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Solver is a Microsoft Excel add-in program you can use for optimization in what-if analysis.

According to O'Brien and Marakas, optimization analysis is a more complex extension of goal-seeking analysis. Instead of setting a specific target value for a variable, the goal is to find the optimum value for one or more target variables, under certain constraints. Then, one or more other variables are changed repeatedly, subject to the specified constraints, until you discover the best values for the target variables.

In Excel, you can use Solver to find an optimal value (maximum or minimum, or a certain value) for a formula in one cell called the objective cell, subject to certain constraints or limits, on the values of other formula cells on the worksheet.

This means that the Solver works with a group of cells called decision variables that are used in computing the formulas in the objective and constraint cells. Solver adjusts the values in the decision variable cells to satisfy the limits on constraint cells and produce the result you want for the objective cell.

You can use Solver to find optimal solutions for diverse problems such as −

Determining the monthly product mix for a drug manufacturing unit that maximizes the profitability.

Scheduling workforce in an organization.

Solving transportation problems.

Financial planning and budgeting.

Activating Solver Add-in

Before you proceed with finding solution for a problem with Solver, ensure that the Solver Add-in is activated in Excel as follows −

Click the DATA tab on the Ribbon. The Solver command should appear in the Analysis group as shown below.

In case you do not find the Solver command, activate it as follows −

Click the FILE tab.

Click Options in the left pane. Excel Options dialog box appears.

Click Add-Ins in the left pane.

Select Excel Add-Ins in the Manage box and click Go.

The Add-Ins dialog box appears. Check Solver Add-in and click Ok. Now, you should be able to find the Solver command on the Ribbon under the DATA tab.

Solving Methods used by Solver

You can choose one of the following three solving methods that Excel Solver supports, based on the type of problem −

LP Simplex

Used for linear problems. A Solver model is linear under the following conditions −

The target cell is computed by adding together the terms of the (changing cell)&ast;(constant) form.

Each constraint satisfies the linear model requirement. This means that each constraint is evaluated by adding together the terms of the (changing cell)&ast;(constant) form and comparing the sums to a constant.

Generalized Reduced Gradient (GRG) Nonlinear

Used for smooth nonlinear problems. If your target cell, any of your constraints, or both contain references to changing cells that are not of the (changing cell)&ast;(constant) form, you have a nonlinear model.

Evolutionary

Used for smooth nonlinear problems. If your target cell, any of your constraints, or both contain references to changing cells that are not of the (changing cell)&ast;(constant) form, you have a nonlinear model.

Understanding Solver Evaluation

The Solver requires the following parameters −

Decision Variable Cells

Constraint Cells

Objective Cells

Solving Method

Solver evaluation is based on the following −

The values in the decision variable cells are restricted by the values in the constraint cells.

The calculation of the value in the objective cell includes the values in the decision variable cells.

Solver uses the chosen Solving Method to result in the optimal value in the objective cell.

Defining a Problem

Suppose you are analyzing the profits made by a company that manufactures and sells a certain product. You are asked to find the amount that can be spent on advertising in the next two quarters subject to a maximum of 20,000. The level of advertising in each quarter affects the following −

The number of units sold, indirectly determining the amount of sales revenue.

The associated expenses, and

The profit.

You can proceed to define the problem as −

Find Unit Cost.

Find the advertising cost per Unit.

Find Unit Price.

Next, set the cells for the required calculations as given below.

As you can observe, the calculations are done for Quarter1 and Quarter2 that are in consideration are −

No. of units available for sale in Quarter1 is 400 and in Quarter2 is 600 (cells - C7 and D7).

The initial values for advertising budget are set as 10000 per Quarter (Cells - C8 and D8).

No. of units sold is dependent on the advertising cost per unit and hence is budget for the quarter / Adv. Cost per unit. Note that we have used the Min function to take care to see that the no. of units sold in <= no. of units available. (Cells - C9 and D9).

Revenue is calculated as Unit Price &ast; No. of Units sold (Cells - C10 and D10).

Expenses is calculated as Unit Cost &ast; No. of Units Available &plus; Adv. Cost for that quarter (Cells - C11 and D12).

