Skip to content Skip to navigation Skip to collection information

Connexions

You are here: Home » Content » Applied Finite Mathematics » Linear Programing: The Simplex Method: Homework

Navigation

Lenses

What is a lens?

Definition of a lens

Lenses

A lens is a custom view of the content in the repository. You can think of it as a fancy kind of list that will let you see content through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

This content is ...

Endorsed by Endorsed (What does "Endorsed by" mean?)

This content has been endorsed by the organizations listed. Click each link for a list of all content endorsed by the organization.
  • College Open Textbooks display tagshide tags

    This collection is included inLens: Community College Open Textbook Collaborative
    By: CC Open Textbook Collaborative

    Comments:

    "Reviewer's Comments: 'I recommend this book for undergraduates. The content is especially useful for those in finance, probability statistics, and linear programming. The course material is […]"

    Click the "College Open Textbooks" link to see all content they endorse.

    Click the tag icon tag icon to display tags associated with this content.

Affiliated with (What does "Affiliated with" mean?)

This content is either by members of the organizations listed or about topics related to the organizations listed. Click each link to see a list of all content affiliated with the organization.
  • Bookshare

    This collection is included inLens: Bookshare's Lens
    By: Bookshare - A Benetech Initiative

    Comments:

    "Accessible versions of this collection are available at Bookshare. DAISY and BRF provided."

    Click the "Bookshare" link to see all content affiliated with them.

  • Featured Content display tagshide tags

    This collection is included inLens: Connexions Featured Content
    By: Connexions

    Comments:

    "Applied Finite Mathematics covers topics including linear equations, matrices, linear programming, the mathematics of finance, sets and counting, probability, Markov chains, and game theory."

    Click the "Featured Content" link to see all content affiliated with them.

    Click the tag icon tag icon to display tags associated with this content.

Recently Viewed

This feature requires Javascript to be enabled.

Tags

(What is a tag?)

These tags come from the endorsement, affiliation, and other lenses that include this content.
Download
x

Download collection as:

  • PDF
  • EPUB (what's this?)

    What is an EPUB file?

    EPUB is an electronic book format that can be read on a variety of mobile devices.

    Downloading to a reading device

    For detailed instructions on how to download this content's EPUB to your specific device, click the "(what's this?)" link.

  • More downloads ...

Download module as:

  • PDF
  • EPUB (what's this?)

    What is an EPUB file?

    EPUB is an electronic book format that can be read on a variety of mobile devices.

    Downloading to a reading device

    For detailed instructions on how to download this content's EPUB to your specific device, click the "(what's this?)" link.

  • More downloads ...
Reuse / Edit
x

Collection:

Module:

Add to a lens
x

Add collection to:

Add module to:

Add to Favorites
x

Add collection to:

Add module to:

 

Linear Programing: The Simplex Method: Homework

Module by: UniqU, LLC. E-mail the author

Based on: Applied Finite Mathematics: Chapter 04 by Rupinder Sekhon

Summary: This chapter covers principles of the simplex method to Linear Programming. After completing this chapter students should be able to: solve linear programming maximization problems using the simplex method and solve the minimization problems using the simplex method.

MAXIMIZATION BY THE SIMPLEX METHOD

Solve the following linear programming problems using the simplex method.

Exercise 1

Maximize z=x1+2x2+3x3z=x1+2x2+3x3 size 12{z=x rSub { size 8{1} } +2x rSub { size 8{2} } +3x rSub { size 8{3} } } {}

subject to x1+x2+x3122x1+x2+3x318x1+x2+x3122x1+x2+3x318 size 12{ matrix { x rSub { size 8{1} } {} # +{} {} # x rSub { size 8{2} } {} # +{} {} # x rSub { size 8{3} } {} # <= {} {} # "12" {} ## 2x rSub { size 8{1} } {} # +{} {} # x rSub { size 8{2} } {} # +{} {} # 3x rSub { size 8{3} } {} # <= {} {} # "18"{} } } {}

x 1 , x 2 , x 3 0 x 1 , x 2 , x 3 0 size 12{x rSub { size 8{1} } ,x rSub { size 8{2} } ,x rSub { size 8{3} } >= 0} {}

