Concurrent users
Unlimited
Authorized users
Open access
Document Delivery Supplied
Open access
Title
Public systems modeling : methods for identifying and evaluating alternative plans and policies / Daniel P. Loucks.
ISBN
9783030939861 (electronic bk.)
3030939863 (electronic bk.)
9783030939854 (print)
3030939855
Published
Cham, Switzerland : Springer, 2022.
Language
English
Description
1 online resource (x, 328 pages) : illustrations (some color).
Item Number
10.1007/978-3-030-93986-1 doi
Call Number
JF1351
Dewey Decimal Classification
351
Summary
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.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Open access.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed June 21, 2022).
Series
International series in operations research & management science ; 318. 2214-7934
Available in Other Form
Print version: 9783030939854
1. Analyzing Public Policy Decisions
2. Public Sector Systems
3. Creating Models
4. Modeling Examples and Solutions
5. Models for Managing Money
6. Solving Models Using Excel
7. Discrete Optimization Modeling
8. Linear Optimization Modeling
9. Some Linearization Methods
10. Solving Models Using Calculus
11. Lagrangian Models
12. Dealing with Uncertainty
13. Modeling Stochastic Processes
14. Chance Constrained and Monte Carlo Modeling
15. Simulation Modeling
16. Multi Criteria Analyses
17. Fuzzy Optimization
18. Conclusions.
