Results 51 to 60 of about 3,794 (238)

Wireless edge device intelligent task offloading in mobile edge computing using hyper-heuristics

EURASIP Journal on Advances in Signal Processing, 2022
To overcome with the computation limitation of resource-constrained wireless IoT edge devices, providing an efficient task computation offloading and resource allocation in distributed mobile edge computing environment is consider as a challenging and ...
B. Vijayaram, V. Vasudevan
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

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

A Hyper-Heuristic for the Orienteering Problem With Hotel Selection

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, Maria-Cristina Riff, Bertrand Neveu   +2 more
doaj   +1 more source

Automated construction of evolutionary algorithm operators for the bi-objective water distribution network design problem using a genetic programming based hyper-heuristic approach [PDF]

, 2015
The water distribution network (WDN) design problem is primarily concerned with finding the optimal pipe sizes that provide the best service for minimal cost; a problem of continuing importance both in the UK and internationally.
Keedwell, Edward, McClymont, Kent, Randall-Smith, Mark, Savic, Dragan   +3 more
core   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +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

An Ant Colony based Hyper-Heuristic Approach for the Set Covering Problem

Advances in Distributed Computing and Artificial Intelligence Journal, 2015
The Set Covering Problem (SCP) is a NP-hard combinatorial optimization problem that is challenging for meta-heuristic algorithms. In the optimization literature, several approaches using meta-heuristics have been developed to tackle the SCP and the ...
Alexandre Silvestre FERREIRA, Aurora POZO, Richard Aderbal GONÇALVES   +2 more
doaj   +1 more source