Optimization

A hands-on text integrating mathematics, numerics and applications of optimization, with MATLAB code illustrating every concept.

A unique treatment of evolutionary games, indirect reciprocity, sequential decision making, and application to wireless and social networks.

Master the design and operation of perfusion cell cultures with this authoritative reference.

Introduces exciting new methods for assessing algorithms for problems ranging from clustering to linear programming to neural networks.

Address vector and matrix methods necessary in numerical methods and optimization of linear systems with this practical text.

Introduces exciting new methods for assessing algorithms for problems ranging from clustering to linear programming to neural networks.

A concise, accessible guide to the modern optimization methods that are transforming computer science, data science, and machine learning.

Discover interplay between matrices, linear programming, and game theory at an introductory level, requiring only high school algebra and curiosity.

Discover interplay between matrices, linear programming, and game theory at an introductory level, requiring only high school algebra and curiosity.

A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.

Modern mortality modelling for actuaries and actuarial students, with example R code, to unlock the potential of individual data.

This book adopts an individual differences approach to explain the psychology of chess by reviewing an extensive body of research.

Presents interplays between numerical approximation and statistical inference as a pathway to simple solutions to fundamental problems.

Provides a comprehensive approach to productivity and efficiency analysis using economic and econometric theory.

A complete introduction to recent advances in preprocessing analysis, or kernelization, with extensive examples using a single data set.

Integrates theory, algorithms, modeling, and computer implementation while solved examples show realistic engineering optimization problems.

A concise, accessible guide to the modern optimization methods that are transforming computer science, data science, and machine learning.

Provides a comprehensive approach to productivity and efficiency analysis using economic and econometric theory.

This analytical history of World War I offers a rigorous yet accessible training in game theory, and a survey of modern political science research.

This analytical history of World War I offers a rigorous yet accessible training in game theory, and a survey of modern political science research.

Integrates theory, algorithms, modeling, and computer implementation while solved examples show realistic engineering optimization problems.

Full treatment, from model formulation to computational implementation, of optimization techniques that solve central problems in finance.

Presents interplays between numerical approximation and statistical inference as a pathway to simple solutions to fundamental problems.

A complete introduction to recent advances in preprocessing analysis, or kernelization, with extensive examples using a single data set.

A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.

Learn state-of-the-art methods for making logically sound decisions when faced with multiple conflicting objectives and uncertainty.

Learn state-of-the-art methods for making logically sound decisions when faced with multiple conflicting objectives and uncertainty.

An international team of experts covers the pros and cons of different auction formats and lessons learned in the field.

This is a single comprehensive reference source covering the key material on this subject, and describing both theoretical and practical aspects.

This beginning graduate textbook teaches data science and machine learning methods for modeling, prediction, and control of complex systems.

Proposes novel methods to incorporate ignorance and uncertainty into economic modeling without complex mathematics.

This hands-on tutorial text for non-experts demonstrates biological applications of a versatile modeling and optimization technique.

This beginning graduate textbook teaches data science and machine learning methods for modeling, prediction, and control of complex systems.

Proposes novel methods to incorporate ignorance and uncertainty into economic modeling without complex mathematics.

This hands-on tutorial text for non-experts demonstrates biological applications of a versatile modeling and optimization technique.

Provides in-depth coverage of the modelling, behaviour, control, and stability analysis of converter-interfaced energy storage systems.

An introduction to Mathematica® and the Wolfram Language™ in the familiar context of the standard university mathematics curriculum.

The first step-by-step introduction to the methodology of agent-based models in economics, their mathematical and statistical analysis, and real-world applications.

The first step-by-step introduction to the methodology of agent-based models in economics, their mathematical and statistical analysis, and real-world applications.

Are we safer from terrorism today and is our homeland security money well spent?

Are we safer from terrorism today and is our homeland security money well spent?

An introduction to the modern theory of economic design, it develops an up-to-date treatment of the adjudication of conflicting claims.

An introduction to the modern theory of economic design, it develops an up-to-date treatment of the adjudication of conflicting claims.

With a simple approach that includes real-time applications and algorithms, this book covers the theory of model predictive control (MPC).

With a simple approach that includes real-time applications and algorithms, this book covers the theory of model predictive control (MPC).

This text introduces students to an experimental approach to mathematics, using Maple to systematically investigate and develop mathematical theory.

This text introduces students to an experimental approach to mathematics, using Maple to systematically investigate and develop mathematical theory.

This book provides an introduction to Suzanne Scotchmer''s contributions to the economics of innovation, intellectual property incentives, and equilibrium theory.

This book provides an introduction to Suzanne Scotchmer''s contributions to the economics of innovation, intellectual property incentives, and equilibrium theory.

A self-contained introduction to the use of stochastic geometry techniques for studying the behaviour of heterogeneous cellular networks.