Exercise 2

Maximize z=x1+2x2+x3z=x1+2x2+x3 size 12{z=x rSub { size 8{1} } +2x rSub { size 8{2} } +x rSub { size 8{3} } } {}

subject to x1+x23x2+x34x1+x35x1+x23x2+x34x1+x35 size 12{ matrix { x rSub { size 8{1} } {} # +{} {} # x rSub { size 8{2} } {} # <= {} {} # 3 {} ## x rSub { size 8{2} } {} # +{} {} # x rSub { size 8{3} } {} # <= {} {} # 4 {} ## x rSub { size 8{1} } {} # +{} {} # x rSub { size 8{3} } {} # <= {} {} # 5{} } } {}

x 1 , x 2 , x 3 0 x 1 , x 2 , x 3 0 size 12{x rSub { size 8{1} } ,x rSub { size 8{2} } ,x rSub { size 8{3} } >= 0} {}
(1)

Exercise 3

A farmer has 100 acres of land on which she plans to grow wheat and corn. Each acre of wheat requires 4 hours of labor and $20 of capital, and each acre of corn requires 16 hours of labor and $40 of capital. The farmer has at most 800 hours of labor and $2400 of capital available. If the profit from an acre of wheat is $80 and from an acre of corn is $100, how many acres of each crop should she plant to maximize her profit?

Exercise 4

A factory manufactures chairs, tables and bookcases each requiring the use of three operations: Cutting, Assembly, and Finishing. The first operation can be used at most 600 hours; the second at most 500 hours; and the third at most 300 hours. A chair requires 1 hour of cutting, 1 hour of assembly, and 1 hour of finishing; a table needs 1 hour of cutting, 2 hours of assembly, and 1 hour of finishing; and a bookcase requires 3 hours of cutting, 1 hour of assembly, and 1 hour of finishing. If the profit is $20 per unit for a chair, $30 for a table, and $25 for a bookcase, how many units of each should be manufactured to maximize profit?

Exercise 5

The Acme Apple company sells its Pippin, Macintosh, and Fuji apples in mixes. Box I contains 4 apples of each kind; Box II contains 6 Pippin, 3 Macintosh, and 3 Fuji; and Box III contains no Pippin, 8 Macintosh and 4 Fuji apples. At the end of the season, the company has altogether 2800 Pippin, 2200 Macintosh, and 2300 Fuji apples left. Determine the maximum number of boxes that the company can make.

MINIMIZATION BY THE SIMPLEX METHOD

In problems 1-2, convert each minimization problem into a maximization problem, the dual, and then solve by the simplex method.

Exercise 6

Minimize z=6x1+8x2z=6x1+8x2 size 12{z=6x rSub { size 8{1} } +8x rSub { size 8{2} } } {}

subject to 2x1+3x274x1+5x292x1+3x274x1+5x29 size 12{ matrix { 2x rSub { size 8{1} } {} # +{} {} # 3x rSub { size 8{2} } {} # >= {} {} # 7 {} ## 4x rSub { size 8{1} } {} # +{} {} # 5x rSub { size 8{2} } {} # >= {} {} # 9{} } } {}

x 1 , x 2 0 x 1 , x 2 0 size 12{x rSub { size 8{1} } ,x rSub { size 8{2} } >= 0} {}

Exercise 7

Minimize z=5x1+6x2+7x3z=5x1+6x2+7x3 size 12{z=5x rSub { size 8{1} } +6x rSub { size 8{2} } +7x rSub { size 8{3} } } {}

subject to 3x1+2x2+3x3104x1+3x2+5x3123x1+2x2+3x3104x1+3x2+5x312 size 12{ matrix { 3x rSub { size 8{1} } {} # +{} {} # 2x rSub { size 8{2} } {} # +{} {} # 3x rSub { size 8{3} } {} # >= {} {} # "10" {} ## 4x rSub { size 8{1} } {} # +{} {} # 3x rSub { size 8{2} } {} # +{} {} # 5x rSub { size 8{3} } {} # >= {} {} # "12"{} } } {}

x 1 , x 2 , x 3 0 x 1 , x 2 , x 3 0 size 12{x rSub { size 8{1} } ,x rSub { size 8{2} } ,x rSub { size 8{3} } >= 0} {}

In the next two problems, convert each minimization problem into a maximization problem, the dual, and then solve by the simplex method.

