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ch19 Student: _ 1. Linear programming techniques will always produce an optimal solution to an LP problem. True False 2. LP problems must have a single goal or objective specified. True False 3. Constraints limit the alternatives available to a decisionmaker, removing constraints adds viable alternative solutions. True False 4. An example of a decision variable in an LP problem is profit maximization. True False 5. The feasible solution space only contains points that satisfy all constraints. True False 6. The equation 5x + 7y = 10 is linear. True False 7. The equation 3xy = 9 is linear. True False 8. Graphical linear programming can handle problems that involve any number of decision variables. True False 9. An objective function represents a family of parallel lines. True False 10. The term "isoprofit" line means that all points on the line will yield the same profit. True False 11. The feasible solution space is the set of all feasible combinations of decision variables as defined by only binding constraints. True False 12. The value of an objective function decreases as it is moved away from the origin. True False 13. A linear programming problem can have multiple optimal solutions. True False 14. A maximization problem may be characterized by all greater than or equal to constraints. True False 15. If a single optimal solution exists to a graphical LP problem, it will exist at a corner point. True False 16. The simplex method is a generalpurpose LP algorithm that can be used for solving only problems with more than six variables. True False 17. A change in the value of an objective function coefficient does not change the optimal solution. True False 18. The term "range of optimality" refers to a constraint's righthand side quantity. True False 19. A shadow price indicates how much a oneunit decrease/increase in the righthand side value of a constraint will decrease/increase the optimal value of the objective function. True False 20. The term "range of feasibility" refers to coefficients of the objective function. True False 21. Nonzero slack or surplus is associated with a binding constraint. True False 22. In the range of feasibility, the value of the shadow price remains constant. True False 23. Every change in the value of an objective function coefficient will lead to changes in the optimal solution. True False 24. Nonbinding constraints are not associated with the feasible solution space; i.e., they are redundant and can be eliminated from the matrix. True False 25. When a change in the value of an objective function coefficient remains within the range of optimality, the optimal solution would also remain the same. True False 26. Using the enumeration approach, optimality is obtained by evaluating every coordinate. True False 27. The linear optimization technique for allocating constrained resources among different products is: A. linear regression analysis B. linear disaggregation C. linear decomposition D. linear programming E. linear tracking analysis 28. Which of the following is not a component of the structure of a linear programming model? A. Constraints B. Decision variables C. Parameters D. A goal or objective E. Environmental uncertainty 29. Coordinates of all corner points are substituted into the objective function when we use the approach called: A. Least Squares B. Regression C. Enumeration D. Graphical Linear Programming E. Constraint Assignment 30. Which of the following could not be a linear programming problem constraint? A. 1A + 2B 3 B. 1A + 2B 3 C. 1A + 2B = 3 D. 1A + 2B + 3C + 4D 5 E. 1 A + 2B 31. For the products A, B, C and D, which of the following could be a linear programming objective function? A. Z = 1A + 2B + 3C + 4D B. Z = 1A + 2BC + 3D C. Z = 1A + 2AB + 3ABC + 4ABCD D. Z = 1A + 2B/C + 3D E. all of the above 32. The logical approach, from beginning to end, for assembling a linear programming model begins with: A. identifying the decision variables B. identifying the objective function C. specifying the objective function parameters D. identifying the constraints E. specifying the constraint parameters 33. The region which satisfies all of the constraints in graphical linear programming is called the: A. optimum solution space B. region of optimality C. lower left hand quadrant D. region of nonnegativity E. feasible solution space 34. In graphical linear programming the objective function is: A. linear B. a family of parallel lines C. a family of isoprofit lines D. all of the above E. none of the above 35. Which objective function has the same slope as this one: $4x + $2y = $20? A. $4x + $2y = $10 B. $2x + $4y = $20 C. $2x $4y = $20 D. $4x $2y = $20 E. $8x + $8y = $20 36. For the constraints given below, which point is in the feasible solution space of this maximization problem? A. x = 1, y = 5 B. x = 1, y = 1 C. x = 4, y = 4 D. x = 2, y = 1 E. x = 2, y = 8 37. Which of the choices below constitutes a simultaneous solution to these equations? A. x = 2, y = .5 B. x = 4, y = .5 C. x = 2, y = 1 D. x = y E. y = 2x 38. Which of the choices below constitutes a simultaneous solution to these equations? A. x = 1, y = 1.5 B. x = .5, y = 2 C. x = 0, y = 3 