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Springer Convex and Stochastic Optimization - Universitext Textbook

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Description

Convex and Stochastic Optimization by Springer is a comprehensive textbook designed for students, engineers and researchers seeking to master optimization theory and applications. This Universitext volume introduces convex duality in Banach spaces alongside integration theory, with practical focus on stochastic programming in both static and dynamic settings. The text systematically analyses the main algorithms for stochastic programmes whilst maintaining rigorous theoretical grounding. Readers will discover how to apply these mathematical tools across diverse fields including approximation theory, semidefinite programming, second-order cone programming and linear decision rules. Whether studying applied mathematics or working in optimization-intensive fields, this textbook bridges theoretical foundations with real-world problem-solving strategies.

Key Features

Convex and Stochastic Optimization covers convex duality theory applied to optimization problems in Banach spaces with comprehensive mathematical rigour.

The Springer textbook introduces and thoroughly analyses main algorithms for stochastic programmes in both static and dynamic programming contexts.

This Universitext edition demonstrates practical applications across approximation theory, semidefinite programming and second-order cone programming fields.

The textbook includes linear decision rules methodology, providing engineers and researchers with tools for handling uncertainty in optimisation problems.

Written for students, engineers and researchers, Convex and Stochastic Optimization integrates theoretical aspects with applied problem-solving techniques.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
29 April 2019
Listed Since
06 February 2019

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