This is an open access book discusses readers to various methods of modeling plans and policies that address public sector issues and problems. Written for public policy and social sciences students at the upper undergraduate and graduate level, as well as public sector decision-makers, it demonstrates and compares the development and use of various deterministic and probabilistic optimization and simulation modeling methods for analyzing planning and management issues. These modeling tools offer a means of identifying and evaluating alternative plans and policies based on their physical, economic, environmental, and social impacts. Learning how to develop and use the mathematical modeling tools introduced in this book will give students useful skills when in positions of having to make informed public policy recommendations or decisions.
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Daniel P. Loucks is an emeritus professor on the faculty of the School of Civil and Environmental Engineering, Cornell University (USA). He continues to conduct research in the development and application of economics, ecology, and systems analysis methods to the solution of environmental and regional planning problems. He teaches a graduate course in systems planning and management at the Technical University of Vienna, Austria, and in the Cornell’s School of Public Policy. In the past, he has held positions in over 10 other universities and research institutes in Australia, Europe, and North America, and in various US and UN agencies, NATO, and the World Bank. He has consulted on development projects in Africa, Asia, the Americas, and Europe. He is a fellow of American Geophysical Union, a distinguished member of the American Society of Civil Engineering, and a member of the US National Academy of Engineering.
This is an open access book and introduces readers to various methods of modeling plans and policies that address public sector issues and problems. Written for public policy and social sciences students at the upper undergraduate and graduate level, as well as public sector decision-makers, it demonstrates and compares the development and use of various deterministic and probabilistic optimization and simulation modeling methods for analyzing planning and management issues. These modeling tools offer a means of identifying and evaluating alternative plans and policies based on their physical, economic, environmental, and social impacts. Learning how to develop and use the mathematical modeling tools introduced in this book will give students useful skills when in positions of having to make informed public policy recommendations or decisions.
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