Exercise 8

Minimize z=4x1+3x2z=4x1+3x2 size 12{z=4x rSub { size 8{1} } +3x rSub { size 8{2} } } {}

subject to x1+x2103x1+2x224x1+x2103x1+2x224 size 12{ matrix { x rSub { size 8{1} } {} # +{} {} # x rSub { size 8{2} } {} # >= {} {} # "10" {} ## 3x rSub { size 8{1} } {} # +{} {} # 2x rSub { size 8{2} } {} # >= {} {} # "24"{} } } {}

x , x 2 0 x , x 2 0 size 12{x,x rSub { size 8{2} } >= 0} {}

Exercise 9

A diet is to contain at least 8 units of vitamins, 9 units of minerals, and 10 calories. Three foods, Food A, Food B, and Food C are to be purchased. Each unit of Food A provides 1 unit of vitamins, 1 unit of minerals, and 2 calories. Each unit of Food B provides 2 units of vitamins, 1 unit of minerals, and 1 calorie. Each unit of Food C provides 2 units of vitamins, 1 unit of minerals, and 2 calories. If Food A costs $3 per unit, Food B costs $2 per unit and Food C costs $3 per unit, how many units of each food should be purchased to keep costs at a minimum?

CHAPTER REVIEW

Solve the following linear programming problems using the simplex method.

Exercise 10

Maximize z=5x1+3x2z=5x1+3x2 size 12{z=5x rSub { size 8{1} } +3x rSub { size 8{2} } } {}

subject to x1+x2122x1+x216x1+x2122x1+x216 size 12{ matrix { x rSub { size 8{1} } {} # +{} {} # x rSub { size 8{2} } {} # <= {} {} # "12" {} ## 2x rSub { size 8{1} } {} # +{} {} # x rSub { size 8{2} } {} # <= {} {} # "16"{} } } {}

x 1 0 ; x 2 0 x 1 0 ; x 2 0 size 12{x rSub { size 8{1} } >= 0;x rSub { size 8{2} } >= 0} {}

Exercise 11

Maximize z=5x1+8x2z=5x1+8x2 size 12{z=5x rSub { size 8{1} } +8x rSub { size 8{2} } } {}

subject to x1+2x2303x1+x230x1+2x2303x1+x230 size 12{ matrix { x rSub { size 8{1} } {} # +{} {} # 2x rSub { size 8{2} } {} # <= {} {} # "30" {} ## 3x rSub { size 8{1} } {} # +{} {} # x rSub { size 8{2} } {} # <= {} {} # "30"{} } } {}

x10x10 size 12{x rSub { size 8{1} } >= 0} {}; x20x20 size 12{x rSub { size 8{2} } >= 0} {}

Exercise 12

Maximize z=2x1+3x2+x3z=2x1+3x2+x3 size 12{z=2x rSub { size 8{1} } +3x rSub { size 8{2} } +x rSub { size 8{3} } } {}

subject to 4x1+2x2+5x3322x1+4x2+3x3284x1+2x2+5x3322x1+4x2+3x328 size 12{ matrix { 4x rSub { size 8{1} } {} # +{} {} # 2x rSub { size 8{2} } {} # +{} {} # 5x rSub { size 8{3} } {} # <= {} {} # "32" {} ## 2x rSub { size 8{1} } {} # +{} {} # 4x rSub { size 8{2} } {} # +{} {} # 3x rSub { size 8{3} } {} # <= {} {} # "28"{} } } {}

x 1 , x 2 , x 3 0 x 1 , x 2 , x 3 0 size 12{x rSub { size 8{1} } ,x rSub { size 8{2} } ,x rSub { size 8{3} } >= 0} {}

Exercise 13

Maximize z=x1+6x2+8x3z=x1+6x2+8x3 size 12{z=x rSub { size 8{1} } +6x rSub { size 8{2} } +8x rSub { size 8{3} } } {}

subject to x1+2x212002x2+x318004x1+x33600x1+2x212002x2+x318004x1+x33600 size 12{ matrix { x rSub { size 8{1} } {} # +{} {} # 2x rSub { size 8{2} } {} # <= {} {} # "1200" {} ## 2x rSub { size 8{2} } {} # +{} {} # x rSub { size 8{3} } {} # <= {} {} # "1800" {} ## 4x rSub { size 8{1} } {} # +{} {} # x rSub { size 8{3} } {} # <= {} {} # "3600"{} } } {}

x 1 , x 2 , x 3 0 x 1 , x 2 , x 3 0 size 12{x rSub { size 8{1} } ,x rSub { size 8{2} } ,x rSub { size 8{3} } >= 0} {}