Profit is Revenue - Expenses (Cells C12 and D12).

Total Profit is Profit in Quarter1 &plus; Profit in Quarter2 (Cell - D3).

Next, you can set the parameters for Solver as given below −

As you can observe, the parameters for Solver are −

Objective cell is D3 that contains Total Profit, which you want to maximize.

Decision Variable cells are C8 and D8 that contain the budgets for the two quarters - Quarter1 and Quarter2.

There are three Constraint cells - C14, C15 and C16.

Cell C14 that contains total budget is to set the constraint of 20000 (cell D14).

Cell C15 that contains the no. of units sold in Quarter1 is to set the constraint of <= no. of units available in Quarter1 (cell D15).

Cell C16 that contains the no. of units sold in Quarter2 is to set the constraint of <= no. of units available in Quarter2 (cell D16).

Solving the Problem

The next step is to use Solver to find the solution as follows −

Step 1 − Go to DATA > Analysis > Solver on the Ribbon. The Solver Parameters dialog box appears.

Step 2 − In the Set Objective box, select the cell D3.

Step 3 − Select Max.

Step 4 − Select range C8:D8 in the By Changing Variable Cells box.

Step 5 − Next, click the Add button to add the three constraints that you have identified.

Step 6 − The Add Constraint dialog box appears. Set the constraint for total budget as given below and click Add.

Step 7 − Set the constraint for total no. of units sold in Quarter1 as given below and click Add.

Step 8 − Set the constraint for total no. of units sold in Quarter2 as given below and click OK.

The Solver Parameters dialog box appears with the three constraints added in box -Subject to the Constraints.

Step 9 − In the Select a Solving Method box, select Simplex LP.

Step 10 − Click the Solve button. The Solver Results dialog box appears. Select Keep Solver Solution and click OK.

The results will appear in your worksheet.

As you can observe, the optimal solution that produces maximum total profit, subject to the given constraints, is found to be the following −

Total Profit - 30000.

Adv. Budget for Quarter1 - 8000.

Adv. Budget for Quarter2 - 12000.

Stepping through Solver Trial Solutions

You can step through the Solver trial solutions, looking at the iteration results.

Step 1 − Click the Options button in the Solver Parameters dialog box.

The Options dialog box appears.

Step 2 − Select the Show Iteration Results box and click OK.

Step 3 − The Solver Parameters dialog box appears. Click Solve.

Step 4 − The Show Trial Solution dialog box appears, displaying the message - Solver paused, current solution values displayed on worksheet.

As you can observe, the current iteration values are displayed in your working cells. You can either stop the Solver accepting the current results or continue with the Solver from finding solution in further steps.

Step 5 − Click Continue.

The Show Trial Solution dialog box appears at every step and finally after the optimal solution is found, Solver Results dialog box appears. Your worksheet is updated at every step, finally showing the result values.

Saving Solver Selections

You have the following saving options for the problems that you solve with Solver −

You can save the last selections in the Solver Parameters dialog box with a worksheet by saving the workbook.

Each worksheet in a workbook can have its own Solver selections, and all of them will be saved when you save the workbook.

You can also define more than one problem in a worksheet, each with its own Solver selections. In such a case, you can load and save problems individually with the Load/Save in the Solver Parameters dialog box.

Click the Load/Save button. The Load/Save dialog box appears.

To save a problem model, enter the reference for the first cell of a vertical range of empty cells in which you want to place the problem model. Click Save.

# data[].attributes.attachment_link.description
Solver is a Microsoft Excel add-in program you can use for optimization in what-if analysis. According to O'Brien and Marakas, optimization analysis is a more complex extension of goal-seeking analysis. Instead of setting a specific target value for a variable, the goal is to find the optimum value for one or more target variables, under certain constraints.

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Leave a comment stating a point or two. Compulsory tau.

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Inside the Mind of a Master Procrastinator | Tim Urban | TED

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I'll be using this medium to:
1. Upload notes/assignments/tutorial (alternative to UiTM MOOC)
2. Receive student's assignments
3. Communicate (alternative to Whatsapp) to students

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Age: 40
Asal: Muar, JDT
Status: Married with 3 children
Passion:
Enjoys new method of teaching and hope you guys too!
Website:
https://sitirafidah660.wixsite.com/rafidah-portfolio

Area of Expertise:
Process System Engineering  - Process Control, Process Design, Process Integration

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1. Create a GOOGLE account/gmail account (if you don't have any).
2. Go to PADLET website.
3. Sign in to PADLET using GOOGLE Account.
4. Join a PADLET and copy this link.
https://padlet.com/sitirafidah660/CGE697_20204

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Date: 17 - 29/5/2021
Coverage:
1. Optimisation Basics
2. Unconstrained Optimisation -Bracketing & Newton method

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https://drive.google.com/open?id=1eOngXP3nlygR2cpIyoPYIEXHz_cODb_a

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June 2014

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Notes given is in our syllabus. The method to solve NLP that is in our coverage is Least Square Method.

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Instruction:
1. Divide yourselves into 6 groups and each group must register your group by posting the group name and members below this post.
2. Answer this assignment and submit it within 2 weeks from now.
3. Any plagiarism will be penalised.

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https://kahoot.it/challenge/03551782?challenge-id=0d544778-9447-4468-99ac-6194477d1317_1617609586574

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1. Lecture 1 : Week 1 - Week 7 (29/3 - 9/5)
2. Mid term break: 10/5 - 16/5
3. Lecture 2: Week 8 - Week 14 (7/12 - 24/1/21)
4. MTA: Week 7 - 8 (17 - 29/5)
5. Cuti Perayaan: 30/5 - 6/6
6. Cuti Ulangkaji: 17 - 21/7
7. Final Assessment - 22/7 - 12/8

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1. Introduce yourself in the next column by stating your name, origin (asal) & passion.
2. Do post your pic ya!
3. Share the video resume link (the assignment given in MS Teams) in your posts. This is because, your friends cant watched the video resume in MS Teams.

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Assignment - LP (Graphical & MS Excel Programming)

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Assignment - LP (Graphical & MS Excel Programming)

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Due: 11/7/2021 (Sunday)

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Group Assignment - LP graphical & MS Excel

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Modelling and Optimisation of Oil and Gas Production Systems

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Modelling and Optimisation of Oil and Gas Production Systems

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https://drive.google.com/open?id=1RmZ4FEz_oLUy8SOk3Xn43RPm_aCFJbCl

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Chap 2 - Fundamentals of Unconstrained Optimization.pdf

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June 2015

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Dynamic Oil & Gas Production Systems Optimization via Explicit Reservoir & Well Multiphase Flow Simulation

# data[].attributes.subject
Dynamic Oil & Gas Production Systems Optimization via Explicit Reservoir & Well Multiphase Flow Simulation

# data[].attributes.body
https://drive.google.com/open?id=1WghZqo6fK23QBrHgCN9VRdCHhmwLzaO9

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Matrix addition, multiplication, inversion, determinant and rank calculation, transposing, bringing to diagonal, row echelon form, exponentiation, LU Decomposition, QR-decomposition, Singular Value Decomposition (SVD), solving of systems of linear equations with solution steps

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Dec 2015

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PLANNING AND SCHEDULING of Petroleum Industries

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https://drive.google.com/open?id=13R-e94fkT8qqGyOV-jxXcQUAmzrBueJr

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Development and Applications of Production Optimization Techniques For Petroleum Fields

# data[].attributes.subject
Development and Applications of Production Optimization Techniques For Petroleum Fields

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https://drive.google.com/open?id=1RHyVApWeWi87quDY1VM5oExvQdEbNJwN

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Chap 13 - Linear Programming-The Simplex Method.pdf

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Chap 14 - Linear Programming- Interior-Point Methods.pdf

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Petroleum Production Optimization - Oil&Gas Portal

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AGE : 23
ORIGIN : TERENGGANU
PASSION : STILL SEARCHING AND TRYING : )
RESUME LINK : https://youtu.be/9xAdpTbFFHM

# data[].attributes.body
AGE: 23
ORIGIN: KLANG, SELANGOR
PASSION: NATURE LOVER AND LOVE TO EXPLORE NEW GREEN TECHNNOLOGY

Video Resume link:
https://youtu.be/JTVRBBAl8Lw

# data[].attributes.body
AGE: 23
KAJANG, SELANGOR
PASSION: ADVENTUROUS

DAILY CASUAL GAMER (with verified high skills level hopefully)

VIDEO RESUME LINK:
https://youtu.be/jfwRqtK_rzA

# data[].attributes.body
AGE: 27
ORIGIN: KUCHING, SARAWAK
PASSION: SURFING THE INTERNET AND FOOD HUNTING
VIDEO RESUME LINK: https://youtu.be/dtY-q3FxDdc

# data[].attributes.body
AGE: 23 YEARS OLD
BASED IN KUALA LUMPUR
PASSION: A COFFEE LOVER & LOVE TO EXPLORE THE COFFEE WORLD
RESUME VIDEO: https://drive.google.com/file/d/1jd9XcFhFA-Z556VzQAgjfjDpsbN_Kz4y/view?usp=sharing

Nice to meet you Madam 🥰

# data[].attributes.body
Age: 23
Telok Panglima Garang, Selangor
Passion: Love, Playing Futsal, FIFA & Mobile Games.
Video Resume Link: https://youtu.be/H0wJILP7rIc

# data[].attributes.body
Age: 23
Jempol, Negeri Sembilan
Passion: Family Lover, Outdoor Activities
Video Resume Link: https://drive.google.com/file/d/1dmc_CMk90NxffJSUOulR92VlLltbX9b6/view?usp=sharing

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Age: 23
Origin: Bukit Beruang, Melaka
Passion: Rugby and Powerlifter
Resume Video: https://youtu.be/AM6mhtNXykE

# data[].attributes.body
Age: 26
Origin: Pendang, Kedah
Passion: Game, Family Lover, football
Resume Video:
https://www.youtube.com/watch?v=mVy3boNEMsk

# data[].attributes.body
Age: 23
Origin: Sabah
Passion: Gaming, Basketball, Editting Videos.
Resume Video:
https://www.youtube.com/watch?v=eCJtx6cpasU

# data[].attributes.body
Age:23
Origin: Johor Bharu
Passion: Weeb, Game and Watching Horror/Thriller/Crime Movies
Resume Link:https://drive.google.com/file/d/1Ct821SBgFLUKte0IDnKQlgxm4GYG8FiH/view?usp=sharing

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Age: 23
Pasir Mas, Kelantan
Passion: Love taking pictures and travelling

Here’s the link to my resume’s video
https://youtu.be/S9Pk-XtzGsw

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Age: 23
Origin: Kulai, Johor
Passion: Arts, Journal, Poetry, Photography, Music
Video Resume:
https://youtu.be/iQeC-gxKPpA

# data[].attributes.body
Age: 26
Origin: Puchong, Selangor
Passion: Hiking, Running, Travel, Adventure
Video Resume: https://youtu.be/ma7QfONw5zU

# data[].attributes.body
Age: 23
Origin: Kuala Lumpur
Passion: Read novel, skipping and casual gamer.
Video resume: https://drive.google.com/file/d/1XuZq6r4ONVuarzfaj7kyQOBku1LZ-FQU/view?usp=sharing

# data[].attributes.body
Age: 23
Origin: Negeri Sembilan
Passion: Baking, Gardening, Binge on Netflix
Resume Link:https://youtu.be/A1cEB_SnPdI

# data[].attributes.body
Age: 23
Origin: Klang, Selangor
Passion: Volleyball, Badminton, anime, gaming
video resume : https://youtu.be/TrVornApd60

# data[].attributes.body
Age: 23
Origin: Bachok, Kelantan
Passion: Learning Languages and Monster Hunting
Video Resume: https://youtu.be/SHkPh_LOSSw

# data[].attributes.body
AGE : 23
ORIGIN : KEDAH
PASSION : MOTION PICTURES
RESUME LINK : https://drive.google.com/file/d/1Z58UiE3Dmo_JbHhRVjxoA2ZFcvYDNZ_g/view?usp=drivesdk

# data[].attributes.body
Age: 23
Origin: Changlun, Kedah
Passion: Agriculturist, Football, futsal
video resume: https://youtu.be/iRXQwYtLf3o

