Can I read Modern Optimization Methods for Decision Making Under Risk and Uncertainty on EtoBox?

Modern Optimization Methods for Decision Making Under Risk and Uncertainty by Alexei A. Gaivoronski, Pavel S. Knopov, Volodymyr A. Zaslavskyi, Pavlo S. Knopov is a nonfiction available to read on EtoBox.

What is Modern Optimization Methods for Decision Making Under Risk and Uncertainty about?

The book comprises original articles on topical issues of risk theory, rational decision making, statistical decisions, and control of stochastic systems. The articles are the outcome of a series international projects involving the leading scholars in the field of modern stochastic optimization and decision making. The structure of stochastic optimization solvers is described. The solvers in general implement stochastic quasi-gradient methods for optimization and identification of complex nonlinear models. These models constitute an important methodology for finding optimal decisions under risk and uncertainty. While a large part of current approaches towards optimization under uncertainty stems from linear programming (LP) and often results in large LPs of special structure, stochastic quasi-gradient methods confront nonlinearities directly without need of linearization. This makes them an appropriate tool for solving complex nonlinear problems, concurrent optimization and simulation models, and equilibrium situations of different types, for instance, Nash or Stackelberg equilibrium situations. The solver finds the equilibrium solution when the optimization model describes the sy

Who reads Modern Optimization Methods for Decision Making Under Risk and Uncertainty?

Author

Alexei A. Gaivoronski, Pavel S. Knopov, Volodymyr A. Zaslavskyi, Pavlo S. Knopov

Publisher

CRC Press/Science Publishers

Published

2023

Language

EN

ISBN

9781032196435

Category

nonfiction

Subjects

Engineering, Mathematics, Computer Science