Search
Search Results
-
Derivative-free separable quadratic modeling and cubic regularization for unconstrained optimization
We present a derivative-free separable quadratic modeling and cubic regularization technique for solving smooth unconstrained minimization problems....
-
A derivative-free line search technique for Broyden-like method with applications to NCP, wLCP and SI
We propose a new derivative-free line search technique which contains the classical Li-Fukushima derivative-free line search [Optim. Methods Softw....
-
Managing low–acuity patients in an Emergency Department through simulation–based multiobjective optimization using a neural network metamodel
This paper deals with Emergency Department (ED) fast-tracks for low-acuity patients, a strategy often adopted to reduce ED overcrowding. We focus on...
-
Newton’s Method for Global Free Flight Trajectory Optimization
Globally optimal free flight trajectory optimization can be achieved with a combination of discrete and continuous optimization. A key requirement is...
-
Use of Static Surrogates in Hyperparameter Optimization
Optimizing the hyperparameters and architecture of a neural network is a long yet necessary phase in most applications. This consuming process can...
-
End-to-end risk budgeting portfolio optimization with neural networks
Traditional stochastic optimization in financial operations research applications consist of a two-step process: (1) calibrate parameters of the...
-
Smoothing inexact Newton method based on a new derivative-free nonmonotone line search for the NCP over circular cones
In this paper we consider the nonlinear complementarity problem over circular cones (CCNCP) which contains a lot of circular cone optimization...
-
Revenue maximization based joint optimization in mmWave cell-free network: an equivalent decomposition and alternative iteration combined approach
Recently, the ever-increasing demands including higher rate and connection stability have bottlenecked the user experience of the traditional...
-
Practicable robust stochastic optimization under divergence measures with an application to equitable humanitarian response planning
We seek to provide practicable approximations of the two-stage robust stochastic optimization model when its ambiguity set is constructed with an f -di...
-
GTIACO: energy efficient clustering algorithm based on game theory and improved ant colony optimization
Recently, wireless sensor networks have been widely used for environmental and structural safety monitoring. However, node batteries cannot be...
-
A General Mathematical Framework for Constrained Mixed-variable Blackbox Optimization Problems with Meta and Categorical Variables
A mathematical framework for modelling constrained mixed-variable optimization problems is presented in a blackbox optimization context. The...
-
Enhanced index tracking problem: a new optimization model and a sum-of-ratio based algorithm
Enhanced index tracking as one of the approaches of stock portfolio selection has received great attention from researchers. In this paper, a new...
-
Portfolio optimization and marginal contribution to risk on multivariate normal tempered stable model
This paper proposes a market model with returns assumed to follow a multivariate normal tempered stable distribution defined by a mixture of the...
-
An optimization framework for large-scale screening under limited testing capacity with application to COVID-19
We consider the problem of targeted mass screening of heterogeneous populations under limited testing capacity. Mass screening is an essential tool...
-
Robust selective maintenance optimization of series–parallel mission-critical systems subject to maintenance quality uncertainty
This paper studies the optimization of the joint selective maintenance and repairperson assignment problem when the quality of maintenance actions is...
-
Non-monotone derivative-free algorithm for solving optimization models with linear constraints: extensions for solving nonlinearly constrained models via exact penalty methods
This paper describes a non-monotone direct search method (NMDSM) that finds a stationary point of linearly constrained minimization problems. At each...
-
Nonlinear optimization and support vector machines
Support vector machine (SVM) is one of the most important class of machine learning models and algorithms, and has been successfully applied in...
-
Essentials of numerical nonsmooth optimization
Approximately sixty years ago two seminal findings, the cutting plane and the subgradient methods, radically changed the landscape of mathematical...
-
Optimization of Port Cluster Facilities and Equipment Resources Operation
By summarizing the characteristics of yard, domestic and foreign scholars divide the study of yard operation optimization into two categories from...
-
Cloud computing load prediction by decomposition reinforced attention long short-term memory network optimized by modified particle swarm optimization algorithm
Computer resources provision over the internet resulted in the wide spread usage of cloud computing paradigm. With the use of such resources come...
