# 2022 Cornell Optimization Open Textbook Feedback

## Parametric linear programming

• Author list
1. All equations and math symbols should be italicized. Please use latex equations or equation editor to add equations/math symbols throughout the Wiki.
• Theory, methodology, and/or algorithmic discussion
1. Please use equation editor for all math symbols and equations. Refer https://optimization.cbe.cornell.edu/index.php?title=Duality to see how the equations/symbols are typed and aligned.
2. Explain what zj means. It's unclear from the current text.
• At least one numerical example
1. Row matrices should also be in square brackets. Use equation editor to fix these.

## Evolutionary algorithms

• Theory, methodology, and/or algorithmic discussion
1. Several words and phrases are capitalized. Please use the sentence case throughout the wiki.
• References
1. Some resources are inconsistent (missing publishing year, only a link and title, etc)

## Alternating direction method of multipliers

• Theory, methodology, and/or algorithmic discussion
1. Please use equation editor/Latex equations for all math symbols and equations.
2. Many words are capitalized in the text. Please use the sentence case throughout the Wiki.
3. Please use the symbol * as superscript. It should look like x* and y*.

## Sequential linear programming

• Theory, methodology, and/or algorithmic discussion
1. Please include more details of how the SLP problem is formulated at the beginning of the subsection.
• At least one numerical example
1. Please avoid using asterisks for representing multiplication.

## Monte Carlo for machine learning applications

• Conclusion
1. Please correct the last sentence “there could be other optimized methods emerge”

• Theory, methodology, and/or algorithmic discussion
1. Please avoid pronouns such as “we” and “us”. This goes for all the sections.

## Convex optimization in classification problems

• Author list
• Introduction
1. The introduction of classification problems has not been included. Please expand the section by providing more context about the topic.
3. The statement of “in a minimization problem, all objective and constraint functions are convex” without specifying convex optimization problems is misleading. Please double check the writing and update if necessary.
• Theory, methodology, and/or algorithmic discussion
1. It is recommended to put “Definition” and “Properties and Benefits” under a new section “Theory” and also add a “Classification Problems” subsection.
2. Please emphasize the combination of convex optimization and classification problems.
• At least one numerical example
1. Please formulate a convex optimization problem for the classification problem and solve it with a solver.
2. The details of the algorithm are expected.
• References
1. Please avoid citing pages from Wikipedia. Please try to add journal articles or books for references.

## Weighted metric method

• Introduction
1. Please use the sentence case throughout the wiki. Many words/phrases are capitalized in the current version.
• Applications
1. The complete reference from the image caption can be removed since there’s already a citation present.

## Support vector clustering

• Introduction
1. Please place references after the period at the end of each sentence. This goes for all the sections in the wiki.
• Theory, methodology, and/or algorithmic discussion
1. Please use abbreviations after they have been introduced (e.g., “SVC algorithm” instead of “support vector clustering algorithm”).
• References
1. Please use the same reference style for each reference.

## Quantum computing for optimization

• Theory, methodology, and/or algorithmic discussion
1. Quantum approximate optimization algorithms are scarce with barely introduced concepts and math notation.

## Model predictive control

• At least one numerical example
1. “Gaussian” should be capitalized.

## Ellipsoid method

• References
1. References are not linked in the text. Please consider having the references as this Wiki page: https://optimization.cbe.cornell.edu/index.php?title=Simplex_algorithm