Pls create a case problem with the application of linear programming distribution models with formulation and interpret the results of it with the following format: 1. Decision variables 2. Objective function 3. Constraints 4. Non-negativity constraints 5. Optimal solution
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- Solve Problem 1 with the extra assumption that the investments can be grouped naturally as follows: 14, 58, 912, 1316, and 1720. a. Find the optimal investments when at most one investment from each group can be selected. b. Find the optimal investments when at least one investment from each group must be selected. (If the budget isnt large enough to permit this, increase the budget to a larger value.)Consider the following LP problem: Min 6X+ 27Y Subject to : 2 X + 9Y => 25, and X + Y <= 75. Pick a suitable statement for this problem: a. X=37.5, Y=37.5 is the only optimal solution. b. Optimal Obj. function value is 75 c. X = 0, Y = 0 is the only optimal solution. d. Optimal Obj. function value is 01. Consider the following linear programming formulation: Min 5x + 2y Subject to (1) 3x + 6y ≥ 18 (2) 5x + 4y ≥ 20 (3) 8x + 2y ≥ 16 (4) 7x + 6y ≤ 42 (5) x, y ≥ 0 a. Solve the problem graphically. Specifically, show each constraint and the feasible region, draw an objective function line and identify an optimal point (the solution). When reporting the optimal solution and the corresponding objective function value, you may estimate the optimal x and y values from the graph. b. What are the optimal values of x and y, using the solver add-in? What is the corresponding value of the objective function? c. How many extreme points does the feasible region have? Enumerate them. Hint: It's from the graph. d. Change the objective function to 15x + 12y.. What is the new optimal solution(s)?
- An XYZ company has a W, H, O plant with a monthly production capacity of 60 tons, 50 tons, and 42 tons, respectively; and has 3 sales warehouses in cities A, B, C, D Where each warehouse has a monthly requirement of 30 tons, 34 tons, 44 tons and 25 tons. With shipping cost W to ABCD = IDR 12,000,-, IDR. 8.000,-, Rp. 12.000,-, Rp. 14,000,-; H to A B C D = Rp. 8.000,-, Rp. 18.000,-, Rp. 10,000,-, Rp. 6.000,-; and O to ABCD = Rp. 16.000,-, Rp. 16.000,-, Rp. 2,000, Rp. 10,000,-. Please calculate using Vogel's Approximation Method or VAM Question a. What is the best transportation model in your opinion to solve the above problems? b. What is the minimum transportation cost to solve the shipping transportation problem! c. Based on these calculations, give suggestions regarding the transportation model and the amount of costs incurred by the company!Please do not give solution in image format thanku Consider the following set of constraints (Maximization problem): 10X+ 20y>= 43, and 30X+ 10Y >= 21.5. The following is true for this problem: a. Infeasible problem b. Unbounded problem c. X=0, Y=10 is the optimal solution d. X=10, Y=16 is the optimal solution. 2. Consider the following LP problem: Min 12X+ 12Y; Subject to ; 4 X + 4Y <= 31, and X + Y <= 93. Which one of the following is true: a. Optimal objective function value is O. b. Optimal objective function value is 93. c. Slack for each constraint is 0. d. X-46.5, Y=46.5 is the optimal solutionSet up the simplex matrix used to solve the linear programming problem. Assume all variables are nonnegative.Maximize f = 5x + 9y subject to 8x + 5y ≤ 200 x + 6y ≤ 250. x y s1 s2 f first constraint second constraint objective function
- Max 30x1 x2 s.t. 2x1 x2 ≤ 4 2x1 2x2 ≤ 6 x1, x2 ≥ 0 (a) Solve graphically and state the optimal solution. (b) Keeping all the other data as is, what per unit profitability should the product, whose current optimal value is zero, have in order that this product enter the optimal solution at a positive level? (c) How many optimal corner solutions exist after making the change described in part (b)? What are they? (d) In the original problem, how much can the right-hand side (RHS) of the second constraint be increased (or decreased) before the optimal solution is changed? (e) Answer part (d) for the RHS of the first constraint. (f) How do you explain the difference between parts (d) and (e)? (g) What will be the impact of adding the constraint 4x1 x2 = 4 to the original model? (h) What is the impact (on the optimal solution) of adding the constraint 3x1 3x2 ≤ 15 to the original model? (i) Fill in the blanks: The difference between parts (g) and (h) is that the original optimal solution…Suppose Jack like to solve the following formulation in Excel. And the problem is setup in Excel like this: See attached picture. A B C D E 1 X1 X2 2 decision variable objective 3 coefficient of objective function 2 3 4 Constraints LHS RHS 5 Constraints 1 2 1 3 6 Constraints 2 4 5 20 7 Constraints 3 2 8 16 8 Constraints 4 5 6 60 We want to put our objective function in cell D3. What should we type in D3? In cell D5 to D8, we will put the left hand side of our constraint. What should we type in D8? In OpenSolver, what should we assign to Variable Cell? What should you do to input the non-negativity constraint in OpenSolver?Consider the following LP problem: Min 6X+ 18Y; Subject to : 3 X + 9Y <= 47, and X + Y <= 141. Which one of the following is true?: a. Slack for each constraint is zero. b. Optimal Obj. function value is 94 c. X=70.5, Y=70.5 is the only optimal solution. d. Optimal Obj. function value is 0
- Which of the following could not be a constraint for a linear programming problem? Multiple Choice 1A + 2B = 3 1A + 2B 1A + 2B ≤ 3 1A + 2B ≥ 3 1A + 2B + 3C ≤ 3Explain all the steps when implementing the Branch and Bound method for the following optimization problem: Max 15*x1+12*x2+4*x3+2*x4 s.t. 8*x1+5*x2+3*x3+2*x4 <=10 3*x1+2*x3<=4 x1, x2, x3, x4 binary21. A linear programming problem has two constraints 2X + 4Y ≤ 100 and 1X + 8Y ≤ 100, plus nonnegativity constraints on X and Y. Which of the following statements about its feasible region is TRUE? Part 2 A. The graphical origin (0, 0) is not in the feasible region. B. The feasible region includes all points that satisfy one constraint, the other, or both. C. The feasible region cannot be determined without knowing whether the problem is to be minimized or maximized. D. The two corner points are (0, 0) and (50, 12.5). E. There are four corner points including (50, 0) and (0, 12.5)