Results 11 to 20 of about 3,693 (219)
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
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Applied Sciences, 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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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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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
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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
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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 +5 more
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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
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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
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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IET Networks, EarlyView., 2022 Abstract Everything can be connected in the Internet of Things (IoTs) technology that enables efficient communication between connected objects. IoTs industry‐based meta‐heuristic and mining algorithms, which are considered an important field of Artificial Intelligence will be used to construct a healthcare application in this study for lowering costs,
Muhaned Al‐Hashimi +4 more
wiley +1 more source