Math 164 Homework 4: Linear Programming, Assignments of Optimization Techniques in Engineering

A university mathematics homework assignment focusing on linear programming. Students are required to solve various problems, including graphically representing and finding extreme points of feasible regions, converting linear programs to standard form, and determining directions of unboundedness.

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Pre 2010

Uploaded on 08/26/2009

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Math 164: Homework #4, due on Wednesday, April 29, 2009
Review Sections 4.1-4.3 from the textbook and solve additional problems.
[1] Solve the following linear program graphically:
maximize z= 6x13x2,subject to
2x1+ 5x210,
3x1+ 2x240,
x1, x215.
[2] Convert the following linear program to standard form:
minimize z=x15x27x3, subject to
5x12x2+ 6x35
3x1+ 4x29x3= 3
7x1+ 3x2+ 5x39
x1 2, x2, x3free.
[3] Consider the system of linear constraints
2x1+x2100,
x1+x280,
x140,
x1, x20.
(a) Write this system in standard form, and determine all the basic solu-
tions (feasible and infeasible).
(b) Determine the extreme points of the feasible region (corresponding to
both the standard form, as well as the original version).
[4] Consider a linear program with the constraints in standard form:
{Ax =b, x 0}.
Prove that if d6= 0 satisfies Ad = 0 and d0, then dis a direction of
unboundedness.
[5] Consider the linear program: minimize z=5x17x2, subject to
3x1+ 2x230
2x1+x212
x1, x20.
(a) Draw a graph of the feasible region
(b) Determine the extreme points of the feasible region
(c) Determine two linearly-independent directions of unboundedness.
(b) Convert the linear program to standard form and determine two
linearly-independent directions of unboundedness for this version of the prob-
lem. Verify that the directions of unboundedness satisfy Ad =~
0 and d~
0.
1

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Math 164: Homework #4, due on Wednesday, April 29, 2009

  • Review Sections 4.1-4.3 from the textbook and solve additional problems.

[1] Solve the following linear program graphically:

maximize z = 6x 1 − 3 x 2 , subject to

  

2 x 1 + 5x 2 ≥ 10 , 3 x 1 + 2x 2 ≤ 40 , x 1 , x 2 ≤ 15.

[2] Convert the following linear program to standard form:

minimize z = x 1 − 5 x 2 − 7 x 3 , subject to

    

5 x 1 − 2 x 2 + 6x 3 ≥ 5 3 x 1 + 4x 2 − 9 x 3 = 3 7 x 1 + 3x 2 + 5x 3 ≤ 9 x 1 ≥ − 2 , x 2 , x 3 free.

[3] Consider the system of linear constraints

2 x 1 + x 2 ≤ 100 , x 1 + x 2 ≤ 80 , x 1 ≤ 40 , x 1 , x 2 ≥ 0.

(a) Write this system in standard form, and determine all the basic solu- tions (feasible and infeasible). (b) Determine the extreme points of the feasible region (corresponding to both the standard form, as well as the original version).

[4] Consider a linear program with the constraints in standard form:

{Ax = b, x ≥ 0 }.

Prove that if d 6 = 0 satisfies Ad = 0 and d ≥ 0, then d is a direction of unboundedness.

[5] Consider the linear program: minimize z = − 5 x 1 − 7 x 2 , subject to 



− 3 x 1 + 2x 2 ≤ 30 − 2 x 1 + x 2 ≤ 12 x 1 , x 2 ≥ 0. (a) Draw a graph of the feasible region (b) Determine the extreme points of the feasible region (c) Determine two linearly-independent directions of unboundedness. (b) Convert the linear program to standard form and determine two linearly-independent directions of unboundedness for this version of the prob- lem. Verify that the directions of unboundedness satisfy Ad = ~0 and d ≥ ~0.