作业math | 作业Objective – math

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作业math – 该题目是一个常规的math的练习题目代写, 是比较有代表性的math/Objective等代写方向

math代写 代写math 数学代做

 math 484 Final Examination Spring 2022
Students in this class are expected to complete the final examination on their own, and to write their
answers in their own words. Students are not to obtain exam answers from any other person and
present them as their own. Students who present other peoples work as their own may receive a
zero score on the examination and an F or XF grade for the course. All University and College
policies regarding academic integrity/academic dishonesty apply to this course and to the students
enrolled in this course. Academic dishonesty could result in a transcript notation indicating failure
due to academic misconduct.
Show all your work and explain your work briefly in full sentences.
Final answers without supporting work and explanations will not receive credit.
Write cleanly! If your work is not easily readable and intelligible, you will lose points!
  1. Benjamin is trying to solve a linear optimization problem involving seven decision variables and with constraints in standard form. He is using the tableau implementation of the simplex algorithm. Having performed a number of pivots, he has reached the following tableau:

1 2 3 4 5 6 7

123 0 0 489 321 45 0 0

1 = 40 1 0 163 107 15 0 0

2 = 12 0 1 54 35 4 0 0

6 = 71 0 0 294 193 28 1 0

7 = 494 0 0 2046 1340 180 0 1

Let us denote the feasible polyhedron of the problem Benjamin is attempting to solve by the
symbol.

2 points (a) What is the basic feasible solution ofcorresponding to the tableau above? Explain.

6 points (b) Find all the extreme points of, which are adjacent to this basic feasible solution. Explain.

3 points (c) Find their respective Objective values. Explain.

3 points (d) From the given tableau, is it possible to recover a system of linear constraints describing

? If yes, write down such a description. Explain.
1 point (e) Is it possible to recover the objective vector of Benjamins problem? If yes, write down
the objective vector. Explain.
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