Management science and decision technology / Jeffrey D. Camm and James R. Evans.
By: Camm, Jeffrey D [author]
.
Contributor(s): Evans, James R. (James Robert) [author].
Material type: 
BookPublisher: Cincinnati, Ohio : South-Western College Publishing, Thomson Learning, c2000Description: xiii, 390 pages : illustrations ; 26 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 0324007159.Subject(s): Management science | Industrial management -- Mathematical models | Industrial management -- Decision making | Decision making -- Mathematical models | Risk managementDDC classification: 658.403 | Item type | Current library | Call number | Copy number | Status | Barcode | |
|---|---|---|---|---|---|---|
| General lending | MTU Bishopstown Library Lending | 658.403 (Browse shelf(Opens below)) | 1 | Available | 00094903 |
Enhanced descriptions from Syndetics:
The focus of this book is on using data and spreadsheet models effectively for the analysis of business problems and decision making. Included are discussions of building good spreadsheet models; data collection, visualization, and statistical analysis; forecasting; optimization using Excel Solver; decision and risk analysis; and simulation using Crystal Ball add-in for Excel and Arena BE. The principal focus is on gaining insight and intuition for better decisions, with applications in operations planning, finance, and marketing.
Bibliography: (page 378) and index.
Part 1: Models, data management and analysis -- Modeling for decisions and insight -- Data management and analysis -- Forecasting -- Part 2: Optimization -- Linear and multiobjective optimization models -- Integer and nonlinear optimization models -- Part 3: Decision, risk and simulation -- Decision and risk analysis -- Monte Carlo simulation -- Systems modeling and simulation.
Table of contents provided by Syndetics
- Part 1 Models and Decisions
- 1 Modeling for Decisions and Insight
- Part 2 Data and Information Management
- 2 Data Management and Analysis
- 3 Forecasting
- Part 3 Optimization
- 4 Linear and Multiobjective Optimization Models
- 5 Integer and Nonlinear Optimization Models
- Part 4 Decisions, Risk, and Uncertainty
- 6 Decision and Risk Analysis
- 7 Monte-Carlo Simulation
- 8 Modeling and Analyzing Dynamic Systems