Results 121 to 130 of about 19,980 (297)
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 +1 more source
Unconstrained Optimization [PDF]
, 1999 This lecture note is intended for use in the course 04212 Optimization and Data Fitting at the Technincal University of Denmark. It covers about 25% of the curriculum. Hopefully, the note may be useful also to interested persons not participating in that
Poul Erik Frandsen +7 more
core
Vernacular Futurism: How Persian Language Users Imagine AI
AI &Innovation, EarlyView.ABSTRACT Public discourse about artificial intelligence increasingly unfolds through compressed forecasts, moral warnings, and everyday speculation circulating at platform speed. This study examines how Persian language users on X construct and contest AI futures, analyzing a corpus of 4741 posts collected between January 2023 and December 2025, with ...
Arthur Asa Berger, Ehsan Shahghasemi
wiley +1 more source
Some modifications of conjugate gradient coefficient for unconstrained optimization [PDF]
, 2010 Conjugate gradient methods hold an important role in unconstrained optimization. Numerous studies and modifications have been done recently to improve this method. However, these new modifications tend to be complicated and difficult.
Mohd Rivaie Mohd Ali
core
AI &Innovation, EarlyView.ABSTRACT Maintaining an effective balance between exploration and exploitation is essential during optimization processes, from mathematical functions to more complex problems such as constrained engineering design optimization, particularly when addressing highly nonlinear issues with numerous local optima and strict feasibility requirements.
Enrique Lizárraga +3 more
wiley +1 more source
Parallel Unconstrained Optimization [PDF]
, 1993 We deal with the parallel solution of the nonlinear, unconstrained, optimization problem minff(x) j x 2 R n g where the objective function f : R n ! R is continuous and differentiable.
Kwok L. Chow
core
Tensor Methods for Large, Sparse Unconstrained Optimization [PDF]
, 1994 Tensor methods for unconstrained optimization were first introduced in Schnabel and Chow [SIAM Journal on Optimization, 1 (1991), pp. 293-315], who describe these methods for small to moderate size problems.
Ali Bouaricha
core
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
Asia-Pacific Journal of Chemical Engineering, EarlyView.ABSTRACT The global trend toward sustainable and intensified bioprocesses is driving innovation in the design and scalable synthesis of liposomal nanocarriers, a cornerstone of modern drug delivery. For decades, these nanosystems have relied exclusively on polyethylene glycol (PEG) for their sustained circulation in vivo, but they are currently ...
Chandra Has
wiley +1 more source
Multi-Objective Optimization Technique Based on QUBO and an Ising Machine
IEEE AccessWith an increase in the complexity of society, solving multi-objective optimization problems (MOPs) has become crucial. In this study, we introduced a novel method called “quadratic unconstrained binary optimization based on the weighted normal ...
Hiroshi Ikeda, Takashi Yamazaki
doaj +1 more source