Transportation Model - Gams

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10 Binary Variables • Powerful Tool to model yes/no decisions • <strong>Model</strong>s with discrete variables (MIP) – Solved using Branch-and-Cut algorithms (lots or LPs) – Theoretically difficult problem class – Practical: • mixed bag • Art of <strong>Model</strong>ing • Example: Minimum Shipment – Ship at least 100 tons or don’t ship
11 Minimum Shipment • Continuous Variable x (shipment) • Binary Variable ship (indicator for minimum shipment): – ship=1 if x > 100 – ship=0 if x = 0 • Coupling Constraints: – x > 100 * ship – x < bigM * ship • How big do we have to make bigM?
Page 1 and 2: GAMS Transportation Model Michael B
Page 3 and 4: 3 A Transportation Model San Diego
Page 5 and 6: 5 GAMS Algebra
Page 7 and 8: 7 Hands-on! Transportation Model
Page 9: 9 Types of Variables • Continuous
Page 13 and 14: 13 Economy of Scales: Cost = Volume
Page 15 and 16: 15 Implement Min/Max and Nonlinear
Page 17 and 18: 17 Put Utility set help(*) option h
Page 19: 19 Capture an Instance with convert

Transportation Model - Gams

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