Exercise 14

Maximize z=6x1+8x2+5x3z=6x1+8x2+5x3 size 12{z=6x rSub { size 8{1} } +8x rSub { size 8{2} } +5x rSub { size 8{3} } } {}

subject to 4x1+x2+x318002x1+2x2+x320004x1+2x2+x332004x1+x2+x318002x1+2x2+x320004x1+2x2+x33200 size 12{ matrix { 4x rSub { size 8{1} } {} # +{} {} # x rSub { size 8{2} } {} # +{} {} # x rSub { size 8{3} } {} # <= {} {} # "1800" {} ## 2x rSub { size 8{1} } {} # +{} {} # 2x rSub { size 8{2} } {} # +{} {} # x rSub { size 8{3} } {} # <= {} {} # "2000" {} ## 4x rSub { size 8{1} } {} # +{} {} # 2x rSub { size 8{2} } {} # +{} {} # x rSub { size 8{3} } {} # <= {} {} # "3200"{} } } {}

x 1 , x 2 , x 3 0 x 1 , x 2 , x 3 0 size 12{x rSub { size 8{1} } ,x rSub { size 8{2} } ,x rSub { size 8{3} } >= 0} {}

Exercise 15

Minimize z=12x1+10x2z=12x1+10x2 size 12{z="12"x rSub { size 8{1} } +"10"x rSub { size 8{2} } } {}

subject to x1+x262x1+x28x1+x262x1+x28 size 12{ matrix { x rSub { size 8{1} } {} # +{} {} # x rSub { size 8{2} } {} # >= {} {} # 6 {} ## 2x rSub { size 8{1} } {} # +{} {} # x rSub { size 8{2} } {} # >= {} {} # 8{} } } {}

x10x10 size 12{x rSub { size 8{1} } >= 0} {}; x20x20 size 12{x rSub { size 8{2} } >= 0} {}

Exercise 16

Minimize z=4x1+6x2+7x3z=4x1+6x2+7x3 size 12{z=4x rSub { size 8{1} } +6x rSub { size 8{2} } +7x rSub { size 8{3} } } {}

subject to x1+x2+2x320x1+2x2+x330x1+x2+2x320x1+2x2+x330 size 12{ matrix { x rSub { size 8{1} } {} # +{} {} # x rSub { size 8{2} } {} # +{} {} # 2x rSub { size 8{3} } {} # >= {} {} # "20" {} ## x rSub { size 8{1} } {} # +{} {} # 2x rSub { size 8{2} } {} # +{} {} # x rSub { size 8{3} } {} # >= {} {} # "30"{} } } {}

x 1 , x 2 , x 3 0 x 1 , x 2 , x 3 0 size 12{x rSub { size 8{1} } ,x rSub { size 8{2} } ,x rSub { size 8{3} } >= 0} {}
(2)

Exercise 17

Minimize z=40x1+48x2+30x3z=40x1+48x2+30x3 size 12{z="40"x rSub { size 8{1} } +"48"x rSub { size 8{2} } +"30"x rSub { size 8{3} } } {}

subject to 2x1+2x2+x325x1+3x2+2x3302x1+2x2+x325x1+3x2+2x330 size 12{ matrix { 2x rSub { size 8{1} } {} # +{} {} # 2x rSub { size 8{2} } {} # +{} {} # x rSub { size 8{3} } {} # >= {} {} # "25" {} ## ital "xl"1 {} # +{} {} # 3x rSub { size 8{2} } {} # +{} {} # 2 ital "xl"3 {} # >= {} {} # "30"{} } } {}

x 1 , x 2 , x 3 0 x 1 , x 2 , x 3 0 size 12{x rSub { size 8{1} } ,x rSub { size 8{2} } ,x rSub { size 8{3} } >= 0} {}

Exercise 18

A department store sells three different types of televisions: small, medium, and large. The store can sell up to 200 sets a month. The small, medium, and large televisions require, respectively, 3, 6, and 6 cubic feet of storage space, and a maximum of 1,020 cubic feet of storage space is available. The three types, small, medium, and large, take up, respectively, 2, 2, and 4 sales hours of labor, and a maximum of 600 hours of labor is available. If the profit made from each of these types is $40, $80, and $100, respectively, how many of each type of television should be sold to maximize profit, and what is the maximum profit?

