Zero/large variables: look at cost and benefits of these variables in individual equations
High shadow prices: indicate resource scarcity (check endowments, technical coefficients, units)
In general, analyst needs a combination of mathematical and context knowledge
Conclusions
Large mathematical programming models are not necessarily black boxes
Drivers for individual results can be traced and understood
Generic misspecifications can and should always be corrected
Systematic post-optimality analysis is by far better and faster than intuition and guesswork
IV Modifying FASOM
Possible Modicfications
Easy Difficult Data updates
Data calculations
Scenario anaysis
Equation modifications
Documentation
Write log of changes in text file
Place comments on purpose of programming statements in FASOM code
Put „????“ where you make preliminary modifications
Frequent Errors
Units (Ex: 5 vs. 1 years)
Inconsistent conditions
Ignorance of GAMSCHK
Comments