## Main.OptimizationBasics History

June 21, 2020, at 04:44 AM by 136.36.211.159 -
Deleted lines 64-82:

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April 24, 2017, at 04:24 PM by 10.5.113.121 -

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January 11, 2013, at 02:30 PM by 69.169.188.188 -
Changed line 51 from:
• What resources (at least 3) did you find particularly useful or informative as you reviewed the tutorials, documentation, videos, or other online material?
to:
• What resources (at least 3) did you find particularly useful or informative as you reviewed the tutorials, documentation, videos, or other online material? Please enter any that you'd like to share below in the comments section.
January 11, 2013, at 02:19 PM by 69.169.188.188 -
Changed line 37 from:
• Review information on optimization platforms such as (2 or 3 is fine):
to:
• Review information on optimization platforms (2 or 3 is fine) such as:
January 11, 2013, at 02:12 PM by 69.169.188.188 -
Changed line 7 from:
1. Complete the information sheet to tell me a little more about your background and interests
to:
• Complete the information sheet to tell me a little more about your background and interests
Changed lines 9-25 from:
1. Think of an optimization problem. Define the following for this optimization problem of your choice:
1. Objective
2. Analysis variables (Parameters)
3. Design variables (Variables)
4. Equality constraints
5. Inequality constraints
6. Continuous variables
7. Discrete variables
2. Optimizers sometimes report that the optimization problem is infeasible. What does infeasible mean and how can it generally be corrected?
3. Give the general form of the following types of problems and list at least one method that is used to solve them.
1. Linear programming (LP)
3. Nonlinear programming (NLP)
4. Mixed integer linear programming (MILP)
5. Mixed integer nonlinear programming (MINLP)
to:
• Think of an optimization problem. Define the following for this optimization problem of your choice:
• Objective
• Analysis variables (Parameters)
• Design variables (Variables)
• Equality constraints
• Inequality constraints
• Continuous variables
• Discrete variables
• Optimizers sometimes report that the optimization problem is infeasible. What does infeasible mean and how can it generally be corrected?
• Give the general form of the following types of problems and list at least one method that is used to solve them.
• Linear programming (LP)
• Nonlinear programming (NLP)
• Mixed integer linear programming (MILP)
• Mixed integer nonlinear programming (MINLP)
Changed lines 28-51 from:
1. Define the following and tell how it is relevant to optimization:
1. Equation residuals
2. Global (vs. local) optimization techniques
3. Lagrange multiplier
4. Jacobian matrix
5. Hessian matrix
6. Sensitivity analysis
7. Optimization under uncertainty
2. Review information on optimization platforms such as (2 or 3 is fine):
1. AIMMS
2. AMPL
3. APMonitor
4. Frontline Excel Solver
5. GAMS
6. MATLAB Optimization Toolbox
7. OptdesX - see OptdesX section
8. Python Optimization Packages
9. Additional tutorials available for the Two Bar Truss Problem
3. What optimization software tutorials did you review?
4. What resources (at least 3) did you find particularly useful or informative as you reviewed the tutorials, documentation, videos, or other online material?
to:
• Define the following and tell how it is relevant to optimization:
• Equation residuals
• Global (vs. local) optimization techniques
• Lagrange multiplier
• Jacobian matrix
• Hessian matrix
• Sensitivity analysis
• Optimization under uncertainty
• Review information on optimization platforms such as (2 or 3 is fine):
• AIMMS
• AMPL
• APMonitor
• Frontline Excel Solver
• GAMS
• MATLAB Optimization Toolbox
• OptdesX - see OptdesX section
• Python Optimization Packages
• Additional tutorials available for the Two Bar Truss Problem
• What optimization software tutorials did you review?
• What resources (at least 3) did you find particularly useful or informative as you reviewed the tutorials, documentation, videos, or other online material?
January 11, 2013, at 02:06 PM by 69.169.188.188 -
January 11, 2013, at 02:05 PM by 69.169.188.188 -

January 11, 2013, at 02:05 PM by 69.169.188.188 -
Changed lines 60-77 from:

This assignment can be completed as a collaborative assignment. Additional guidelines on individual, collaborative, and group assignments are provided under the Expectations link.

to:

This assignment can be completed as a collaborative assignment. Additional guidelines on individual, collaborative, and group assignments are provided under the Expectations link.

