use the simplex method to solve the given linear programming problem (In each case the objective function is to be maximized.) Objective function: z = x_{1} - x_{2} + 2x_{3} Constraints: 2x_{1} + 2x_{2} <= 8 x_{3} <= 5 x_{1}, x_{2}, x_{3} >= 0
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use the simplex method to solve the given linear programming problem (In each case the objective function is to be maximized.) Objective function: z = x_{1} - x_{2} + 2x_{3} Constraints: 2x_{1} + 2x_{2} <= 8 x_{3} <= 5 x_{1}, x_{2}, x_{3} >= 0
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- Solve the following Linear Programming model using the graphical method (USING EXCEL){Write the steps of construction} Q1)MaximizeH = x + 3y Objective functionsubject tox + y ≤ 502x + y ≤ 60 x ≥ 0, y ≥ 0Having trouble setting up the problem using excel solver and inputting the constraintsWhat function does linear programming play in OR?
- Which of the folowing linear programming model has an unbounded feasible region? = 3x + 2y subject to the following : O max z x+ y34 *< 10 – 4y x20 y20 O None of the above O max z = 3x + 2y subject to the following : x+ 2y <4 x- ys1 x20 y20 O max z = 4x +2y subject to the following : x + 2y 24 3x + y27 -x + 2y s7 x20 y20Why Modifying the objective function is required?Maximize f = x + y subject to the following constraints: x + 2y ≤ 8 -2x + 3y ≤ 2 x ≤ 4 ≤ x 0 ≤ y
- Facility Location. A paper products manufacturer has enough capital to build and manage some additional manufacturing plants in the United States in order to meet increased demand in three cities: New York City, NY; Los Angeles, CA; and Topeka, KS. The company is considering building in Denver, CO; Seattle, WA; and St. Louis, MO. Max Operating Capacity 400 tons/day 700 tons/day Denver Seattle $10/ton $17/tor $5/ton $11/ton.... $18/ton.... $28/ton Los Angeles Topeka New York City Figure 1: Graphical representation of the given data = • The cost fi of building plants in these cities is fi $10,000,000 in Seattle. Unmet Demand 300 tons/day 100 tons/day 500 tons/day • Due to geographic constraints, plants in Denver and Seattle would have a maximum operating capacity kį of 400 tons/day and 700 tons/day respectively. $5,000,000 in Denver and f2 = • The cost cij per ton of transporting paper from city i to city j is outlined in Figure 1. • The unmet demand d, for Los Angeles, Topeka, and New…Can you give me a clear answer to this question: Decision Variables: Objective Function: Constraints: (By table) Explicit constraints: Implicit contraints:The sketch of a feasible region is given below, which point is not a point consistent with a production option for this programming problem? (0,10) (0,8) (0,0) O (0,6) O (4,0) O (4,2) O (6,0) (2,8) (6,4) (6,0) 27 (10,0) They are all in the feasible region.
- In problems involving maximization and minimization, what is the objective function? States intended outcome in equation form Incorporates constraint of maximum budget Lists set of potential restrictions on the solution Cites constraints to ensure objectivityAna is a university student with 12 hours available daily, and she wants to distribute her time betweenstudy (x) and leisure (y) activities. She wants to maximize her total enjoyment while fulfilling heruniversity obligations. Ana considers leisure to be twice (2) as enjoyable as studying, but she alsobelieves that she should spend at least twice (2) as much time studying as she does on leisure activities.Additionally, she cannot spend more than five (5) hours a day on leisure activities to ensure that she hasenough time for her university obligations. 1. How much additional enjoyment would Ana get if she had one more hour per dayavailable, so 13 instead of 12 (dual price)?2. Would Ana experience a greater level of enjoyment if she allows herself to have amaximum of six hours per day to leisure activities instead of five, while still fulfilling her universityobligations within the 12 hours available (dual price)?3. What is the allowable increase of the coefficient accompanying leisure…Solve the linear programming problem by the method of corners. Maximize P= x + 6y subject to x + y s4 2x + y s6 x 2 0, y 20 The maximum is P = at (x, y) = Need Help? Read It