Results 111 to 120 of about 1,840,782 (294)
Why Methods for Optimization Problems with Time-Consuming Function Evaluations and Integer Variables Should Use Global Approximation Models [PDF]
This paper advocates the use of methods based on global approximation models for optimization problems with time-consuming function evaluations and integer variables.We show that methods based on local approximations may lead to the integer rounding of ...
Brekelmans, R.C.M. +4 more
core
A contribution to theory and practice of nonlinear parameter optimization [PDF]
, 1975 Nonlinear parameter optimization in least squares was studied from a point of view of differential geometry. Properties of curvilinear coordinates, scale factors and curvature were investigated.
Stol, P.T.
core
An Improved Unconstrained Approach for Bilevel Optimization
, 2022 In this paper, we focus on the nonconvex-strongly-convex bilevel optimization problem (BLO). In this BLO, the objective function of the upper-level problem is nonconvex and possibly nonsmooth, and the lower-level problem is smooth and strongly convex ...
Hu, Xiaoyin +3 more
core
Degradation Mechanism of Phosphate‐Based Li‐NASICON Conductors in Alkaline Environment
Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.The presence of water in the cathode of a Li‐air battery shifts reactions to produce LiOH, creating a corrosive, alkaline environment. This study investigates the alkaline stability of the common Li‐NASICON solid‐state conductor chemistries through a systematic experimental study combined with computational modeling to understand the degradation ...
Benjamin X. Lam +3 more
wiley +1 more source
Comparison of response surface methodology and the Nelder and Mead simplex method for optimization in microsimulation models [PDF]
Microsimulation models are increasingly used in the evaluation of cancer screening. Latent parameters of such models can be estimated by optimization of the goodness-of-fit.
Neddermeijer, H.G. +4 more
core
Advanced Energy Materials, EarlyView.Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source
AIChE Journal, EarlyView.Abstract Sorption in glassy polymer membranes is commonly modeled with the dual‐mode sorption (DMS) model. Fitting the DMS model to sorption isotherms presents challenges, as multiple parameter sets may prove satisfactory. This work presents pyDMS, an open‐source Python package for the computation of DMS parameters obtained via a physics‐informed ...
Brandon C. Tapia +4 more
wiley +1 more source
Two Algorithms for Solving Unconstrained Global Optimization by Auxiliary Function Method
Tikrit Journal of Pure ScienceIn this paper, we present two algorithms that are designed to solve unconstrained global optimization problems. The first algorithm is introduced for resolving unconstrained optimization problems by dividing a multidimensional problem into partitions of
Shehab Ahmed Ibrahem +2 more
doaj +1 more source
Methods for large scale unconstrained optimization
, 2010 In this article, we review methods for the solution of unconstrained optimization problems, where the number of unknowns is large.We first describe the basics of unconstrained optimization, then we consider the iterative methods that are commonly used ...
FASANO, Giovanni, FASANO G.
core
Advanced Intelligent Discovery, EarlyView.This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source