D. x = 2, y = 0 E. x = 0, y = 0 39. What combination of x and y will yield the optimum for this problem? A. x = 2, y = 0 B. x = 0, y = 0 C. x = 0, y = 3 D. x = 1, y = 5 E. none of the above 40. In graphical linear programming, when the objective function is parallel to one of the binding constraints, then: A. the solution is suboptimal B. multiple optimal solutions exist C. a single corner point solution exists D. no feasible solution exists E. the constraint must be changed or eliminated 41. For the constraints given below, which point is in the feasible solution space of this minimization problem? A. x = 0.5, y = 5.0 B. x = 0.0, y = 4.0 C. x = 2.0, y = 5.0 D. x = 1.0, y = 2.0 E. x = 2.0, y = 1.0 42. What combination of x and y will provide a minimum for this problem? A. x = 0, y = 0 B. x = 0, y = 3 C. x = 0, y = 5 D. x = 1, y = 2.5 E. x = 6, y = 0 43. The theoretical limit on the number of decision variables that can be handled by the simplex method in a single problem is: A. 1 B. 2 C. 3 D. 4 E. unlimited 44. The theoretical limit on the number of constraints that can be handled by the simplex method in a single problem is: A. 1 B. 2 C. 3 D. 4 E. unlimited 45. A shadow price reflects which of the following in a maximization problem? A. marginal cost of adding additional resources B. marginal gain in the objective that would be realized by adding one unit of a resource C. net gain in the objective that would be realized by adding one unit of a resource D. marginal gain in the objective that would be realized by subtracting one unit of a resource E. expected value of perfect information 46. In linear programming, a nonzero reduced cost is associated with a: A. decision variable in the solution B. decision variable not in the solution C. constraint for which there is slack D. constraint for which there is surplus E. constraint for which there is no slack or surplus 47. A constraint that does not form a unique boundary of the feasible solution space is a: A. redundant constraint B. binding constraint C. nonbinding constraint D. feasible solution constraint E. constraint that equals zero 48. In linear programming, sensitivity analysis is associated with: (I) objective function coefficient (II) righthand side values of constraints (III) constraint coefficient A. I and II B. II and III C. I, II and III D. I and III E. none of the above 49. Consider the following linear programming problem: Solve the values of x and y that will maximize revenue. What revenue will result? 50. A manager must decide on the mix of products to produce for the coming week. Product A requires three minutes per unit for molding, two minutes per unit for painting, and one minute per unit for packing. Product B requires two minutes per unit for molding, four minutes per unit for painting, and three minutes per unit for packing. There will be 600 minutes available for molding, 600 minutes for painting, and 420 minutes for packing. Both products have profits of $1.50 per unit (A) What combination of A and B will maximize profit? (B) What is the maximum possible profit? (C) How much of each resource will be unused for your solution? 51. Given this problem: (A) Solve for the quantities of x and y which will maximize Z (B) What is the maximum value of Z? 52. Solve the following linear programming problem: 53. Consider the linear programming problem below: Determine the optimum amounts of x and y in terms of cost minimization. What is the minimum cost? 72. What is the assembly time constraint (in hours)? A. 1 A + 1 B 800 B. 0.25 A + 0.5 B 800 C. 0.5 A + 0.25 B 800 D. 1 A + 0.5 B 800 E. 0.25 A + 1 B 800 This summarizes the usage possibilities for this resource AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1902 Formulate a linear programming model from a description of a problem Stevenson Chapter 19 #72 Topic Area: Linear Programming Models 73. Which of the following is not a feasible production/sales combination? A. 0 A & 0 B B. 0 A & 1,000 B C. 1,800 A & 700 B D. 2,500 A & 0 B E. 100 A & 1,600 B This is not a feasible combination AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #73 Topic Area: Graphical Linear Programming 74. What are optimal weekly profits? A. $10,000 B. $4,600 C. $2,500 D. $5,200 E. $6,400 Use the graphical linear programming approach AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #74 Topic Area: Graphical Linear Programming 75. For the production combination of 1,400 A100's and 900 B200's which resource is "slack" (not fully used)? A. circuit boards (only) B. assembly time (only) C. both circuit boards and assembly time D. neither circuit boards nor assembly time E. cannot be determined exactly Enter appropriate values for the decision variables and interpret the results AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #75 Topic Area: Graphical Linear Programming A local bagel shop produces two products: bagels (B) and croissants (C). Each bagel requires 6 ounces of flour, 1 gram of yeast, and 2 tablespoons of sugar. A croissant requires 3 ounces of flour, 1 gram of yeast, and 4 tablespoons of sugar. The company has 6,600 ounces of flour, 1,400 grams of yeast, and 4,800 tablespoons of sugar available for today's production run. Bagel