Results 51 to 60 of about 3,693 (219)
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 resource allocation in distributed mobile edge computing environment is consider as a challenging and ...
B. Vijayaram, V. Vasudevan
doaj +1 more source
Automated generation of constructive ordering heuristics for educational timetabling [PDF]
Construction heuristics play an important role in solving combinatorial optimization problems. These heuristics are usually used to create an initial solution to the problem which is improved using optimization techniques such as metaheuristics.
B McCollum +12 more
core +2 more sources
Hyper-heuristic decision tree induction [PDF]
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
A Hyper-Heuristic for the Orienteering Problem With Hotel Selection
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 +2 more
doaj +1 more source
A stochastic local search algorithm with adaptive acceptance for high-school timetabling [PDF]
Automating high school timetabling is a challenging task. This problem is a well known hard computational problem which has been of interest to practitioners as well as researchers.
A Hertz +25 more
core +4 more sources
Hyper-heuristics: A survey and taxonomy
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 +2 more
openaire +2 more sources
Enhancing Selection Hyper-Heuristics via Feature Transformations [PDF]
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. +6 more
openaire +2 more sources
Non‐Equilibrium Synthesis Methods to Create Metastable and High‐Entropy Nanomaterials
ABSTRACT Stabilizing multiple elements within a single phase enables the creation of advanced materials with exceptional properties arising from their complex composition. However, under equilibrium conditions, the Hume–Rothery rules impose strict limitations on solid‐state miscibility, restricting combinations of elements with mismatched crystal ...
Shuo Liu +3 more
wiley +1 more source
Intelligent System Design Using Hyper-Heuristics
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
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 +10 more
wiley +1 more source

