# Difference between revisions of "2020 Cornell Optimization Open Textbook Feedback"

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* Theory, methodology, and/or algorithmic discussions | * Theory, methodology, and/or algorithmic discussions | ||

− | *# Equation in most infeasible branching section is not properly formatted | + | *# Equation in most infeasible branching section is not properly formatted. |

*# Step 2 appears abruptly in the algorithm and does not explain much. Please add more information regarding the same. | *# Step 2 appears abruptly in the algorithm and does not explain much. Please add more information regarding the same. | ||

*# Step 5 contains latex code terms that are not properly formatted. Please fix the same. | *# Step 5 contains latex code terms that are not properly formatted. Please fix the same. | ||

− | *# Fix typos: e.g., repeated “for the current” | + | *# Fix typos: e.g., repeated “for the current”. |

== [[Mixed-integer linear fractional programming (MILFP)]] == | == [[Mixed-integer linear fractional programming (MILFP)]] == | ||

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* A section to discuss and/or illustrate the applications | * A section to discuss and/or illustrate the applications | ||

− | *# Applications of fuzzy programming are quite versatile. Please discuss few of the mentioned applications briefly. The provided example Wikis can be used as a reference to write this section. | + | *# Applications of fuzzy programming are quite versatile. Please discuss few of the mentioned applications briefly. The provided example Wikis can be used as a reference to write this section. |

==[[Adaptive robust optimization]]== | ==[[Adaptive robust optimization]]== |

## Revision as of 08:26, 15 December 2020

## Duality

- Theory, methodology, and/or algorithmic discussions
- Remove colon in the subsection title

## Simplex algorithm

## Computational complexity

- At least one numerical example
- Finding subsets of a set is NOT O(2
^{n}).

- Finding subsets of a set is NOT O(2
- A section to discuss and/or illustrate the applications
- The applications mentioned need to be discussed further.

## Network flow problem

- At least one numerical example
- There is NO need to include code. Simply mention how the problem was coded along with details on the LP solver used.
- The subsection title style should be consistent. Subsection titles in Real Life Applications section are not in title case like the ones in Theory section.

## Interior-point method for LP

- An introduction of the topic
- Fix typos “where A ε R” in Lagrange Function subsection.
- Please type “minimize” and “subject to” in formal optimization problem form throughout the whole page.

- A section to discuss and/or illustrate the applications
- Please type optimization problem in the formal form.

## Optimization with absolute values

- An introduction of the topic
- Add few sentences on how absolute values convert optimization problem into a nonlinear optimization problem

- A section to discuss and/or illustrate the applications
- Inline equations at the beginning of this section are not formatted properly. Please fix the notation for expected return throughout the section.

## Matrix game (LP for game theory)

- Theory, methodology, and/or algorithmic discussions
- aij are not defined in this section.

## Quasi-Newton methods

- Theory, methodology, and/or algorithmic discussions
- Please ensure that few spaces are kept between the equations and equation numbers.

## Markov decision process

- An introduction of the topic
- Please fix typos such as “discreet”.

- Theory, methodology, and/or algorithmic discussions
- If abbreviations are defined like MDP, use the abbreviations throughout the Wiki

## Eight step procedures

- At least one numerical example
- Data for the example Knapsack problem (b,w) are missing.
- How to arrive at optimal solutions is missing.

## Facility location problem

- At least one numerical example
- Mention how the formulated problem is coded and solved. No need to provide GAMS code.

## Set covering problem

- Theory, methodology, and/or algorithmic discussions
- Use proper math notations for “greater than equal to”.

- At least one numerical example
- Please leave some space between equation and equation number.

## Quadratic assignment problem

- Theory, methodology, and/or algorithmic discussions
- Discuss dynamic programming and cutting plane solution techniques briefly.

## Newsvendor problem

- Theory, methodology, and/or algorithmic discussions
- A math programming formulation of the optimization problem with objective function and constraints is expected for the formulation. Please add any variant of the newsvendor problem along with some operational constraints.
- A mathematical presentation of the solution technique is expected. Please consider any distribution for R and present a solution technique for that specific problem.

## Mixed-integer cuts

- A section to discuss and/or illustrate the applications
- MILP and their solution techniques involving cuts are extremely versatile. Yet, only two sentences are added to describe their applications. Please discuss their applications, preferably real-world applications, in brief. Example Wikis provided on the website could be used as a reference to do so.

## Column generation algorithms

- An introduction of the topic
- References at the end of the sentence should be placed after the period.

- Theory, methodology, and/or algorithmic discussions
- Some minor typos/article agreement issues exist “is not partical in real-world”.

## Heuristic algorithms

- Theory, methodology, and/or algorithmic discussions
- Please use proper symbol for "greater than or equal to".
- Greedy method to solve minimum spanning tree seems to be missing.

## Branch and cut

- Theory, methodology, and/or algorithmic discussions
- Equation in most infeasible branching section is not properly formatted.
- Step 2 appears abruptly in the algorithm and does not explain much. Please add more information regarding the same.
- Step 5 contains latex code terms that are not properly formatted. Please fix the same.
- Fix typos: e.g., repeated “for the current”.

## Mixed-integer linear fractional programming (MILFP)

- At least one numerical example
- Please check the index notation in Mass Balance Constraint

## Convex generalized disjunctive programming (GDP)

- An introduction of the topic
- Please refrain from defining the same abbreviations multiple times.
- Please use abbreviations throughout the page if they have been defined.

- At least one numerical example
- There is a duplicate figure 3.

## Fuzzy programming

- A section to discuss and/or illustrate the applications
- Applications of fuzzy programming are quite versatile. Please discuss few of the mentioned applications briefly. The provided example Wikis can be used as a reference to write this section.

## Adaptive robust optimization

- Theory, methodology, and/or algorithmic discussions
- Please check typos such as "Let
*u*bee a vector". - The abbreviation KKT is not previously defined.

- Please check typos such as "Let

## Stochastic gradient descent

- At least one numerical example
- Amount of whitespace can be reduced by changing orientation of example dataset by converting it into a table containing 3 rows and 6 columns.

- A section to discuss and/or illustrate the applications
- Deep learning can become a subsection on its own.

## RMSProp

- An introduction of the topic
- References at the end of the sentence should be placed after the period.

- Theory, methodology, and/or algorithmic discussions
- Please check grammar in this section.

- A section to discuss and/or illustrate the applications
- The applications section does not contain any discussion on applications. Please mention a few applications of the widely used RMSprop and discuss them briefly.

## Adam

- Theory, methodology, and/or algorithmic discussions
- References at the end of the sentence should be placed after the period.