Results 71 to 80 of about 111,305 (313)
Goal seeking Quadratic Unconstrained Binary Optimization
The Quadratic Unconstrained Binary Optimization (QUBO) modeling and solution framework is a requirement for quantum and digital annealers. However optimality for QUBO problems of any practical size is extremely difficult to achieve.
Amit Verma, Mark Lewis
doaj
Abstract Modern longitudinal data from wearable devices consist of biological signals at high‐frequency time points. Distributed statistical methods have emerged as a powerful tool to overcome the computational burden of estimation and inference with large data, but methodology for distributed functional regression remains limited.
Cole Manschot, Emily C. Hector
wiley +1 more source
On the Relationship Between Financial Distress and ESG Scores
ABSTRACT This empirical study analyzes the relationship between a company's financial distress obtained from a bankruptcy prediction model and ESG scores from Refinitiv, MSCI, ESG Book, and Moody's ESG. Applying a nonparametric regression technique on panel data of listed US companies for 2003–2022 reveals a pronounced and statistically significant U ...
Christian Lohmann+2 more
wiley +1 more source
Hessian sufficiency for bordered Hessian [PDF]
We show that the second–order condition for strict local extrema in both constrained and unconstrained optimization problems can be expressed solely in terms of principal minors of the (Lagrengean) [sic] Hessian.
Im, Eric Iksoon
core
This study focused on reducing the simulation counts required for circuit sizing by optimizing the initial population selection in evolutionary algorithms. We investigated the impact of different sampling methods on the efficiency of multi‐objective optimization based on differential evolution and Bayesian inference, a leading algorithm in circuit ...
Georgian Nicolae+5 more
wiley +1 more source
A Novel Conjugate Gradient Algorithm as a Convex Combination of Classical Conjugate Gradient Methods
Conjugate gradient (CG) algorithms are constructive for handling large-scale nonlinear optimization problems. One optimization technique intended to address unconstrained optimization issues effectively is the hybrid conjugate gradient (HCG) algorithm ...
Sara Sahib Mohammed Zaki+2 more
doaj +1 more source
A new algorithm for general multiobjective optimization [PDF]
Described is a new technique for converting a constrained optimization problem to an unconstrained one, and a new method for multiobjective optimization based on that technique. The technique transforms the objective functions into goal constraints.
Dovi, Augustine R.+2 more
core +1 more source
Tri‐axial compressive behavior of high‐water material for deep underground spaces
The relationship between the mechanical behavior and microstructures of the laterally confined high‐water material associated with water bleeding was established. Abstract Attributed to its superior water‐to‐solid ratio and quick setting time, the high‐water material is widely adopted in underground spaces as a cost‐effective and environmentally ...
Honglin Liu+5 more
wiley +1 more source
We propose a new method for equality constrained optimization based on augmented Lagrangian method. We construct an unconstrained subproblem by adding an adaptive quadratic term to the quadratic model of augmented Lagrangian function.
Hao Zhang, Qin Ni
doaj +1 more source
Optimal zoning in the unconstrained Hotelling game
This paper studies a zoning mechanism that gives the optimal locations of two firms in a linear city under mill prices. A regulator biased towards consumers allows a central area of the city to be shared by firms and consumers and thus firms are not allowed to locate outside the city limits.
Rodríguez Iglesias, Isabel+3 more
openaire +3 more sources