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Transcript of Introduction to Linear Programming Chapter 3: Hillier and Lieberman Chapter 3: Decision Tools for...
![Page 1: Introduction to Linear Programming Chapter 3: Hillier and Lieberman Chapter 3: Decision Tools for Agribusiness Dr. Hurley’s AGB 328 Course.](https://reader033.fdocuments.us/reader033/viewer/2022061517/56649e4a5503460f94b3e62d/html5/thumbnails/1.jpg)
Introduction to Linear ProgrammingChapter 3: Hillier and LiebermanChapter 3: Decision Tools for AgribusinessDr. Hurley’s AGB 328 Course
![Page 2: Introduction to Linear Programming Chapter 3: Hillier and Lieberman Chapter 3: Decision Tools for Agribusiness Dr. Hurley’s AGB 328 Course.](https://reader033.fdocuments.us/reader033/viewer/2022061517/56649e4a5503460f94b3e62d/html5/thumbnails/2.jpg)
Terms to KnowSimplex Method, Feasible Region,
Slope-Intercept Form, Optimal Solution, Graphical Method, Decision Variables, Parameters, Objective Function, Constraints, Functional Constraints, Non-Negativity Constraints, Feasible Solution, Infeasible Solution, Feasible Region
![Page 3: Introduction to Linear Programming Chapter 3: Hillier and Lieberman Chapter 3: Decision Tools for Agribusiness Dr. Hurley’s AGB 328 Course.](https://reader033.fdocuments.us/reader033/viewer/2022061517/56649e4a5503460f94b3e62d/html5/thumbnails/3.jpg)
Terms to Know Cont.No Feasible Solution, Optimal
Solution, Most Favorable Value, Multiple Optimal Solutions, No Optimal Solutions, Unbounded Z, Corner-Point Feasible Solution (CPF), Blending Problem, Data Cells, Range Name, Changing Cells, Output Cells, Target Cell
![Page 4: Introduction to Linear Programming Chapter 3: Hillier and Lieberman Chapter 3: Decision Tools for Agribusiness Dr. Hurley’s AGB 328 Course.](https://reader033.fdocuments.us/reader033/viewer/2022061517/56649e4a5503460f94b3e62d/html5/thumbnails/4.jpg)
Wyndor Glass Co. ExampleCompany has two new products
—a door and a windowThe company has three plants to
develop these two new productsThe goal of the company is to
maximize profits
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Key Data for Wyndor Doors Window
sTime Available Hours
Plant 1 Usage (Hours)
1 0 4
Plant 2 Usage (Hours)
0 2 12
Plant 3 Usage (Hours)
3 2 18
Unit Profit $3,000 $5,000
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Mathematical ModelLet x1 = number of doors produced per
weekLet x2 = number of windows produced
per weekLet Z = profit per week
Subject to:
2
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Graphical Solution
x2
0 6
9
6
4
Z=3x1+5x2=36
3x1+2x2=18
2x2=12
x1
x1=4
Z=3x1+5x2=20
Z=3x1+5x2=10
![Page 8: Introduction to Linear Programming Chapter 3: Hillier and Lieberman Chapter 3: Decision Tools for Agribusiness Dr. Hurley’s AGB 328 Course.](https://reader033.fdocuments.us/reader033/viewer/2022061517/56649e4a5503460f94b3e62d/html5/thumbnails/8.jpg)
The General Linear Programming ModelZ = measure of performancexj = a decision variable that indicates how
much you are doing of activity j for j = 1, 2, …, n
cj = a parameter that converts activity j into the overall measure of performance
bi = the amount of resource i you have available to allocate to your different activities for i = 1, 2, …, m
aij = a parameter that converts activity j into the amount of resource i used
![Page 9: Introduction to Linear Programming Chapter 3: Hillier and Lieberman Chapter 3: Decision Tools for Agribusiness Dr. Hurley’s AGB 328 Course.](https://reader033.fdocuments.us/reader033/viewer/2022061517/56649e4a5503460f94b3e62d/html5/thumbnails/9.jpg)
Resource Allocation Data Matrix
Activity 1
Activity 2
… Activity n
Resource Available
Resource 1 a11 a12 … a1n b1
Resource 2 a21 a22 … a2n b2
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Resource m am1 am2 … amn bm
Contribution to Z
c1 c2 … cn
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Standard Mathematical Form
Subject to: . .
, …,
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Changes that Can Be Made to the Standard Form The objective function could be
minimized instead of maximizedThe functional constraints can be
met with equality (=) or greater than (≥) signs
The decision variables xj could be unrestricted in sign, i.e., xj < 0 is also possible
![Page 12: Introduction to Linear Programming Chapter 3: Hillier and Lieberman Chapter 3: Decision Tools for Agribusiness Dr. Hurley’s AGB 328 Course.](https://reader033.fdocuments.us/reader033/viewer/2022061517/56649e4a5503460f94b3e62d/html5/thumbnails/12.jpg)
Major Assumptions Behind Linear ProgrammingAll functions are linearProportionality AssumptionAdditivityDivisibilityCertainty
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Solving Linear Programming Problems Using a SpreadsheetExcel has an add-in called Solver that
can solve linear programming problems.
Major components to Solver are:◦Set Objective:◦To:◦By Changing Variable Cells:◦Subject to the Constraints:◦Make Unconstrained Variables Non-
negative should be checked◦Select a Solving Method:
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Guidelines for Building Good SpreadsheetsEnter the data first
◦Since the data can dictate the structure of the spreadsheet model, it is valuable to input the data in the spreadsheet first.
◦This can also allow you to build the spreadsheet to closely resemble the structure of the data.
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Guidelines for Building Good Spreadsheets Cont.Organize and clearly identify the
data◦Data should be grouped together in
a convenient format.◦Each piece of data or group of data
should be appropriately labeled.Enter each piece of data into one
cell only◦If you need to use the data
elsewhere in the model, you can reference it.
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Guidelines for Building Good Spreadsheets Cont.Separate data from formulas
◦If possible, formulas should have no specific parameters encoded in them.
◦By keeping the data separate from formulas, you can save time when changes are needed by only having to change one parameter rather than looking for all the formulas that use a specific piece of data.
◦This allows all the data to be visual in the spreadsheet.
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Guidelines for Building Good Spreadsheets Cont.Keep it simple
◦ You should avoid more powerful functions when simpler ones will accomplish the same task.
◦ Keep formulas simple. If you have a very complicated formula, you
should break it up into components on the spreadsheet.
Use range names◦ Range names should be indicative of what
they represent.◦ When using range names, care should be
taken not to allow too many range names so the names become unwieldy.
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Guidelines for Building Good Spreadsheets Cont.Use relative and absolute
references to simplify copying formulas◦This also allows you to copy cells
without making as many errors.Use borders, shading, and colors
to distinguish between cell types◦This will make it easy for you to keep
track of the items within your spreadsheet model.
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Guidelines for Building Good Spreadsheets Cont.Show the entire model on the
spreadsheet◦You should attempt to put as many
of the elements of the model on the spreadsheet. This will allow others to more easily
understand your model. This will allow people using the
spreadsheet to more easily understand the Solver dialog box.
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Review the Following Spreadsheet ModelsWyndor GlassRadiation TherapyKibbutzimNori and LeetsSave-ItUnion AirwaysDistribution Unlimited
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Example3.1-10 in the textbook
◦Develop a mathematical model◦Solve the problem using the
graphical method◦Solve the problem using excel by
developing a spreadsheet model
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In-Class Activity (Not Graded)Solve the following using the
graphical method and the spreadsheet method:
Subject to: