Results 41 to 50 of about 50,778 (275)
Automatic Design of Metaheuristics for Practical Engineering Applications
IEEE Access, 2023 It is common to find multiple metaheuristics to solve continuous optimization problems. However, choosing what optimizer may obtain the best results for a given task requires exhaustive evaluations that are highly application-dependent.
Daniel F. Zambrano-Gutierrez +5 more
doaj +1 more source
Addressing the 5G cell switch-off problem with a multi-objective cellular genetic algorithm [PDF]
, 2018 © 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new ...
Luna, Francisco +4 more
core +1 more source
Brazilian Journal of Radiation Sciences, 2019 This paper brings to light optimized proposal for a circular particle accelerator for proton beam therapy purposes (named as ACPT). The methodology applied is based on computational metaheuristics based on genetic algorithms (GA) were used to obtain ...
Gustavo Lobato Campos +1 more
doaj +1 more source
A Walk into Metaheuristics for Engineering Optimization: Principles, Methods and Recent Trends [PDF]
International Journal of Computational Intelligence Systems, 2015 Metaheuristics has attained increasing interest for solving complex real-world problems. This paper studies the principles and the state-of-the-art of metaheuristic methods for engineering optimization.
Ning Xiong +3 more
doaj +1 more source
A synthesis of logic and biology in the design of dependable systems [PDF]
, 2015 The technologies of model-based design and dependability analysis in the design of dependable systems, including software intensive systems, have advanced in recent years.
Papadopoulos, Yiannis
core +1 more source
Energy Reports, 2022 The management of renewable-powered smart grids deals with nonlinear optimization problems featuring a variety of linear or nonlinear constraints, discrete or continuous optimization variables, involving high dimensionality of the solution space, and ...
Cristina Bianca Pop +6 more
doaj +1 more source
Multi-Objective Big Data Optimization with jMetal and Spark [PDF]
, 2017 Big Data Optimization is the term used to refer to optimization problems which have to manage very large amounts of data. In this paper, we focus on the parallelization of metaheuristics with the Apache Spark cluster computing system for solving multi ...
A Cabanas-Abascal +11 more
core +1 more source
Firefly Algorithm: Recent Advances and Applications [PDF]
, 2013 Nature-inspired metaheuristic algorithms, especially those based on swarm intelligence, have attracted much attention in the last ten years. Firefly algorithm appeared in about five years ago, its literature has expanded dramatically with diverse ...
He, Xingshi, Yang, Xin-She
core +1 more source
Advanced Intelligent Discovery, EarlyView.A machine learning‐guided self‐driving laboratory screened over 500 nickel‐based layered double‐hydroxide catalysts for alkaline oxygen evolution. Out of the eight metals, the robot uncovered a quaternary Ni–Fe–Cr–Co catalysts requiring only 231 mV overpotential to reach 20 mA cm−2.
Nis Fisker‐Bødker +3 more
wiley +1 more source
A Fully Soft Sensing Suit With Optimal Sensor Placement for Real‐Time Motion Tracking
Advanced Intelligent Systems, EarlyView.A fully soft, skin‐conformable sensing suit integrating stretchable sensors, liquid metal wiring, and soft electrodes was developed using direct ink writing, with sensor placement optimized through an automated algorithmic pipeline. This system enables accurate and unobtrusive real‐time motion tracking, providing a scalable, material‐based solution to ...
Jinhyeok Oh, Joonbum Bae
wiley +1 more source