#### Transcript Anatomy of a GAMS Model

Anatomy of a GAMS Model Miles K. Light University of Colorado Preliminaries: GAMS Program Anatomy: All GAMS programs are TEXT. Save GAMS programs as: program.gms (input) program.gms: Input file Output from GAMS comes as a listing file: program.lst (output) program.lst: Output file Preliminaries: The INPUT File: GAMS programs use the following Structure: 1. Make the Definitions 2. Define the Data 3. Write the Model Algebra 4. Solve the model program.gms: Define Variables: X = Rice, Y = Oil PX = Price1,PY = Price2 Insert the Data: PX = 20; PY = 35; Write the Algebra: X = .. Y = .. Solve Preliminaries: Model Setup: Definitions program.gms: $title: Breakfast Optimization Set Keyword: $title set Description: Main model description Defines the data domain scalar A preset value parameter A preset vector variable equation Endogenous value determined in optimization Equation definition I /eggs, toast/; Scalar a Eggs to toast ratio / 2 /; Parameter b(I) Supply /eggs 3, toast 2/; Variable phi(I) Optimal use of inputs; Equation obj Objective function; Preliminaries: program.gms (cont.): Model execution: … top half of model … Keyword: Model .iterlim Solve .l Description: Tell GAMS which equations define the model Maximum iterations are allowed Tell GAMS to solve the model Level value .up Upper limit for variable .lo Lower limit .m Shadow Value of Constraint model static phi(i).l phi(i).lo phi(i).up /obj/; = 2.0; = 0.0; = 100; static.iterlim = 2000; solve static using lp; parameter marginals(i) ; marginals(i) = phi.m(i); Practice: $title: Breakfast Optimization: Make best use of Breakfast inputs – to maximize breakfast happiness Practice: Set Scalar Parameter Variable Equations obj.. I /eggs, toast/; a c Preferred Eggs to toast ratio / 2 /, Maximum items you can eat at one time / 5 /; b(I) r(i) Supply (in refrigerator) /eggs 3, toast 6/, Marginal Benefit from eating / eggs 2, toast 1 /; phi(i) z Optimal use of food inputs Value of objective function (happiness); obj const(i) totfood Objective function Constraint Total food intake; z =E= sum(i, r(i) * phi(i)); Preliminaries: Exercise #1: The Soft Suds Brewing and Bottling Company: Soft Suds is planning for the 2010 New Year's party. There was to be a big party at the _____ house in Yerevan, and Gus Guzzler, the manager, knew that Soft Suds would be called upon to supply the refreshments. However the raw materials were not ordered and could not be obtained before the party. So there are fixed-supplies for inputs. Gus took an inventory of the available supplies and found the following: Malt Hops Yeast 75 units 60 units 50 units Soft Suds produces two types of pick-me-ups: light beer and dark beer, with the following specifications: Malt Hops Light Beer 2 3 2 2.00 Problem: Maximize profits given input requirements, supplies, and prices. Dark Beer 3 1 5/3 1.00 Use Linear Programming Yeast Price: Preliminaries: Exercise #2: Problem: Copy the ‘ TRNsport’ model from the GAMS library. -- Impose a “toll” of 20% on the Seattle—Chicago trade route. -- Compute the new shipping quantitites Use Linear Programming