Practical Management Science
Practical Management Science
6th Edition
ISBN: 9781337406659
Author: WINSTON, Wayne L.
Publisher: Cengage,
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Problem #3 - PK Inc. manufactures interior and exterior paints from two raw materials, M1 and M2. The following table provides the basic data of the problem: Tons of raw materials per ton of Interior paint 4 Maximum daily Exterior paint availability (tons) Raw material M, Raw material M2 24 1 2 6 Profit per ton $5,000 $4,000 A market survey indicates that the daily demand for interior paint cannot exceed that for exterior paint by more than 1 ton. Also, the maximum daily demand for interior paint is 2 tons. PK Inc. wants to determine the optimum (best) product mix of interior and exterior paints that maximizes the total daily profit. -; Formulate and explain the mathematical model for this LP problem, including: a. The Objective Function All the constr aints that the solution must satisfy, including nonnegativity. b. ie Solve the LP problem using the graphical method.
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Transcribed Image Text:Problem #3 - PK Inc. manufactures interior and exterior paints from two raw materials, M1 and M2. The following table provides the basic data of the problem: Tons of raw materials per ton of Interior paint 4 Maximum daily Exterior paint availability (tons) Raw material M, Raw material M2 24 1 2 6 Profit per ton $5,000 $4,000 A market survey indicates that the daily demand for interior paint cannot exceed that for exterior paint by more than 1 ton. Also, the maximum daily demand for interior paint is 2 tons. PK Inc. wants to determine the optimum (best) product mix of interior and exterior paints that maximizes the total daily profit. -; Formulate and explain the mathematical model for this LP problem, including: a. The Objective Function All the constr aints that the solution must satisfy, including nonnegativity. b. ie Solve the LP problem using the graphical method.
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Step 1: Determine given data
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Step 2: Determine objective and constraints
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Step 3: Find coordinates
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Step 4: Plot graph
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Step 5: Find optimal solution
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