profits are 20 cents each, and croissant profits are 30 cents each Stevenson Chapter 19 76. What is the objective function? A. $0.30 B + $0.20 C = Z B. $0.60 B + $0.30 C = Z C. $0.20 B + $0.30 C = Z D. $0.20 B + $0.40 C = Z E. $0.10 B + $0.10 C = Z This is the objective function AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1902 Formulate a linear programming model from a description of a problem Stevenson Chapter 19 #76 Topic Area: Linear Programming Models 77. What is the sugar constraint (in tablespoons)? A. 6 B + 3 C 4,800 B. 1 B + 1 C 4,800 C. 2 B + 4 C 4,800 D. 4 B + 2 C 4,800 E. 2 B + 3 C 4,800 This summarizes usage possibilities with respect to this resource AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1902 Formulate a linear programming model from a description of a problem Stevenson Chapter 19 #77 Topic Area: Linear Programming Models 78. Which of the following is not a feasible production combination? A. 0 B & 0 C B. 0 B & 1,100 C C. 800 B & 600 C D. 1,100 B & 0 C E. 0 B & 1,400 C This uses 5,600 when only 4,800 are available AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #78 Topic Area: Graphical Linear Programming 79. What are optimal profits for today's production run? A. $580 B. $340 C. $220 D. $380 E. $420 Use the graphical linear programming method AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #79 Topic Area: Graphical Linear Programming 80. For the production combination of 600 bagels and 800 croissants, which resource is "slack" (not fully used)? A. flour (only) B. sugar (only) C. flour and yeast D. flour and sugar E. yeast and sugar These resources are not fully utilized AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #80 Topic Area: Graphical Linear Programming The owner of Crackers, Inc. produces two kinds of crackers: Deluxe (D) and Classic (C). She has a limited amount of the three ingredients used to produce these crackers available for her next production run: 4,800 ounces of sugar; 9,600 ounces of flour, and 2,000 ounces of salt. A box of Deluxe crackers requires 2 ounces of sugar, 6 ounces of flour, and 1 ounce of salt to produce; while a box of Classic crackers requires 3 ounces of sugar, 8 ounces of flour, and 2 ounces of salt. Profits for a box of Deluxe crackers are $0.40; and for a box of Classic crackers, $0.50 Stevenson Chapter 19 81. What is the objective function? A. $0.50 D + $0.40 C = Z B. $0.20 D + $0.30 C = Z C. $0.40 D + $0.50 C = Z D. $0.10 D + $0.20 C = Z E. $0.60 D + $0.80 C = Z This is the objective function AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1902 Formulate a linear programming model from a description of a problem Stevenson Chapter 19 #81 Topic Area: Linear Programming Models 82. What is the constraint for sugar? A. 2 D + 3 C 4,800 B. 6 D + 8 C 4,800 C. 1 D + 2 C 4,800 D. 3 D + 2 C 4,800 E. 4 D + 5 C 4,800 This summarizes usage possibilities for this resource AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1902 Formulate a linear programming model from a description of a problem Stevenson Chapter 19 #82 Topic Area: Linear Programming Models 83. Which of the following is not a feasible production combination? A. 0 D & 0 C B. 0 D & 1,000 C C. 800 D & 600 C D. 1,600 D & 0 C E. 0 D & 1,200 C This is not a feasible combination AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #83 Topic Area: Graphical Linear Programming 84. What are profits for the optimal production combination? A. $800 B. $500 C. $640 D. $620 E. $600 Use the graphical linear programming method AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #84 Topic Area: Graphical Linear Programming 85. For the production combination of 800 boxes of Deluxe and 600 boxes of Classic, which resource is slack (not fully used)? A. sugar (only) B. flour (only) C. salt (only) D. sugar and flour E. sugar and salt These resources are not fully used AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #85 Topic Area: Graphical Linear Programming The logistics/operations manager of a mail order house purchases two products for resale: King Beds (K) and Queen Beds (Q). Each King Bed costs $500 and requires 100 cubic feet of storage space, and each Queen Bed costs $300 and requires 90 cubic feet of storage space. The manager has $75,000 to invest in beds this week, and her warehouse has 18,000 cubic feet available for storage. Profit for each King Bed is $300, and for each Queen Bed is $150 Stevenson Chapter 19 86. What is the objective function? A. Z = $150K + $300Q B. Z = $500K + $300Q C. Z = $300K + $150Q D. Z = $300K + $500Q E. Z = $100K + $90Q This is the objective function AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1902 Formulate a linear programming model from a description of a problem Stevenson Chapter 19 #86 Topic Area: Linear Programming Models 87. What is the storage space constraint? A. 200K + 100Q 18,000 B. 200K + 90Q 18,000 C. 300K + 90Q 18,000 D. 500K + 100Q 18,000 E. 100K + 90Q 18,000 This summarizes usage possibilities for this resource AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1902 Formulate a linear programming model from a description of a problem Stevenson Chapter 19 #87 Topic Area: Linear Programming Models 88. Which of the following is not