# 2020 Cornell Optimization Open Textbook Feedback

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## Computational complexity

- Numerical Example
- Finding subsets of a set is NOT O(2
^{n}).

- Finding subsets of a set is NOT O(2
- Application
- The applications mentioned need to be discussed further.

## Network flow problem

- Numerical Example and Solution
- There is NO need to include code. Simply mention how the problem was coded along with details on the LP solver used.

## Interior-point method for LP

- Introduction
- 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

- 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 and Algorithmic Discussion
- aij are not defined in this section.

## Quasi-Newton methods

- Theory and Algorithm
- Please ensure that few spaces are kept between the equations and equation numbers.

## Eight step procedures

- Numerical Example
- Data for the example Knapsack problem (b,w) are missing.
- How to arrive at optimal solutions is missing.

## Set covering problem

- 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

- Formulation
- 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

- 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.

## Heuristic algorithms

- Methodology
- Greedy method to solve minimum spanning tree seems to be missing.

## Branch and cut

- Methodology & Algorithm
- 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.

## Mixed-integer linear fractional programming (MILFP)

- Application and Modeling for Numerical Examples
- Please check the index notation in Mass Balance Constraint

## Fuzzy programming

- 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.

## Stochastic gradient descent

- 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.

## RMSProp

- Theory and Methodology
- Please check grammar in this section.

- Applications and Discussion
- The applications section does not contain any discussion on applications. Please mention a few applications of the widely used RMSprop and discuss them briefly.

- Reference
- Many references listed here are not used in any of the text in the Wiki. Please link them appropriately.