Exercise 19

A factory manufactures three products, A, B, and C. Each product requires the use of two machines, Machine I and Machine II. The total hours available, respectively, on Machine I and Machine II per month are 180 and 300. The time requirements and profit per unit for each product are listed below.

Table 1
  A B C
Machine I 1 2 2
Machine II 2 2 4
Profit 20 30 40

How many units of each product should be manufactured to maximize profit, and what is the maximum profit?

Exercise 20

A company produces three products, A, B, and C, at its two factories, Factory I and Factory II. Daily production of each factory for each product is listed below.

Table 2
  Factory I Factory II
Product A 10 20
Product B 20 20
Product C 20 10

The company must produce at least 1000 units of product A, 1600 units of B, and 700 units of C. If the cost of operating Factory I is $4,000 per day and the cost of operating Factory II is $5000, how many days should each factory operate to complete the order at a minimum cost, and what is the minimum cost?

Exercise 21

For his classes, Professor Wright gives three types of quizzes, objective, recall, and recall-plus. To keep his students on their toes, he has decided to give at least 20 quizzes next quarter. The three types, objective, recall, and recall-plus quizzes, require the students to spend, respectively, 10 minutes, 30 minutes, and 60 minutes for preparation, and Professor Wright would like them to spend at least 12 hours(720 minutes) preparing for these quizzes above and beyond the normal study time. An average score on an objective quiz is 5, on a recall type 6, and on a recall-plus 7, and Dr. Wright would like the students to score at least 130 points on all quizzes. It takes the professor one minute to grade an objective quiz, 2 minutes to grade a recall type quiz, and 3 minutes to grade a recall-plus quiz. How many of each type should he give in order to minimize his grading time?

Collection Navigation

Content actions

Download:

Collection as:

PDF | EPUB (?)

What is an EPUB file?

EPUB is an electronic book format that can be read on a variety of mobile devices.

Downloading to a reading device

For detailed instructions on how to download this content's EPUB to your specific device, click the "(?)" link.

| More downloads ...

Module as:

PDF | EPUB (?)

What is an EPUB file?

EPUB is an electronic book format that can be read on a variety of mobile devices.

Downloading to a reading device

For detailed instructions on how to download this content's EPUB to your specific device, click the "(?)" link.

| More downloads ...

Add:

Collection to:

My Favorites (?)

'My Favorites' is a special kind of lens which you can use to bookmark modules and collections. 'My Favorites' can only be seen by you, and collections saved in 'My Favorites' can remember the last module you were on. You need an account to use 'My Favorites'.

| A lens I own (?)

Definition of a lens

Lenses

A lens is a custom view of the content in the repository. You can think of it as a fancy kind of list that will let you see content through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

| External bookmarks

Module to:

My Favorites (?)

'My Favorites' is a special kind of lens which you can use to bookmark modules and collections. 'My Favorites' can only be seen by you, and collections saved in 'My Favorites' can remember the last module you were on. You need an account to use 'My Favorites'.

| A lens I own (?)

Definition of a lens

Lenses

A lens is a custom view of the content in the repository. You can think of it as a fancy kind of list that will let you see content through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

| External bookmarks

Reuse / Edit:

Reuse or edit collection (?)

Check out and edit

If you have permission to edit this content, using the "Reuse / Edit" action will allow you to check the content out into your Personal Workspace or a shared Workgroup and then make your edits.

Derive a copy

If you don't have permission to edit the content, you can still use "Reuse / Edit" to adapt the content by creating a derived copy of it and then editing and publishing the copy.

| Reuse or edit module (?)

Check out and edit

If you have permission to edit this content, using the "Reuse / Edit" action will allow you to check the content out into your Personal Workspace or a shared Workgroup and then make your edits.

Derive a copy

If you don't have permission to edit the content, you can still use "Reuse / Edit" to adapt the content by creating a derived copy of it and then editing and publishing the copy.