a feasible purchase combination? A. 0 King Beds and 0 Queen Beds B. 0 King Beds and 250 Queen Beds C. 150 King Beds and 0 Queen Beds D. 90 King Beds and 100 Queen Beds E. 0 King Beds and 200 Queen Beds This is not a feasible combination AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #88 Topic Area: Graphical Linear Programming 89. What is the maximum profit? A. $0 B. $30,000 C. $42,000 D. $45,000 E. $54,000 Use the graphical linear programming method AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #89 Topic Area: Graphical Linear Programming 90. For the purchase combination 0 King Beds and 200 Queen Beds, which resource is "slack" (not fully used)? A. investment money (only) B. storage space (only) C. both investment money and storage space D. neither investment money nor storage space E. cannot be determined exactly These resources are not fully utilized AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #90 Topic Area: Graphical Linear Programming 91. Wood Specialties Company produces wall shelves, bookends, and shadow boxes. It is necessary to plan the production schedule for next week. The wall shelves, bookends, and shadow boxes are made of oak, of which the company has 600 board feet. A wall shelf requires 4 board feet, bookends require 2 board feet, and a shadow box requires 3 board feet. The company has a power saw for cutting the oak boards into the appropriate pieces; a wall shelf requires 30 minutes, bookends require 15 minutes, and a shadow box requires 15 minutes. The power saw is expected to be available for 36 hours next week. After cutting, the pieces of work in process are hand finished in the finishing department, which consists of 4 skilled and experienced craftsmen, each of whom can complete any of the products. A wall shelf requires 60 minutes of finishing, bookends require 30 minutes, and a shadow box requires 90 minutes. The finishing department is expected to operate for 40 hours next week. Wall shelves sell for $29.95 and have a unit variable cost of $17.95; bookends sell for $11.95 and have a unit variable cost of $4.95; a shadow box sells for $16.95 and has a unit variable cost of $8.95 (A) Is this a problem in maximization or minimization? (B) What are the decision variables? Suggest symbols for them (C) What is the objective function? (D) What are the constraints? (A) Since the problem contains information about the selling price, it will involve maximization (B) The management can decide how many wall shelves, bookends, and shadow boxes to produce each week. We suggest using W, B, and S (C) Maximize Z = 12W + 7B + 8S (D) Oak) 4W + 2B + 3S 600 board feet Saw) (1/2)W + (1/4)B + (1/4)S 36 hours Finishing) 1W + (1/2)B +(3/2)S 40 hours Feedback: Put the details of the situation into the usual linear programming format AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1901 Describe the type of problem that would lend itself to solution using linear programming Learning Objective: 1902 Formulate a linear programming model from a description of a problem Stevenson Chapter 19 #91 Topic Area: Linear Programming Models A company produces two products (A and B) using three resources (I, II, and III). Each product A requires 1 unit of resource I and 3 units of resource II; and has a profit of $1. Each product B requires 2 units of resource I, 3 units of resource II, and 4 units of resource III; and has a profit of $3. Resource I is constrained to 40 units maximum per day; resource II, 90 units; and resource III, 60 units Stevenson Chapter 19 92. What is the objective function? Z = $1A + $3B Feedback: This is the objective function AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1902 Formulate a linear programming model from a description of a problem Stevenson Chapter 19 #92 Topic Area: Linear Programming Models 93. What is the constraint for resource I? 1A + 2B 40 Feedback: This is the constraint for resource I AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1902 Formulate a linear programming model from a description of a problem Stevenson Chapter 19 #93 Topic Area: Linear Programming Models 94. What is the constraint for resource II? 3A + 3B 90 Feedback: This is the constraint for resource II AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1902 Formulate a linear programming model from a description of a problem Stevenson Chapter 19 #94 Topic Area: Linear Programming Models 95. What is the constraint for resource III? 4B 60 Feedback: This is the constraint for resource III AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1902 Formulate a linear programming model from a description of a problem Stevenson Chapter 19 #95 Topic Area: Linear Programming Models 96. What are the corner points of the feasible solution space? A= 0,B= 0; A= 30,B= 0; A= 20,B= 10; A= 10,B= 15; A= 0,B= 15 Feedback: Use the graphical method to find these corners AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #96 Topic Area: Graphical Linear Programming 97. Is the production combination 10 A's and 10 B's feasible? Yes Feedback: Enter these values into the constraint equations and verify that no constraints are violated AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #97 Topic Area: Graphical