Results 41 to 50 of about 4,754 (207)

How Much Is Too Much? Facing Practical Limitations in Hyper-Heuristic Design for Packing Problems

Algorithms
Hyper-heuristics, or simply heuristics to choose heuristics, represent a powerful approach to tackling complex optimization problems. These methods decide which heuristic to apply throughout the solving process, aiming to improve the solving process ...
José Carlos Ortiz-Bayliss, Alonso Vela Morales, Ivan Amaya   +2 more
doaj   +1 more source

Intelligent System Design Using Hyper-Heuristics

South African Computer Journal, 2015
Determining the most appropriate search method or artificial intelligence technique to solve a problem is not always evident and usually requires implementation of the different approaches to ascertain this. In some instances a single approach may not be
Nelishia Pillay
doaj   +1 more source

Algorithm Selection for Allocating Pods Within Robotic Mobile Fulfillment Systems: A Hyper-Heuristic Approach

IEEE Access
Robotic Mobile Fulfillment Systems (RMFS) are an example of warehouse automation. Nonetheless, the complexity of RMFS is such that tackling the entire problem at once is unfeasible. So, this work focuses on a component known as the Pod Allocation Problem
Maria Torcoroma Benavides-Robles, Jorge M. Cruz-Duarte, Jose Carlos Ortiz-Bayliss, Ivan Amaya   +3 more
doaj   +1 more source

Batched Mode Hyper-heuristics [PDF]

, 2013
A primary role for hyper-heuristics is to control search processes based on moves generated by neighbourhood operators. Studies have shown that such hyper-heuristics can be effectively used, without modification, for solving unseen problem instances not only from a particular domain, but also on different problem domains.
Shahriar Asta, Ender Özcan, Andrew J. Parkes   +2 more
openaire   +1 more source

The Scientific Landscape of Hyper-Heuristics: A Bibliometric Analysis Based on Scopus

Algorithms
Hyper-heuristics emerged as a broader metaheuristic framework to address the limitations of traditional optimization heuristics. By abstracting the design of low-level heuristics, hyper-heuristics offer a flexible and adaptable approach to solving ...
Helen C. Peñate-Rodríguez, Gilberto Rivera, J. Patricia Sánchez-Solís, Rogelio Florencia   +3 more
doaj   +1 more source

Hyper-heuristic decision tree induction [PDF]

2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 2009
Hyper-heuristics are increasingly used in function and combinatorial optimization. Rather than attempt to solve a problem using a fixed heuristic, a hyper-heuristic approach attempts to find a combination of heuristics that solve a problem (and in turn may be directly suitable for a class of problem instances).
Alan Vella, David Corne, Chris Murphy
openaire   +1 more source

HyperDE: An Adaptive Hyper-Heuristic for Global Optimization

Algorithms, 2023
In this paper, a novel global optimization approach in the form of an adaptive hyper-heuristic, namely HyperDE, is proposed. As the naming suggests, the method is based on the Differential Evolution (DE) heuristic, which is a well-established ...
Alexandru-Razvan Manescu, Bogdan Dumitrescu   +1 more
doaj   +1 more source

Hyper-heuristics: A survey and taxonomy

Computers & Industrial Engineering
Hyper-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.
Dokeroglu, Tansel, Kucukyilmaz, Tayfun, Talbi, El-Ghazali   +2 more
openaire   +2 more sources

Enhancing Selection Hyper-Heuristics via Feature Transformations [PDF]

IEEE Computational Intelligence Magazine, 2018
Hyper-heuristics are a novel tool. They deal with complex optimization problems where standalone solvers exhibit varied performance. Among such a tool reside selection hyper-heuristics. By combining the strengths of each solver, this kind of hyper-heuristic offers a more robust tool.
Amaya, I., Ortiz-Bayliss, J. C., Rosales-Pérez, A., Gutiérrez-Rodríguez, A. E., Conant-Pablos, S. E., Terashima-Marín, H., Coello, C. A. Coello   +6 more
openaire   +2 more sources

Identification of Exhaled Volatile Organic Compounds Biomarkers for Lung Cancer Under Data‐Limited Conditions Using Data Augmentation and Multi‐View Feature Selection

Advanced Intelligent Discovery, EarlyView.
This work introduces a novel framework for identifying non‐small cell lung cancer biomarkers from hundreds of volatile organic compounds in breath, analyzed via gas chromatography‐mass spectrometry. This method integrates generative data augmentation and multi‐view feature selection, providing a stable and accurate solution for biomarker discovery in ...
Guancheng Ren, Bohao Liu, Zhiyuan Qu, Xue Jiang, Heng Zhao, Danyao Qu, Ruizhi Ning, Chen Su, Taoping Liu, Guangjian Zhang, Weiwei Wu   +10 more
wiley   +1 more source