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Decision Support Systems: Chapter 4 - Modeling and Analysis present about Modeling for DSS; Static and Dynamic models; Treating certainty, uncertainty; Influence diagrams; Modeling with spreadsheets; Decision Tables and Decision trees; MSS mathematical models; Search approaches. | Chapter 4 Modeling and Analysis Decision Support Systems 4- Outline 1. Modeling for DSS 2. Static and Dynamic models 3. Treating certainty, uncertainty 4. Influence diagrams 5. Modeling with spreadsheets 6.Decision Tables and Decision trees 7.MSS mathematical models 8. Search approaches 9.Simulation 10. Model base management system 4- 1.Modeling for DSS Modeling is key element in DSS Many classes of models Simulation is an example Specialized techniques for each model Allows for rapid examination of alternative solutions Multiple models often included in a DSS Trend toward model transparency Multidimensional modeling exhibits as spreadsheet 4- Some major modeling issues Identification of the problem and environment analysis Variable identification Decision variables Uncontrollable variables Result variables, etc. Note: using influence diagrams and cognitive maps to identify variables and relationships. Forecasting: DSS is designed to determine what will be. Time series . | Chapter 4 Modeling and Analysis Decision Support Systems 4- Outline 1. Modeling for DSS 2. Static and Dynamic models 3. Treating certainty, uncertainty 4. Influence diagrams 5. Modeling with spreadsheets 6.Decision Tables and Decision trees 7.MSS mathematical models 8. Search approaches 9.Simulation 10. Model base management system 4- 1.Modeling for DSS Modeling is key element in DSS Many classes of models Simulation is an example Specialized techniques for each model Allows for rapid examination of alternative solutions Multiple models often included in a DSS Trend toward model transparency Multidimensional modeling exhibits as spreadsheet 4- Some major modeling issues Identification of the problem and environment analysis Variable identification Decision variables Uncontrollable variables Result variables, etc. Note: using influence diagrams and cognitive maps to identify variables and relationships. Forecasting: DSS is designed to determine what will be. Time series forecasting There exist several forecasting packages. Multiple models 4- DSS Models Algorithm-based models Statistic-based models Linear programming models Graphical models Quantitative models Qualitative models Simulation models 4- 4- 2. Static and Dynamic Models Static Models Single snapshot of situation Single interval Time can be rolled forward, a snapshot at a time Usually repeatable Steady state Optimal operating parameters Continuous Unvarying Primary tool for process design 4- Dynamic Models Represent changing situations Time dependent Varying conditions Generate and use trends and patterns over time Occurrence may not repeat 4- 3.Treating certainty, uncertainty and risk Decision making under certainty Assume complete knowledge All potential outcomes known Easy to develop Resolution determined easily Can be very complex 4- Decision-Making under uncertainty Uncertainty Several outcomes for each decision Probability of occurrence of each outcome unknown .
