Mark each statement as True or False.The basic feasible solutions before and after a pivot are always(a)different.(b)The artificial linear program of phase 1 might terminate with anunbounded solution.(c)original LP must be infeasible.If the phase 1 LP terminates with a basic artificial variable, the(d)cost and still be the unique optimum.An optimal solution may have a nonbasic variable with zero reduced(e)guaranteed to terminate with an optimal solution.If a linear program is not degenerate, then the simplex method is(f)If the simplex method cycles, the LP is degenerate.(g)Every feasible linear program has an optimal solution or has anunbounded solution.

mark each statement true or false (a) the basic feasible solutions before and after a pivot are…

Answered: Mark each statement as True or False.…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Perth Mining Company operates two mines for the purpose of extracting gold and silver. The Saddle Mine costs $30,000/day to operate, and it yields 50 oz of gold and 3000 oz of silver each of a day The Horseshoe Mine costs $16,000/day to operate, and it yields 75 oz of gold and 1000 oz of silver each of y day. Company management has set a target of at least 650 oz of gold and 18,000 of silver. (a) How many days should each mine be operated so that the target can be met at a minimum cost? The minimum is C - 288000 at (x,y)-(0,18 (b) Suppose C cx + 16,000y. Find the range of values that the Saddle Mine's daily operating cost, the coefficient c of x, can assume without changing the optimal auton SCS (c) Find the range of values that the requirement for gold can assume. s (requirement for gold) s (d) Find the shadow price for the requirement for gold. (Round your answer to the nearest cent.) S
2. Solve by Lagrange Multiplier Method: Clearly identify your constraint function and your system. You may use either approach you learned in class and on the video. Mr. Eppolito has S360 to spend on fencing to fence a rectangular garden. The fencing for the north and south sides of the garden costs $10/ft. The fencing for the east and west sides costs $15/ft. Find the dimensions that will allow Mr. Eppolito to fence in the largest-sized garden. Draw a diagram of this scenario. Write the method you will use to solve it, then do so, showing all the necessary equations.
Hi. I got the solution to this question wrong, despite asking one of your experts. Please can you give it another go and help me by providing a detailed solution. Thank you
In this problem we want to understand how the simplex method deals with an LP problem having an infinite number of solutions. Solve: Maximize z = 2.x1 + 4x2 subject to x1 + 2x2 0. You will get an optimal solution by doing just one iteration. But there could be more solutions as the objective function has the same slope as the line determined by the second constraint. If you did not know that, what features in the tableau would have signalled this possibility? State your idea as a rule that checks the final tableau to determine if an infinite number of op solutions is possible. Give a very brief explanation to justify why your rule should work. mal Using your rule, do one more iteration to obtain a second optimal solution.
Food item 1 has 11 units of nutrient 1, 275 units of nutrient 2, and 17units of nutrient 3. Food item 2 has 2 units of nutrient 1, 875 units of nutrient 2, and4 units of nutrient 3. A human desires a constraint of at most 15 units of nutrient 1and 700 units of nutrient 2 among these two food items. How much of each food itemwould maximize the value of nutrient 3?
2. Given the general linear programming problem, write the equations (with slack/surplus variables) that would be used for the simplex method. Write the initial tableau and give the current solution Minimize: c = 3x + 2y + 4z Subject to: 3x + 2y +4z 2 20 2х -у + 3z < 18 х, у, z 2 0 Tableau: Current solution:
Hi, I would need some help for certain parts regarding a linear optimization problem. (a) Prove that the set of feasible solutions of the problem is bounded. (b) Find all basic feasible solutions by considering all the combinations of linearly independent constraints. (c) Which basic feasible solutions found in (c) are optimal solutions?
Q1\A) Put True or False for the following questions: 1. A solution of linear programing problem is called feasible if it satisfies all of the constraints. 2. Every linear program has a function called objective function. 3. Level line is the set of all points where the objective function takes no specific value. 4. The dual problem of primal problem is also primal. 5. We compute a new tableau if we get the optimal solution from the simplex method.
6. Consider a constrained optimisation problem with the objective function f(x) = 3x + 2y and the constraint 2x+y=10. Find the maximum value of f(x) within the feasible region.
A company decides to change its floor plan from cubicle to open office. This will bring in a constant stream of $1,000 in extra income annually. If the company invests this extra income in an account that earns 2.5% continuously compounded interest for ten years, is it worth the change? The change in floor plan costs $7,000.
Can you please help me?

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