Linear Programming 98. Is the production combination 15 A's and 15 B's feasible? No Feedback: When these values are entered into the constrain equations, at least one constraint is violated AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #98 Topic Area: Graphical Linear Programming 99. What is the optimum production combination and its profits? A= 10,B= 15; Z= $55 Feedback: Use the graphical linear programming method AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #99 Topic Area: Graphical Linear Programming 100. What is the slack (unused amount) for each resource for the optimum production combination? S(I)= 0; S(II)= 15; S(III)= 0 Feedback: Enter the values for the decision variables into the constraint equations AACSB: Analytic Blooms: Apply Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #100 Topic Area: Graphical Linear Programming 101. A novice linear programmer is dealing with a three decisionvariable problem. To compare the attractiveness of various feasible decisionvariable combinations, values of the objective function at corners are calculated. This is an example of _. A. empiritation B. explicitation C. evaluation D. enumeration E. elicitation The enumeration approach substitutes the coordinates of each corner point into the objective function to determine which corner point is optimal AACSB: Reflective Thinking Blooms: Remember Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #101 Topic Area: Graphical Linear Programming 102. When we use less of a resource than was available, in linear programming that resource would be called non . A. binding B. feasible C. reduced cost D. linear E. enumerated Nonbinding resources are not used up AACSB: Reflective Thinking Blooms: Remember Difficulty: Medium Learning Objective: 1903 Solve simple linear programming problems using the graphical method Stevenson Chapter 19 #102 Topic Area: Graphical Linear Programming 103. Once we go beyond two decision variables, typically the _ method of linear programming must be used. A. simplicit B. unidimensional C. simplex D. dynamic E. exponential The simplex method typically must be used for situations in which there are more than two decision variables AACSB: Reflective Thinking Blooms: Remember Difficulty: Easy Learning Objective: 1904 Interpret computer solutions of linear programming problems Stevenson Chapter 19 #103 Topic Area: The Simplex Method 104. _ is a means of assessing the impact of changing parameters in a linear programming model. A. simulplex B. simplex C. slack D. surplus E. sensitivity Evaluating the impact of parameter changes is in the realm of sensitivity analysis AACSB: Reflective Thinking Blooms: Remember Difficulty: Medium Learning Objective: 1905 Do sensitivity analysis on the solution of a linear programming problem Stevenson Chapter 19 #104 Topic Area: Sensitivity Analysis 105. It has been determined that, with respect to resource X, a oneunit increase in availability of X would lead to a $3.50 increase in the value of the objective function. This value would be X's _. A. range of optimality B. shadow price C. range of feasibility D. slack E. surplus The shadow price is the marginal value of an additional unit of the resource in question AACSB: Reflective Thinking Blooms: Remember Difficulty: Medium Learning Objective: 1905 Do sensitivity analysis on the solution of a linear programming problem Stevenson Chapter 19 #105 Topic Area: Sensitivity Analysis ch19 Summary Category # of Questions AACSB: Analytic 58 AACSB: Reflective Thinking 47 Blooms: Apply 58 Blooms: Remember 40 Blooms: Understand Difficulty: Easy 13 Difficulty: Hard Difficulty: Medium 83 Learning Objective: 1901 Describe the type of problem that would lend itself to solution using linear programming 13 Learning Objective: 1902 Formulate a linear programming model from a description of a problem 26 Learning Objective: 1903 Solve simple linear programming problems using the graphical method 52 Learning Objective: 1904 Interpret computer solutions of linear programming problems Learning Objective: 1905 Do sensitivity analysis on the solution of a linear programming problem 12 Stevenson Chapter 19 113 Topic Area: Computer Solutions Topic Area: Graphical Linear Programming 53 Topic Area: Introduction Topic Area: Linear Programming Models 33 Topic Area: Sensitivity Analysis 12 Topic Area: The Simplex Method ... C. both Colombian beans and Dominican beans D. neither Colombian beans nor Dominican beans E. cannot be determined exactly The operations manager for the Blue Moon Brewing Co. produces two beers: Lite (L) and Dark (D). Two of his... A. sugar (only) B. flour (only) C. salt (only) D. sugar and flour E. sugar and salt The logistics /operations manager of a mail order house purchases two products for resale: King Beds (K) and Queen Beds (Q). Each King Bed costs $500 and requires 100 cubic feet of storage space, and each Queen Bed ... to a $3.50 increase in the value of the objective function. This value would be X's _. A. range of optimality B. shadow price C. range of feasibility D. slack E. surplus ch19 Key 1. Linear programming techniques will always produce an optimal solution to an LP problem.
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