Max 1W + 1.25M s.t. 5W + 7M 3W + 1M 2W + 2M W, M 20 S 4,400 S 2,240 S 1,600 oz of whole tomatoes oz of tomato sauce oz of tomato paste The computer solution is shown below. Optimal Objective Value - 850.00000 Variable Value Reduced Cost 600.00000 0.00000 200.00000 0.00000 Slack/Surplus 0.00000 Constraint Dual Value 1. 0.12500 2. 240.00000 0.00000 3. 0.00000 0.18750 Objective Coefficient Allowable Increase Allowable Variable Decrease 1.00000 0.25000 0.10714 1.25000 0.15000 0.25000 Constraint RHS Allowable Allowable Value Increase Decrease 4400.00000 1200.00000 240.00000 2 2240.00000 Infinite 240.00000 3 1600.00000 60.00000 342.85714 (a) What is the optimal solution, and what are the optimal production quantities? |jars jars profit (b) Specify the objective function ranges. (Round your answers to five decimal places.) Western Foods Salsa to Mexico City Salsa to (c) What are the dual values for each constraint? Interpret each. constraint 1 O One additional ounce of whole tomatoes will improve profits by $0.125. One additional ounce of whole tomatoes will improve profits by $0.188. O One additional ounce of whole tomatoes will improve profits by $240.00. Additional ounces of whole tomatoes will not improve profits. constraint 2 O One additional ounce of tomato sauce will improve profits by $0.125. O One additional ounce of tomato sauce will improve profits by $0.188. O One additional ounce of tomato sauce will improve profits by $240.00. O Additional ounces of tomato sauce will not improve profits. constraint 3 O One additional ounce of tomato paste will improve profits by $0.125. O One additional ounce of tomato paste will improve profits by $0.188. O One additional ounce of tomato paste will improve profits by $240.00. O Additional ounces of tomato paste will not improve profits. (d) Identify each of the right-hand-side ranges. (Round your answers to two decimal places. If there is no upper or lower limit, enter NO LIMIT.) constraint 1 to constraint 2 to constraint 3 to
Max 1W + 1.25M s.t. 5W + 7M 3W + 1M 2W + 2M W, M 20 S 4,400 S 2,240 S 1,600 oz of whole tomatoes oz of tomato sauce oz of tomato paste The computer solution is shown below. Optimal Objective Value - 850.00000 Variable Value Reduced Cost 600.00000 0.00000 200.00000 0.00000 Slack/Surplus 0.00000 Constraint Dual Value 1. 0.12500 2. 240.00000 0.00000 3. 0.00000 0.18750 Objective Coefficient Allowable Increase Allowable Variable Decrease 1.00000 0.25000 0.10714 1.25000 0.15000 0.25000 Constraint RHS Allowable Allowable Value Increase Decrease 4400.00000 1200.00000 240.00000 2 2240.00000 Infinite 240.00000 3 1600.00000 60.00000 342.85714 (a) What is the optimal solution, and what are the optimal production quantities? |jars jars profit (b) Specify the objective function ranges. (Round your answers to five decimal places.) Western Foods Salsa to Mexico City Salsa to (c) What are the dual values for each constraint? Interpret each. constraint 1 O One additional ounce of whole tomatoes will improve profits by $0.125. One additional ounce of whole tomatoes will improve profits by $0.188. O One additional ounce of whole tomatoes will improve profits by $240.00. Additional ounces of whole tomatoes will not improve profits. constraint 2 O One additional ounce of tomato sauce will improve profits by $0.125. O One additional ounce of tomato sauce will improve profits by $0.188. O One additional ounce of tomato sauce will improve profits by $240.00. O Additional ounces of tomato sauce will not improve profits. constraint 3 O One additional ounce of tomato paste will improve profits by $0.125. O One additional ounce of tomato paste will improve profits by $0.188. O One additional ounce of tomato paste will improve profits by $240.00. O Additional ounces of tomato paste will not improve profits. (d) Identify each of the right-hand-side ranges. (Round your answers to two decimal places. If there is no upper or lower limit, enter NO LIMIT.) constraint 1 to constraint 2 to constraint 3 to
Practical Management Science
6th Edition
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter4: Linear Programming Models
Section: Chapter Questions
Problem 77P
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