Optimization and Its Applications in Control and Data Sciences
In Honor of Boris T. Polyak’s 80th Birthday

Editors: Boris Goldengorin



Presents open problems in optimization, game theory and control theory

Concentrates on recent research in modern optimization

Focuses on techniques for solving complex optimization problems

This book focuses on recent research in modern optimization and its implications in control and data analysis. This book is a collection of papers from the conference “Optimization and Its Applications in Control and Data Science” dedicated to Professor Boris T. Polyak, which was held in Moscow, Russia on May 13-15, 2015.

This book reflects developments in theory and applications rooted by Professor Polyak’s fundamental contributions to constrained and unconstrained optimization, differentiable and nonsmooth functions, control theory and approximation. Each paper focuses on techniques for solving complex optimization problems in different application areas and recent developments in optimization theory and methods. Open problems in optimization, game theory and control theory are included in this collection which will interest engineers and researchers working with efficient algorithms and software for solving optimization problems in market and data analysis. Theoreticians in operations research, applied mathematics, algorithm design, artificial intelligence, machine learning, and software engineering will find this book useful and graduate students will find the state-of-the-art research valuable.

Table of contents

Front Matter

A New Adaptive Conjugate Gradient Algorithm for Large-Scale Unconstrained Optimization

On Methods of Terminal Control with Boundary-Value Problems: Lagrange Approach

Optimization of Portfolio Compositions for Small and Medium Price-Taking Traders

Indirect Maximum Likelihood Estimation

Lagrangian Duality in Complex Pose Graph Optimization

State-Feedback Control of Positive Switching Systems with Markovian Jumps

Matrix-Free Convex Optimization Modeling

Invariance Conditions for Nonlinear Dynamical Systems

Modeling of Stationary Periodic Time Series by ARMA Representations

A New Two-Step Proximal Algorithm of Solving the Problem of Equilibrium Programming

Nonparametric Ellipsoidal Approximation of Compact Sets of Random Points

Extremal Results for Algebraic Linear Interval Systems

Applying the Gradient Projection Method to a Model of Proportional Membership for Fuzzy Cluster Analysis

Algorithmic Principle of Least Revenue for Finding Market Equilibria

The Legendre Transformation in Modern Optimization