Optimization Methods and Applications in Public Sector Policy and Planning

Erscheinungsjahr 2027
ISBN: 978-0-443-51006-9
Verlag: Elsevier Science

Buch, Englisch, 354 Seiten, Format (B × H): 152 mm x 229 mm

Optimization Methods and Applications in Public Sector Policy and Planning offers a comprehensive scientific reference integrating optimization theory, algorithms, and practical applications in public-sector domains. This book uniquely combines foundational mathematical concepts with advanced optimization methods, addressing complex challenges in environmental management, energy systems, urban planning, and sustainability. It equips readers with tools to formulate and solve optimization problems relevant to policy and planning.

The book is organized into twelve chapters covering classical programming, linear and integer programming, nonlinear and multi-objective programming, stochastic and multi-level optimization, network and transportation models, cooperative game theory, and the intersection of optimization with machine learning. It concludes with a synthesis chapter and includes appendices on matrix algebra, multivariable calculus, and GAMS programming basics to support computational implementation. Each chapter blends methodological exposition with applied examples, enhanced by visual aids such as diagrams and flowcharts to facilitate understanding.

Designed for upper-level undergraduate and graduate students, academic faculty, researchers, as well as consultants and professionals in planning, policy, and energy sectors, this reference provides the knowledge necessary to mathematically model, numerically solve, and interpret optimization problems. It supports disciplines including urban and regional planning, environmental sciences, civil and environmental engineering, geography, public policy, and natural resources management.

Autoren/Hrsg.

Guldmann, Jean-Michel

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein
• Geowissenschaften Geographie | Raumplanung Regional- & Raumplanung Stadtplanung, Kommunale Planung

Inhaltsverzeichnis

1. Introduction
2. Classical Programming
3. Linear Programming
4. Integer Programming
5. Nonlinear Programming
6. Multi-Objective Programming
7. Stochastic Programming
8. Multi-Level Optimization
9. Network and Transportation Models
10. Cooperative Games
11. Optimization and Machine Learning
12. Conclusions

Über Autor(innen)

Guldmann, Jean-Michel
Jean-Michel Guldmann is Professor Emeritus of City and Regional Planning at The Ohio State University (OSU), Columbus, Ohio. During a 35-year career at OSU, he has taught advanced graduate-level courses in static optimization, dynamic optimization, and decision analysis. He has advised and graduated 31 PhD students. He has published a book (Industrial Location and Air Quality Control: A Planning Approach – Wiley, 1980), two book chapters, and more than 100 peer-reviewed journal articles. He has also served as consultant to several organizations, including Argonne National Laboratory, California Energy Commission, The President’s Commission on Critical Infrastructure Protection, and the National Bureau of Standards. His current research focuses on modeling the urban heat island, building energy consumption, and the impact of the built environment on population health. His past research has focused on modeling air quality control, natural gas distribution, non-point source water pollution control, land-use-related seismic losses, and Census data suppression.