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Subjects / keywords: Linear programming; Algebras, Linear; Industrial management; Electronic books

Subjects / keywords: Linear programming; Network analysis (Planning); Mathematical optimization; Dynamic programming; Electronic books

Subjects / keywords: Linear programming; Programming (Mathematics); Electronic books

Subjects / keywords: Linear programming; Mathematical models; PERT (Network analysis); Critical path analysis

Subjects / keywords: Linear programming; Mathematical models; Critical path analysis; PERT (Network analysis); Electronic books

Subjects / keywords: Linear programming; Problems, exercises, etc; Graph theory

Transportation networks are sized to efficiently achieve some set of service objectives. Under particular circumstances, such as the COVID-19 pandemic, the demand for transportation can significantly change, both qualita...

Subjects / keywords: Mathematical optimization; Numerical analysis; Linear programming

Subjects / keywords: Algebras, Linear; Vector algebra; Linear programming; Electronic books

The distributed optimization problem is set up in a collection of nodes interconnected via a communication network. The goal is to find the minimizer of a global objective function formed by the sum of local functions kn...

Subjects / keywords: Operations research; Management; Research; Linear programming; Electronic books

Subjects / keywords: Operations research; Management; Research; Commercial crimes; Linear programming; Organizational effectiveness; Evaluation; Electronic books

Increasing crop diversity in agricultural landscapes can increase biodiversity but it is unclear how different diversification strategies affect crop diversity across spatial scales. Here we compared different diversific...

Subjects / keywords: Numerical analysis; Linear programming; Equations; Numerical solutions; Electric power systems; Mathematical models; Engineering mathematics

Available for the first time in paperback, R. Tyrrell Rockafellar's classic study presents readers with a coherent branch of nonlinear mathematical analysis that is especially suited to the study of optimization problems...

In management contexts, mathematical programming is usually used to evaluate a collection of possible alternative courses of action en route to selecting one which is best. In this capacity, mathematical programming serv...

El objetivo central del proyecto es diseñar algoritmos eficientes para problemas de grafos, previo estudio de su tratabilidad. Nos centramos, en particular, en los problemas de coloreo y transversal en hipergrafos de in...

El trabajo reseña una experiencia educativa en la enseñanza de la estructuración de redes de intercambio térmico (RIT) mediante el método de Transbordo. La aplicación de la técnica en la que se basa el método, Pr...

Abstract. The Nelder–Mead simplex algorithm, first published in 1965, is an enormously popular direct search method for multidimensional unconstrained minimization. Despite its widespread use, essentially no theoretica...

Fully describes optimization methods that are currently most valuable in solving real-life problems. Since optimization has applications in almost every branch of science and technology, the text emphasizes their practic...

Collinearity refers to the non independence of predictor variables, usually in a regression‐type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation bec...

We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multi- nomial regression problems while the penalties...

Summary In the analysis of data it is often assumed that observations y 1, y 2, …, yn are independently normally distributed with constant variance and with expectations specified by a model linear in a set of paramete...

The purpose of model selection algorithms such as All Subsets, Forward Selection and Backward Elimination is to choose a linear model on the basis of the same set of data to which the model will be applied. Typically we ...