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January 11, 2013, at 05:49 AM by 69.169.188.188 -
Changed line 37 from:
1. Review information on optimization platforms such as:
to:
1. Review information on optimization platforms such as (2 or 3 is fine):
January 10, 2013, at 07:10 AM by 69.169.188.188 -
Changed line 26 from:
Example problems for each can be solved at the following links by selecting the run button (green arrow) and viewing the results in the window below.
to:
Example problems for each can be solved by clicking on the links and selecting the run button (green arrow). The solution appears in the window below the model file by selecting the results table icon.
January 10, 2013, at 07:09 AM by 69.169.188.188 -
Changed line 26 from:

Example problems for each can be solved at the following links by selecting the run button (green arrow) and viewing the results in the window below.

to:
Example problems for each can be solved at the following links by selecting the run button (green arrow) and viewing the results in the window below.
January 10, 2013, at 07:09 AM by 69.169.188.188 -

Example problems for each can be solved at the following links by selecting the run button (green arrow) and viewing the results in the window below.

January 10, 2013, at 07:07 AM by 69.169.188.188 -
Changed lines 29-34 from:
1. Global (vs. local) optimization techniques
2. Lagrange multiplier
3. Jacobian matrix
4. Hessian matrix
5. Sensitivity analysis
6. Optimization under uncertainty
to:
1. Global (vs. local) optimization techniques
2. Lagrange multiplier
3. Jacobian matrix
4. Hessian matrix
5. Sensitivity analysis
6. Optimization under uncertainty
January 10, 2013, at 07:04 AM by 69.169.188.188 -
Changed lines 21-25 from:
1. Linear programming (LP)
3. Nonlinear programming (NLP)
4. Mixed integer linear programming (MILP)
5. Mixed integer nonlinear programming (MINLP)
to:
1. Linear programming (LP)
3. Nonlinear programming (NLP)
4. Mixed integer linear programming (MILP)
5. Mixed integer nonlinear programming (MINLP)
January 08, 2013, at 04:00 PM by 128.187.97.21 -
Changed line 46 from:
1. Additional tutorial available under the next homework assignment for the Two Bar Truss
to:
1. Additional tutorials available for the Two Bar Truss Problem
January 08, 2013, at 03:59 PM by 128.187.97.21 -
1. Additional tutorial available under the next homework assignment for the Two Bar Truss
January 07, 2013, at 01:30 PM by 69.169.188.188 -
Changed lines 9-10 from:
1. Define the following for an optimization problem of your choice:
to:
1. Think of an optimization problem. Define the following for this optimization problem of your choice:
1. Objective
January 07, 2013, at 01:10 PM by 69.169.188.188 -
January 07, 2013, at 01:10 PM by 69.169.188.188 -
Changed line 7 from:
1. Complete the [Main/InfoSheet | information sheet] to tell me a little more about your background and interests
to:
1. Complete the information sheet to tell me a little more about your background and interests
January 07, 2013, at 01:09 PM by 69.169.188.188 -
January 07, 2013, at 01:09 PM by 69.169.188.188 -
1. Complete the [Main/InfoSheet | information sheet] to tell me a little more about your background and interests
Changed line 35 from:
1. Review tutorials on optimization platforms such as:
to:
1. Review information on optimization platforms such as:
Deleted lines 43-44:
1. How much time did you spend reviewing tutorials? _________ Hours
January 04, 2013, at 06:02 AM by 69.169.188.188 -
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#### Optimization Basics

Review tutorials on optimization platforms such as:

• AIMMS
• AMPL
• APMonitor
• Frontline Excel Solver
• GAMS
• MATLAB Optimization Toolbox
• OptdesX - see OptdesX section
• Python Optimization Packages

Once you have done this, answer the following questions.

1. Define the following types of parameters, variables, and equations
1. Analysis variables
2. Design variables
to:

### Optimization Basics

1. Define the following for an optimization problem of your choice:
1. Analysis variables (Parameters)
2. Design variables (Variables)
1. Review tutorials on optimization platforms such as:
1. AIMMS
2. AMPL
3. APMonitor
4. Frontline Excel Solver
5. GAMS
6. MATLAB Optimization Toolbox
7. OptdesX - see OptdesX section
8. Python Optimization Packages
Changed line 56 from:

This assignment can be completed as a collaborative assignment. Additional guidelines on individual, collaborative, and group assignments are provided under the Expectations link.

to:

This assignment can be completed as a collaborative assignment. Additional guidelines on individual, collaborative, and group assignments are provided under the Expectations link.

