Mathematical Optimization and Economic Analysis [electronic resource] / by Mikulás Luptácik.

By: Luptácik, Mikulás [author.]
Contributor(s): SpringerLink (Online service)
Material type: TextTextSeries: Springer Optimization and Its Applications: 36Publisher: New York, NY : Springer New York, 2010Description: XIV, 294 p. 53 illus. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9780387895529Subject(s): Mathematics | Operations research | Decision making | Mathematical optimization | Economic theory | Econometrics | Mathematics | Optimization | Econometrics | Economic Theory/Quantitative Economics/Mathematical Methods | Operation Research/Decision TheoryAdditional physical formats: Printed edition:: No titleDDC classification: 519.6 LOC classification: QA402.5-402.6Online resources: Click here to access online
Contents:
Single-Objective Optimization -- Scarcity and Efficiency -- Kuhn#x2013;Tucker Conditions -- Convex Programming -- Linear Programming -- Data Envelopment Analysis -- Geometric Programming -- Multiobjective Optimization -- Fundamentals of Multiobjective Optimization -- Multiobjective Linear Programming -- Multiobjective Geometric Programming.
In: Springer eBooksSummary: "Mathematical Optimization and Economic Analysis" is a self-contained introduction to various optimization techniques used in economic modeling and analysis such as geometric, linear, and convex programming and data envelopment analysis. Through a systematic approach, this book demonstrates the usefulness of these mathematical tools in quantitative and qualitative economic analysis. The book presents specific examples to demonstrate each technique’s advantages and applicability as well as numerous applications of these techniques to industrial economics, regulatory economics, trade policy, economic sustainability, production planning, and environmental policy. Key Features include: - A detailed presentation of both single-objective and multiobjective optimization; - An in-depth exposition of various applied optimization problems; - Implementation of optimization tools to improve the accuracy of various economic models; - Extensive resources suggested for further reading. This book is intended for graduate and postgraduate students studying quantitative economics, as well as economics researchers and applied mathematicians. Requirements include a basic knowledge of calculus and linear algebra, and a familiarity with economic modeling.
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Single-Objective Optimization -- Scarcity and Efficiency -- Kuhn#x2013;Tucker Conditions -- Convex Programming -- Linear Programming -- Data Envelopment Analysis -- Geometric Programming -- Multiobjective Optimization -- Fundamentals of Multiobjective Optimization -- Multiobjective Linear Programming -- Multiobjective Geometric Programming.

"Mathematical Optimization and Economic Analysis" is a self-contained introduction to various optimization techniques used in economic modeling and analysis such as geometric, linear, and convex programming and data envelopment analysis. Through a systematic approach, this book demonstrates the usefulness of these mathematical tools in quantitative and qualitative economic analysis. The book presents specific examples to demonstrate each technique’s advantages and applicability as well as numerous applications of these techniques to industrial economics, regulatory economics, trade policy, economic sustainability, production planning, and environmental policy. Key Features include: - A detailed presentation of both single-objective and multiobjective optimization; - An in-depth exposition of various applied optimization problems; - Implementation of optimization tools to improve the accuracy of various economic models; - Extensive resources suggested for further reading. This book is intended for graduate and postgraduate students studying quantitative economics, as well as economics researchers and applied mathematicians. Requirements include a basic knowledge of calculus and linear algebra, and a familiarity with economic modeling.

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