Applied GAMS Modeling

 

A Short Course Offered By Bruce A. McCarl

 

Detailed Topical Outline

See the course setup and schedule used in the class

I. Basic course tools

• GAMS version
• GAMSIDE
• GAMSCHK

II. Building firm models with GAMS

See the basic GAMS notes used in the class

• Summation notation and GAMS
• Traditional modeling methods
• Basic GAMS modeling
  • Data
  • Calculations
  • Model definition
  • Solution
  • Report writing
  • Including conditionals

III. Firm modeling alternatives -- different ways of presenting alternatives

• Detailed resource availability
• Mixes of firm activities

IV. Adding Risk to a model

See the firm risk notes used in the class

• Risk modeling theory
  • Forms in which risk may enter a programming model
    • Non recourse or non adaptive decision making
    • Recourse or adaptive decision making
  • Nature of aversion to risk
  • Informal modeling approaches to uncertainty
• Risk modeling practice
  • Models without recourse
    • Objective function uncertainty the portfolio model
    • Right hand side uncertainty
    • Technical coefficient uncertainty
  • Models with recourse
    • Stochastic programming with recourse
    • Multiple stage discrete stochastic programming
    • Incorporating risk aversion
  • Specifying risk model parameters
    • Developing probability distributions
    • Developing risk aversion coefficients

V. Transporting Goods

VI. Conduct of impact analysis

• System design
• Comparative statics analysis
• Output Development

VII. Basic CGE Modeling

• Economic theory bassis
• MCP model specification

VIII. Making sure your model is right -- verification tools (GAMSCHK)

• Fixing model formulations before solving
• Post solution debugging of models
  • Fixing models which are unbounded or infeasible
  • Fixing unrealistic solutions

IX. Handling indivisible alternatives -- Integer variables

• Logical Conditions and integer variables
• Fixed costs and investment capacity
• Mixed and Pure Problems
• Solution concerns
  • Solution space and enumeration
  • Solution approaches, Branch and Bound, Rounding
  • Solution difficultues and Gaps
  • Problem reformulation for success