General Algebraic Modeling System - Gams

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•Easy to adapt existing models •Large-scale potential •Customizable solution to problem •Available within GAMS right now •Models hard to solve •Local solutions found •Scarcity of MPEC models Benefits/Drawbacks 32
•Find all or multiple equilibria –Use nlp=baron parametrically •Structural identification –Inverse problems •Optimal tariff calculations –Large-scale datasets Frontiers •Stackelberg (leader/follower) games 33
Page 1 and 2: General Algebraic Modeling System M
Page 3 and 4: Computation Past • Algorithm limi
Page 5 and 6: Basic Principles • Separation of
Page 7 and 8: Supported Solvers 7
Page 9 and 10: Supported Platforms 9
Page 11 and 12: GAMS Implementation • Using the G
Page 13 and 14: Model m1.gms 13
Page 15 and 16: * min and max shipmenst option limc
Page 17 and 18: * min/max and nl obj Min/Max and NL
Page 19 and 20: * flexible demand parameter pbar(j)
Page 21 and 22: Summary Result 21
Page 23 and 24: CONOPT3 Performance 23
Page 25 and 26: Nonlinear equations: ai = à ∞,bi
Page 27 and 28: Definition of MPEC minimize f(x, y)
Page 29 and 30: MPEC Approaches •Implicit: min f(
Page 31: •Create the GAMS model as an MPEC
Page 35 and 36: Excel Data 35
Page 37 and 38: Excel Data 37
Page 39 and 40: E-mail Submission 39
Page 41 and 42: Job Info Via e-mail 41
Page 43 and 44: GAMS World Home Page 43
Page 45 and 46: MINLP World Home Page 45
Page 47 and 48: Performance Home Page 47
Page 49 and 50: Global World Home Page 49
Page 51 and 52: BARON BARON is a computational syst
Page 53 and 54: OQMS OQMS. This system combines exi
Page 55: Contacting GAMS Development 55

General Algebraic Modeling System - Gams

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