Why is it generally necessary to add nonnegativityconstraints to an optimization model? Wouldn’t Solverautomatically choose nonnegative values for thedecision variable cells?
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Why is it generally necessary to add nonnegativity
constraints to an optimization model? Wouldn’t Solver
automatically choose nonnegative values for the
decision variable cells?
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- Adding nonnegativity restrictions to an optimization model is often required because... Are nonnegative values for the decision variable cells picked by Solver by default?1. A specific assignment of values to decision variables is called what? a. Constraint b. Feasible c. Solution d. None of the above 2. Which of the following must be true of a feasible solution a. All of what Solver calls changing variables must be greater than 0 b. It is optimal c. It violates no constraints d. None of the aboveGiven four decision variables A, B, C, and D, which of the following could be a linear programming problem constraint? 1A + 2B - 1C/D >=23 1A + 2A*B + 3A*B/C + 4A*B*C*D >=100 1A + 2B + 3C + 4D >=100 1A + 2B/C + 3D <=45 1A + 2B*C + 3D <=100
- In linear programming problems, you always need to include a(n) ___________ constraint, to ensure that all decision variables are greater than or equal to 0. Group of answer choices positive time production non-negativityXYZ Inc. produces two types of paper towels, called regular and super-soaker. Regular uses 2 units of recycled paper per unit of production and super-soaker uses 3 units of recycled paper per unit of production. The total amount of recycled paper available per month is 10,000. Letting X1 be the number of units of regular produced per month and X2 represent the number of units of super-soaker produced per month, the appropriate constraint/s will be ___________ a. 2X1 = 3X2 b. 2X1 + 3X2 ≥ 10000 c. 2X1 + 3X2 = 10000. d. 2X1 + 3X2 ≤ 1000The linear program Max 3X1 + 2X2 is solved subject to the constraints i) X1 + X2 ≤ 10 ii) 3X1 + X2 ≤ 24 iii) X1 + 2X2 ≤ 16 and iv) non-negativity for both X1 and X2. Which of the following statements is true? A. The optimal solution occurs at the point (6, 6). B. The feasible region has five corner points. C. The optimal solution occurs at (8, 0) and the optimal value is 24. D. The optimal solution value is 41.
- Find the optimal solution for the following problem. Maximize C = 4x + 12y subject to 3x + 5y ≤ 12 6x + 2y ≤ 10 and x ≥ 0, y ≥ 0. What is the optimal value of x? What is the optimal value of y? (Round your answer to 3 decimal places.) What is the maximum value of the objective function? (Round your answer to 3 decimal places.)Analyze algebraically what special case in simplex application is present in each of the LP model below. Give an explanation to support your answer. a) Maximize z = 4x1 + 2x2 Subject to: 2x1 - x2 ≤ 2 3x1 - 4x2 ≤ 8 x1, x2 ≥ 0b) Maximize z = 3x1 + 2x2 Subject to: 4x1 - x2 ≤ 8 4x1 + 3x2 ≤ 12 4x1 + x2 ≤ 8 x1, x2 ≥ 0Do you agree or disagree with the following statements? Match accordingly For a convex programming problem, a local optimum is not a global optimum KKT conditions can be used to determine the optimality of a potential solution for generally constrained problems For convex programming problems, if an objective function is being maximized, it is required to be convex and if it is being minimized it is required to be concave
- what will happen if the right hand side value of a constraint in two variable linear programming problems is changed? a. optimal measure of performance may change b. parallel shift must be made in the graph of that constraint c. optimal valued for one or more of the decision variables may change d. all of the above e. none of the abovePlease help with correct answers in details: step by step Q1 The optimal solution of this linear programming problem is at the intersection of constraints 1 and 2. Max 3x1 + x2 s.t. 4x1 + x2 ≤ 400 4x1 + 3x2 ≤ 600 x1 + 2x2 ≤ 300 x1, x2 ≥ 0 Over what range can the coefficient of x1 vary before the current solution is no longer optimal? (Round your answers to two decimal places.) ______ to ______? Over what range can the coefficient of x2 vary before the current solution is no longer optimal? (Round your answers to two decimal places.) _______ to _______? Compute the dual value for the first constraint. _______ Compute the dual value for the second constraint. _______ Compute the dual value for the third constraint. _______Is my solution correct and did I fully answer the questions? (see attachment for my solution) Question: There are three factories on Momiss River. Each emits two types of pollutants, labeled P1 and P2, into the river. If the waste from each factory is processed, the pollution in the river can be reduced. It costs $1,500 to process a ton of factory 1 waste, and each ton processed reduces the amount of P1 by 0.10 ton and the amount of P2 by 0.45 ton. It costs $2,500 to process a ton of factory 2 waste, and each ton processed reduces the amount of P1 by 0.20 ton and the amount of P2 by 0.25 ton. It costs $3,000 to process a ton of factory 3 waste, and each ton processed reduces the amount of P1 by 0.40 ton and the amount of P2 by 0.50 ton. The state wants to reduce the amount of P1 in the river by at least 125 tons and the amount of P2 by at least 175 tons. a. Use Solver to determine how to minimize the cost of reducing pollution by the desired amounts. Are the LP assumptions…