January 04, 2013, at 02:37 AM by 69.169.188.188 -
Deleted lines 18-23:
1. How much time did you spend reviewing tutorials? _________ Hours
2. What optimization software tutorials did you review?
3. What resources (at least 3) did you find particularly useful or informative as you reviewed the tutorials, documentation, videos, or other online material?
1. How much time did you spend reviewing tutorials? _________ Hours
2. What optimization software tutorials did you review?
3. What resources (at least 3) did you find particularly useful or informative as you reviewed the tutorials, documentation, videos, or other online material?
December 24, 2012, at 05:00 PM by 69.169.188.188 -
Deleted lines 6-16:

Note: Each of the homework assignments are listed as either:

• Group
• Collaborative:
• Individual:

This assignment can be completed as a collaborative assignment. Additional guidelines on individual, collaborative, and group assignments are provided under the Expectations link.

Changed lines 49-58 from:
1. Optimization under uncertainty
to:
1. Optimization under uncertainty

Note: Each of the homework assignments are listed as either:

• Group
• Collaborative:
• Individual:

This assignment can be completed as a collaborative assignment. Additional guidelines on individual, collaborative, and group assignments are provided under the Expectations link.

December 24, 2012, at 04:58 PM by 69.169.188.188 -
December 22, 2012, at 03:40 PM by 69.169.188.188 -
Changed line 14 from:

This assignment can be completed as a collaborative assignment. Addition guidelines on individual, collaborative, and group assignments are provided under the Expectations link.

to:

This assignment can be completed as a collaborative assignment. Additional guidelines on individual, collaborative, and group assignments are provided under the Expectations link.

December 22, 2012, at 03:40 PM by 69.169.188.188 -
Changed line 9 from:

Note: Each of the assignments are listed as either:

to:

Note: Each of the homework assignments are listed as either:

December 22, 2012, at 03:39 PM by 69.169.188.188 -
Changed lines 14-15 from:

This assignment can be completed as a collaborative assignment.

to:

This assignment can be completed as a collaborative assignment. Addition guidelines on individual, collaborative, and group assignments are provided under the Expectations link.

Changed line 60 from:
1. Optimization under uncertainty
to:
1. Optimization under uncertainty
December 22, 2012, at 03:36 PM by 69.169.188.188 -

Changed line 16 from:

Attach:

to:

December 22, 2012, at 03:35 PM by 69.169.188.188 -

#### Optimization Basics

Note: Each of the assignments are listed as either:

• Group
• Collaborative:
• Individual:

This assignment can be completed as a collaborative assignment.

Attach:

December 22, 2012, at 02:46 PM by 69.169.188.188 -
Changed lines 17-18 from:

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to:
1. How much time did you spend reviewing tutorials? _________ Hours
2. What optimization software tutorials did you review?
3. What resources (at least 3) did you find particularly useful or informative as you reviewed the tutorials, documentation, videos, or other online material?
4. Define the following types of parameters, variables, and equations
1. Analysis variables
2. Design variables
3. Equality constraints
4. Inequality constraints
5. Continuous variables
6. Discrete variables
5. Optimizers sometimes report that the optimization problem is infeasible. What does infeasible mean and how can it generally be corrected?
6. Give the general form of the following types of problems and list at least one method that is used to solve them.
1. Linear programming (LP)
3. Nonlinear programming (NLP)
4. Mixed integer linear programming (MILP)
5. Mixed integer nonlinear programming (MINLP)
7. Define the following and tell how it is relevant to optimization:
1. Equation residuals
2. Global (vs. local) optimization techniques
3. Lagrange multiplier
4. Jacobian matrix
5. Hessian matrix
6. Sensitivity analysis
7. Optimization under uncertainty
December 22, 2012, at 02:31 PM by 69.169.188.188 -
Deleted line 5:
Deleted line 13:
December 22, 2012, at 02:30 PM by 69.169.188.188 -
Changed line 13 from:
• See OptdesX Section
to:
• OptdesX - see OptdesX section
December 22, 2012, at 02:19 PM by 69.169.188.188 -

(:title ME 575 Optimization Basics:) (:keywords nonlinear, optimization, engineering optimization, interior point, active set, differential, algebraic, modeling language, university course:) (:description Introductory assignment on Optimization Techniques in Engineering at Brigham Young University:)

Review tutorials on optimization platforms such as:

• AIMMS
• AMPL
• APMonitor
• Frontline Excel Solver
• GAMS
• MATLAB Optimization Toolbox
• See OptdesX Section
• Python Optimization Packages

Once you have done this, answer the following questions.

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