Results 61 to 70 of about 419,297 (312)
Mathematics, 2020 In this research, an easy-to-use particle swarm optimizer (PSO) for solving constrained engineering design problems involving mixed-integer-discrete-continuous (MIDC) variables that adopt two kinds of diversity-enhancing mechanisms to achieve superior ...
Tae-Hyoung Kim +2 more
doaj +1 more source
Automatic Convexity Deduction for Efficient Function’s Range Bounding
Mathematics, 2021 Reliable bounding of a function’s range is essential for deterministic global optimization, approximation, locating roots of nonlinear equations, and several other computational mathematics areas.
Mikhail Posypkin, Oleg Khamisov
doaj +1 more source
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Patients with chronic kidney disease undergoing hemodialysis commonly experience reduced physical function, fatigue, poor sleep quality, and impaired health‐related quality of life. Intradialytic exercise has been proposed as a non‐pharmacological strategy to improve these outcomes.
Klebson da Silva Almeida +6 more
wiley +1 more source
Global Optimization of Gaussian processes
CoRR, 2020 Gaussian processes~(Kriging) are interpolating data-driven models that are frequently applied in various disciplines. Often, Gaussian processes are trained on datasets and are subsequently embedded as surrogate models in optimization problems. These optimization problems are nonconvex and global optimization is desired.
Schweidtmann, Artur M. +6 more
openaire +3 more sources
The cluster problem in constrained global optimization [PDF]
, 2017 Deterministic branch-and-bound algorithms for continuous global optimization often visit a large number of boxes in the neighborhood of a global minimizer, resulting in the so-called cluster problem (Du and Kearfott in J Glob Optim 5(3):253–265, 1994 ...
Rohit Kannan +4 more
core +1 more source
EOFA: An Extended Version of the Optimal Foraging Algorithm for Global Optimization Problems
ComputationThe problem of finding the global minimum of a function is applicable to a multitude of real-world problems and, hence, a variety of computational techniques have been developed to efficiently locate it.
Glykeria Kyrou +2 more
doaj +1 more source
Algorithms, 2022 The article offers a possible treatment for the numerical research of tasks which require searching for an absolute optimum. This approach is established by employing both globalized nature-inspired methods as well as local descent methods for ...
Pavel Sorokovikov, Alexander Gornov
doaj +1 more source
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Establishing a comprehensive apheresis medicine program in a resource‐constrained setting presents significant structural, financial, and logistical challenges. Despite the growing clinical importance of apheresis services globally, published experience from sub‐Saharan Africa remains sparse.
Folasade Adelekan‐Popoola +4 more
wiley +1 more source
A Heuristic for Nonlinear Global Optimization [PDF]
INFORMS Journal on Computing, 2010 We propose a new heuristic for nonlinear global optimization combining a variable neighborhood search framework with a modified trust-region algorithm as local search. The proposed method presents the capability to prematurely interrupt the local search if the iterates are converging to a local minimum that has already been visited or if they are ...
Bierlaire, Michel +2 more
openaire +5 more sources
Machine Learning and Knowledge ExtractionThe electrical storm optimization (ESO) algorithm, inspired by the dynamic nature of electrical storms, is a novel population-based metaheuristic that employs three dynamically adjusted parameters: field resistance, field intensity, and field ...
Manuel Soto Calvo, Han Soo Lee
doaj +1 more source