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Springer Optimization and Its Applications

Springer Optimization and Its Applications
155 Volumes | 2006 - 2020

Description

Aims and Scope

Optimization has continued to expand in all directions at an astonishing rate. New algorithmic and theoretical techniques are continually developing and the diffusion into other disciplines is proceeding at a rapid pace, with a spot light on machine learning, artificial intelligence, and quantum computing. Our knowledge of all aspects of the field has grown even more profound. At the same time, one of the most striking trends in optimization is the constantly increasing emphasis on the interdisciplinary nature of the field. Optimization has been a basic tool in areas not limited to applied mathematics, engineering, medicine, economics, computer science, operations research, and other sciences.

The series

Springer Optimization and Its Applications (SOIA)

aims to publish state-of-the-art expository works (monographs, contributed volumes, textbooks, handbooks) that focus on theory, methods, and applications of optimization. Topics covered include, but are not limited to, nonlinear optimization, combinatorial optimization, continuous optimization, stochastic optimization, Bayesian optimization, optimal control, discrete optimization, multi-objective optimization, and more. New to the series portfolio include Works at the intersection of optimization and machine learning, artificial intelligence, and quantum computing.

Volumes from this series are indexed by Web of Science, zbMATH, Mathematical Reviews, and SCOPUS.

All subseries of the series Springer Optimization and Its Applications

02-12-2015 | Book Series

Nonconvex Optimization and Its Applications

Nonconvex Optimization and Its Applications

All books of the series Springer Optimization and Its Applications

2020 | Book

Convex Optimization with Computational Errors

The book is devoted to the study of approximate solutions of optimization problems in the presence of computational errors. It contains a number of results on the convergence behavior of algorithms in a Hilbert space, which are known as important …

2020 | Book

Computational Mathematics and Variational Analysis

This volume presents a broad discussion of computational methods and theories on various classical and modern research problems from pure and applied mathematics. Readers conducting research in mathematics, engineering, physics, and economics will …

2020 | Book

Nonlinear Conjugate Gradient Methods for Unconstrained Optimization

Two approaches are known for solving large-scale unconstrained optimization problems—the limited-memory quasi-Newton method (truncated Newton method) and the conjugate gradient method. This is the first book to detail conjugate gradient methods …

2020 | Book

Integrated Optimization in Public Transport Planning

This book is one of the first to include an extensive discussion of integrated public transport planning. In times of growing urban populations and increasing environmental awareness, the importance of optimizing public transport systems is …

2020 | Book

Set-Valued Stochastic Integrals and Applications

This book is among the first concise presentations of the set-valued stochastic integration theory as well as its natural applications, as well as the first to contain complex approach theory of set-valued stochastic integrals. Taking particular …

2020 | Book

Aerospace System Analysis and Optimization in Uncertainty

Spotlighting the field of Multidisciplinary Design Optimization (MDO), this book illustrates and implements state-of-the-art methodologies within the complex process of aerospace system design under uncertainties. The book provides approaches to …

2019 | Book

Modeling and Optimization in Space Engineering

State of the Art and New Challenges

This book presents advanced case studies that address a range of important issues arising in space engineering. An overview of challenging operational scenarios is presented, with an in-depth exposition of related mathematical modeling …

2019 | Book

Approximation and Optimization

Algorithms, Complexity and Applications

This book focuses on the development of approximation-related algorithms and their relevant applications. Individual contributions are written by leading experts and reflect emerging directions and connections in data approximation and …

2019 | Book

Analysis and Operator Theory

Dedicated in Memory of Tosio Kato’s 100th Birthday

Dedicated to Tosio Kato’s 100th birthday, this book contains research and survey papers on a broad spectrum of methods, theories, and problems in mathematics and mathematical physics. Survey papers and in-depth technical papers emphasize linear …

2019 | Book

Nonlinear Combinatorial Optimization

Graduate students and researchers in applied mathematics, optimization, engineering, computer science, and management science will find this book a useful reference which provides an introduction to applications and fundamental theories in …

2019 | Book

SOC Functions and Their Applications

This book covers all of the concepts required to tackle second-order cone programs (SOCPs), in order to provide the reader a complete picture of SOC functions and their applications. SOCPs have attracted considerable attention, due to their wide …

2019 | Book

Turnpike Conditions in Infinite Dimensional Optimal Control

This book provides a comprehensive study of turnpike phenomenon arising in optimal control theory. The focus is on individual (non-generic) turnpike results which are both mathematically significant and have numerous applications in engineering …


2019 | Book

Large Scale Optimization in Supply Chains and Smart Manufacturing

Theory and Applications

In this book, theory of large scale optimization is introduced with case studies of real-world problems and applications of structured mathematical modeling. The large scale optimization methods are represented by various theories such as Benders’ …


2019 | Book

Computational Intelligence and Optimization Methods for Control Engineering

This volume presents some recent and principal developments related to computational intelligence and optimization methods in control. Theoretical aspects and practical applications of control engineering are covered by 14 self-contained …

2019 | Book

Differential and Integral Inequalities

Theories, methods and problems in approximation theory and analytic inequalities with a focus on differential and integral inequalities are analyzed in this book. Fundamental and recent developments are presented on the inequalities of Abel …

2019 | Book

Optimization in Large Scale Problems

Industry 4.0 and Society 5.0 Applications

This volume provides resourceful thinking and insightful management solutions to the many challenges that decision makers face in their predictions, preparations, and implementations of the key elements that our societies and industries need to …

2019 | Book

Mathematical Analysis and Applications

An international community of experts scientists comprise the research and survey contributions in this volume which covers a broad spectrum of areas in which analysis plays a central role. Contributions discuss theory and problems in real and …

2019 | Book

Advanced Optimization and Operations Research

This textbook provides students with fundamentals and advanced concepts in optimization and operations research. It gives an overview of the historical perspective of operations research and explains its principal characteristics, tools, and …

2018 | Book

Algorithms for Solving Common Fixed Point Problems

This book details approximate solutions to common fixed point problems and convex feasibility problems in the presence of perturbations. Convex feasibility problems search for a common point of a finite collection of subsets in a Hilbert space; …

2018 | Book

Practical Mathematical Optimization

Basic Optimization Theory and Gradient-Based Algorithms

This textbook presents a wide range of tools for a course in mathematical optimization for upper undergraduate and graduate students in mathematics, engineering, computer science, and other applied sciences. Basic optimization principles are …

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