
Lucas Kletzander, Nysret Musliu
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Evolution of group-theoretic cryptology attacks using hyper-heuristics
Journal of Mathematical Cryptology, 2021 In previous work, we developed a single evolutionary algorithm (EA) to solve random instances of the Anshel–Anshel–Goldfeld (AAG) key exchange protocol over polycyclic groups. The EA consisted of six simple heuristics which manipulated strings.
Craven Matthew J., Woodward John R.
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Adaptive secure malware efficient machine learning algorithm for healthcare data
CAAI Transactions on Intelligence Technology, EarlyView., 2023 Abstract Malware software now encrypts the data of Internet of Things (IoT) enabled fog nodes, preventing the victim from accessing it unless they pay a ransom to the attacker. The ransom injunction is constantly accompanied by a deadline. These days, ransomware attacks are too common on IoT healthcare devices.
Mazin Abed Mohammed +8 more
wiley +1 more source