# data[].attributes.body
Age:23
Origin: Sungai Buloh, Selangor
Passion: Playing video games, reading novels, Binge watching television series
Vid Resume:
https://youtu.be/9w6u14hv630

# data[].attributes.body
AGE : 23
ORIGIN : AMPANG, SELANGOR
STATUS : SINGLE BUT NOT AVAILABLE
PASSION : ANYTHING THAT MAKE ME HAPPY AND ENJOYABLE
VIDEO RESUME LINK:
https://youtu.be/GAP0bv_Keiw

# data[].attributes.body
Age: 23
Origin: Johor Darul Takzim
Passion: Cooking/baking/loves Harry Potter movies
Video Resume:
https://drive.google.com/file/d/1THJJV1dFirc0X2L4Iz2pQZB13t6n2iZP/view?usp=drivesdk

# data[].attributes.body
Age: 23
Origin: Kelantan
Passion: Art and Drawing, Indoor Planting, Cooking
Video Resume:
https://youtu.be/UTb7IC1hyOE

# data[].attributes.body
Age: 23 years old
Origin: Kelantan
Passion: Baking and reading (sometimes)
Resume Link: https://youtu.be/RKYA1ta219s

# data[].attributes.body
Age : 23 years old
Origin : Na na na na na Terengganu kite
Passion : Animals, Cooking, Swimming, Playing Games, Watching Movies and Helping Peoples
Video resume link : https://youtu.be/xuH6vMnZ-NA

# data[].attributes.body
Age: 23 years old
Origin: Petaling Jaya, Selangor
Passion: Still looking but I love to hear people's opinions about life and love.
Video resume's link: https://youtu.be/Fp1zaQdvFC0

# data[].attributes.body
Age: 23 years old
Origin: Pasir gudang, johor
Passion: currently playing online games and baking cause i love to eat 🥰
Video resume : https://youtu.be/7OUL8bxCngc

# data[].attributes.body
Age : 23
Origin : Kota Bharu, Kelantan
Passion : Active in sports and love watching motivational videos.
Video resume :
https://youtu.be/QpGkBNKrPTg

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1. Muhammad Amiruddin Bin Mohd Akhyauddin (2017466112)
2.Mohd Hazwan Bin Khuirauni (2017466068)
3.Muhammad Najmi bin Mualif (2017466136)
4.Muhamad Khairudin Bin Zulkeply (2017466074)
5.Muhammad Syahmi bin Azmi (2017466114)

# data[].attributes.body
1. AJLA IZZATI BT SHAHANIZAM (2017466104)
2. ANIRA NAFIZA BT CHE ABDUL RAHMAN (2017466072)
3. HAFIDZ AFFENDI BIN HENRY (2017466126)
4. MUHAMAD HABIBULLAH BIN MD ASRI (2017798971)
5. NUR ROZALIA BINTI AHMAD ROMZI (2017466096)
6. WAN MUHAMMAD AZREEN BIN WAN ZAIDEL (2017557575)

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1. MUHAMAD NOR AZMI BIN MOHD AZLI
(2017466058)
2. SOFEA JASMEEN BINTI JOHARI (2017466106)
3. MUHAMMAD SYAZWAN HAZIQ BIN HASHIM (2017466078)
4. KAMIL HAFIZUDIN BIN KAMAL AZAM (2017466124)
5. NABILAH BINTI ABDUL RAZAK (2017466088)

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GROUP 4
1. ABDUL HALIM ASMUNGI (2017785897)
2. NORSABRINA BINTI MAT YUSOF (2017466108)
3. SERIADISHAHANA BINTI MASROLL SHAH (2017466098)
4. SITI ZAKIAH BINTI MUSTAFFA KAMAL (2017466132)
5. SOFYAH ANIS IZWANI BINTI JUSOF (2017466052)

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1. Johan Aliff Bin Wan Ajhar (2017466056)
2. Muhammad Addin Bin Md Fauzi (2017466116)
3. Mohamad Aiman Bin Amer(2017466092)
4. Muhammad Afnan Bin Che Zawawi (2017466082)
5. Mohamad NurZikri Bin Samion (2017466062)

