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Full Description
This book offers a comprehensive exploration of mathematical optimization and its critical role in economic analysis. As the scarcity of resources, environmental degradation, and the effects of industrial robots and artificial intelligence (AI) become ever-pressing issues, this second edition expands on the foundational theories of static optimization to include dynamic optimization and new applications in areas such as automation and sustainability.
The authors examine key concepts such as the optimal allocation of resources, the interplay between economic growth and environmental impacts, and the integration of automation in production systems. As renowned experts in the field, the authors provide a robust framework for understanding single and multi-objective optimization models as well as dynamic optimization in continuous and discrete time, emphasizing their use in qualitative analysis. This second edition offers deep insights into investment strategies and resource management over time, making it an indispensable resource for those seeking to navigate the complexities of modern economic landscapes.
Ideal for graduate students, university educators, and researchers in economics, business, and operations research, this book bridges the gap between theoretical rigor and practical application. It is also a valuable resource for practitioners and students of applied mathematics interested in economic applications.
Contents
Part 1. Single-Objective Optimization.- Scarcity and Efficiency.- Kuhn-Tucker Conditions.- Convex Programming.- Linear Programming.- Data Envelopment Analysis.- Geometric Programming.- Part 2. Multiobjective Optimization.- Fundamentals of Multiobjective Optimization.- Multiobjective Linear Programming.- Multiobjective Geometric Programming.- Part 3. Dynamic Optimization.- Dynamic Optimization.- Applications of Dynamic Optimization.
