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Variable Cells Model Variable Constraints. Constraint Number 1 E S D E S 3 D M S D Name Economy Models Standard Models Deluxe Models Total Profit: $ Name Fan Motors Cooling Coils Manufacturing Time Constraints Fan motors Cooling coils Optimal Solution Final Value 80.000 120.000 0.000 Final Value 200.000 320.000 2080.000 Reduced Cost CHINISHA MECRATICA 0.000 0.000 -24.000 a. Identify the range of optimality for each objective function coefficient. If there is no lower or upper limit, then enter the text "NA" as your answer. If required, round your answers to one decimal place. Objective Coefficient Range Variable lower limit upper limit E Right-Hand-Side-Range lower limit upper limit Shadow Price 31.000 32.000 0.000 Objective Coefficient 63.000 95.000 135.000 b. Suppose the profit for the economy model is increased by $6 per unit, the profit for the standard model is decreased by $2 per unit, and the profit for the deluxe model is increased by $4 per unit. What will the new optimal solution be? Constraint R.H. Side 200.000 320.000 2400.000 Allowable Increase 12.000 31.000 24.000 Allowable Increase 80.000 80.000 IE+30 Allowable Decrease 15.500 8.000 IE+30 Allowable Decrease 40.000 c. Identify the range of feasibility for the right-hand-side values. If there is no lower or upper limit, then enter the text "NA" as your answer. 120.000 320.000

Variable Cells Model Variable Constraints. Constraint Number 1 E S D E S 3 D M S D Name Economy Models Standard Models Deluxe Models Total Profit: $ Name Fan Motors Cooling Coils Manufacturing Time Constraints Fan motors Cooling coils Optimal Solution Final Value 80.000 120.000 0.000 Final Value 200.000 320.000 2080.000 Reduced Cost CHINISHA MECRATICA 0.000 0.000 -24.000 a. Identify the range of optimality for each objective function coefficient. If there is no lower or upper limit, then enter the text "NA" as your answer. If required, round your answers to one decimal place. Objective Coefficient Range Variable lower limit upper limit E Right-Hand-Side-Range lower limit upper limit Shadow Price 31.000 32.000 0.000 Objective Coefficient 63.000 95.000 135.000 b. Suppose the profit for the economy model is increased by $6 per unit, the profit for the standard model is decreased by $2 per unit, and the profit for the deluxe model is increased by $4 per unit. What will the new optimal solution be? Constraint R.H. Side 200.000 320.000 2400.000 Allowable Increase 12.000 31.000 24.000 Allowable Increase 80.000 80.000 IE+30 Allowable Decrease 15.500 8.000 IE+30 Allowable Decrease 40.000 c. Identify the range of feasibility for the right-hand-side values. If there is no lower or upper limit, then enter the text "NA" as your answer. 120.000 320.000

Practical Management Science
Practical Management Science
6th Edition
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter2: Introduction To Spreadsheet Modeling
Section: Chapter Questions
Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...
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Variable Cells Model Variable Constraints E S D Constraint Number 1 E 2 3 S D S D Name Economy Models Standard Models Deluxe Models Name Total Profit: $ Fan Motors Cooling Coils Manufacturing Time Optimal Solution Constraints Fan motors Cooling coils Final Value 80.000 120.000 0.000 Final Value 200.000 320.000 2080.000 a. Identify the range of optimality for each objective function coefficient. If there is no lower or upper limit, then enter the text "NA" as your answer. If required, round your answers to one decimal place. Objective Coefficient Range Variable lower limit upper limit E Reduced Cost 0.000 0.000 -24.000 Manufacturing time. AUTO Shadow Price 31.000 32.000 0.000 Right-Hand-Side-Range lower limit upper limit Objective Coefficient 63.000 95.000 135.000 b. Suppose the profit for the economy model is increased by $6 per unit, the profit for the standard model is decreased by $2 per unit, and the profit for the deluxe model is increased by $4 per unit. What will the new optimal solution be? Constraint R.H. Side 200.000 320.000 2400.000 Allowable Increase 12.000 31.000 24.000 Allowable Increase 80.000 80.000 IE+30 Allowable Decrease 15.500 8.000 IE+30 Allowable Decrease 40.000 120.000 320.000 c. Identify the range of feasibility for the right-hand-side values. If there is no lower or upper limit, then enter the text "NA" as your answer.
Transcribed Image Text:Variable Cells Model Variable Constraints E S D Constraint Number 1 E 2 3 S D S D Name Economy Models Standard Models Deluxe Models Name Total Profit: $ Fan Motors Cooling Coils Manufacturing Time Optimal Solution Constraints Fan motors Cooling coils Final Value 80.000 120.000 0.000 Final Value 200.000 320.000 2080.000 a. Identify the range of optimality for each objective function coefficient. If there is no lower or upper limit, then enter the text "NA" as your answer. If required, round your answers to one decimal place. Objective Coefficient Range Variable lower limit upper limit E Reduced Cost 0.000 0.000 -24.000 Manufacturing time. AUTO Shadow Price 31.000 32.000 0.000 Right-Hand-Side-Range lower limit upper limit Objective Coefficient 63.000 95.000 135.000 b. Suppose the profit for the economy model is increased by $6 per unit, the profit for the standard model is decreased by $2 per unit, and the profit for the deluxe model is increased by $4 per unit. What will the new optimal solution be? Constraint R.H. Side 200.000 320.000 2400.000 Allowable Increase 12.000 31.000 24.000 Allowable Increase 80.000 80.000 IE+30 Allowable Decrease 15.500 8.000 IE+30 Allowable Decrease 40.000 120.000 320.000 c. Identify the range of feasibility for the right-hand-side values. If there is no lower or upper limit, then enter the text "NA" as your answer.
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Step 1: Define - Linear programming

Linear programming is a mathematical method used to find the best possible outcome or solution from a given set of requirements or constraints which are represented in the form of linear relationships. It is most often used in mathematics and computer science, but also widely used in business and economic situations. Linear programming can help businesses make decisions such as managing resources, production schedules, and other operational details in order to increase profits or decrease costs while maintaining a certain level of quality and production flow.

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