# data[].attributes.body
1. AINUN SOLIHAH BINTI ZAINAL ABIDIN 2017466066
2. NUREEN ILYANA BINTI HAMMIZZUL (2017466118)
3. MUHAMMAD HANIS FIKRI BIN MOHAMAD UZUMAN (2017466094)
4. AMIRAH NAJWA BINTI HAMID (2017466128)
5. MOHAMAD ALIF HAIQAL BIN EZANI (2017466102)
6. SITI NURINA ADLINA BINTI ROSLAN (2017466054)

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FOR FINAL ASSESSMENT

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Petroleum Production Optimization - Oil&Gas Portal

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Petroleum Production Optimization refers to the various activities of measuring, analyzing, modelling, prioritizing and implementing actions to enhance productivity of a field

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Essential Steps

To define an optimization model in Excel you'll follow these essential steps:

1. Organize the data for your problem in the spreadsheet in a logical manner.

2. Choose a spreadsheet cell to hold the value of each decision variable in your model.

3. Create a spreadsheet formula in a cell that calculates the objective function for your model.

4. Create a formulas in cells to calculate the left hand sides of each constraint.

5. Use the dialogs in Excel to tell the Solver about your decision variables, the objective, constraints, and desired bounds on constraints and variables.

6. Run the Solver to find the optimal solution.

Within this overall structure, you have a great deal of flexibility in how you choose cells to hold your model's decision variables and constraints, and which formulas and built-in functions you use. In general, your goal should be to create a spreadsheet that communicates its purpose in a clear and understandable manner.

Creating an Excel Worksheet

Assuming that you have organized the data for the problem in Excel, the next step is to create a worksheet where the formulas for the objective function and the constraints are calculated. Because decision variables and constraints usually come in logical groups, you'll often want to use cell ranges in your spreadsheet to represent them.

In the worksheet below, we have reserved cells B4, C4, D4 and E4 to represent our decision variables X ₁, X ₂, X ₃, and X ₄ representing the number of pallets of each type of panel to produce. The Solver will determine the optimal values for these cells. (Click on the worksheet for a full-size image.)

Notice that the profit for each pallet of panels ($450, $1,150, $800 and $400) was entered in cells B5, C5, D5 and E5, respectively. This allows us to compute the objective in cell F5 as:

Formula for cell F5: =B5*B4+C5*C4+D5*D4+E5*E4

or equivalently,

Formula for cell F5: =SUMPRODUCT(B5:E5,B4:E4)

In cells B8:E11, we've entered the amount of resources needed to produce a pallet of each type of panel. For example, the value 15 in cell C9 means that 15 hours of pressing is required to produce a pallet of Pacific style panels. These numbers come directly from the formulas for the constraints shown earlier. With these values in place, we can enter a formula in cell F8 to compute the total amount of glue used for any number of pallets produced:

Formula for cell F8: =SUMPRODUCT(B8:E8,$B$4:$E$4)

We can copy this formula to cells F9:F11 to compute the total amount of pressing, pine chips, and oaks chips used. (The dollar signs in $B$4:$E$4 specify that this cell range stays constant, while the cell range B8:E8 becomes B9:E9, B10:E10, and B11:E11 in the copied formulas.) The formulas in cells F8:F11 correspond to the left hand side values of the constraints.

In cells G8:G11, we've entered the available amount of each type of resource (corresponding to the right hand side values of the constraints). This allows us to express the constraints shown earlier as:

F8:F11<=G8:G11

This is equivalent to the four constraints: F8<=G8, F9<=G9, F10<=G10, and F11<=G11. We can enter this set of constraints directly in the Solver dialogs along with the non-negativity conditions:

B4:E4 >= 0

Click on the links below to see how this model can be solved using Excel's built-in Solver (or Premium Solver) or with FrontLine Systems' flagship Risk Solver Platform product.

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Excel Solver Tutorial - Step by Step Product Mix Example In Excel

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Essential Steps To define an optimization model in Excel you'll follow these essential steps: Organize the data for your problem in the spreadsheet in a logical manner. Choose a spreadsheet cell to hold the value of each decision variable in your model. Create a spreadsheet formula in a cell that calculates the objective function for your model.