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

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* An introduction of the topic | * An introduction of the topic | ||

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

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* At least one numerical example | * At least one numerical example | ||

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*# Please check the index notation in Mass Balance Constraints. | *# Please check the index notation in Mass Balance Constraints. | ||

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

* A conclusion section | * A conclusion section | ||

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* An introduction of the topic | * An introduction of the topic | ||

− | *# Please | + | *# Please refrain from defining the same abbreviations multiple times. |

− | *# Please | + | *# Please use abbreviations throughout the page if they have been defined. |

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

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* At least one numerical example | * At least one numerical example | ||

− | *# | + | *# There is a duplicate figure. |

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

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* A conclusion section | * A conclusion section | ||

* References | * References | ||

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==[[Fuzzy programming]]== | ==[[Fuzzy programming]]== | ||

* An introduction of the topic” | * An introduction of the topic” | ||

− | *# | + | *# References at the end of the sentence should be placed after the period. |

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

*# Very well written. | *# Very well written. | ||

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* At least one numerical example | * At least one numerical example | ||

− | *# | + | *# The numeric example should be before the applications section. |

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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. | ||

− | * A conclusion section | + | * A conclusion section |

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* References | * References | ||

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*# Please consider linking the references by using this as Wiki template, [[Quantum computing for optimization|https://optimization.cbe.cornell.edu/index.php?title=Quantum_computing_for_optimization]] | *# Please consider linking the references by using this as Wiki template, [[Quantum computing for optimization|https://optimization.cbe.cornell.edu/index.php?title=Quantum_computing_for_optimization]] | ||

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* An introduction of the topic | * An introduction of the topic | ||

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

− | *# | + | *# Please check typos such as "Let ''u'' bee a vector". |

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*# The abbreviation KKT is not previously defined. | *# The abbreviation KKT is not previously defined. | ||

* At least one numerical example | * At least one numerical example | ||

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== [[Stochastic gradient descent]] == | == [[Stochastic gradient descent]] == | ||

* An introduction of the topic | * An introduction of the topic | ||

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

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* At least one numerical example | * At least one numerical example | ||

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*# Amount of whitespace can be reduced by changing orientation of example dataset by converting it into a table containing 3 rows and 6 columns. | *# Amount of whitespace can be reduced by changing orientation of example dataset by converting it into a table containing 3 rows and 6 columns. | ||

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

− | *# | + | *# Deep learning can become a subsection on its own. |

− | + | * A conclusion section | |

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− | * A conclusion section | ||

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* References | * References | ||

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==[[RMSProp]]== | ==[[RMSProp]]== |

## Revision as of 18:37, 14 December 2020

## Duality

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions
- Double check indexes in the dual problem. LHS of the dual problem constraint should be aji.
- Equations in the “constructing the dual” subsection should be aligned properly.
- Please add more details to the KKT Conditions section.
- Remove colon in the subsection title

- At least one numerical example
- A section to discuss and/or illustrate the applications
- A conclusion section
- References
- Lecture notes may not be a credible reference. Please find the original source.

## Simplex algorithm

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions
- The symbol i in the second expression in dictionary functions, ranges from 1 to m.

- At least one numerical example
- A section to discuss and/or illustrate the applications
- A conclusion section
- References 1. Please be consistent with referencing style.

## Computational complexity

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions
- Please introduce the Big-oh notation in this section.

- At least one numerical example
- Examples of combinatorial optimization is suggested.

- A section to discuss and/or illustrate the applications
- The applications mentioned need to be discussed further.

- A conclusion section
- References.

## Network flow problem

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions.
- 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.

- A section to discuss and/or illustrate the application
- A conclusion section
- References

## Interior-point method for LP

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

- Theory, methodology, and/or algorithmic discussions
- At least one numerical example
- The numerical example does not use any Newton’s method iterations that are presented in the above section. Please consider using a complicated example that actually uses Newton’s iterations.
- Please type the maximization problem in LaTex form.

- A section to discuss and/or illustrate the applications
- Please double check typos and extra spaces.

- A conclusion section
- References

## Optimization with absolute values

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

- Theory, methodology, and/or algorithmic discussions
- Please add more details to absolute values in nonlinear optimization. (very important!)

- At least one numerical example
- 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.

- A conclusion section
- References

## Matrix game (LP for game theory)

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions
- aij are not defined in this section.

- At least one numerical example
- Interesting example, very well explained.

- A section to discuss and/or illustrate the applications
- A conclusion section
- References
- Please consider linking the references by using this as Wiki template, https://optimization.cbe.cornell.edu/index.php?title=Quantum_computing_for_optimization

## Quasi-Newton methods

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions
- Please ensure that few spaces are kept between the equations and equation numbers.
- Step 6 of DFP algorithm should use the same variable M as in equation 1.14.

- At least one numerical example
- A section to discuss and/or illustrate the applications
- A conclusion section
- References

## 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.

- At least one numerical example
- A section to discuss and/or illustrate the applications
- A conclusion section
- References
- Please consider linking the references by using this as Wiki template, https://optimization.cbe.cornell.edu/index.php?title=Quantum_computing_for_optimization

## Eight step procedures

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions
- At least one numerical example
- Please be consistent in the formatting of mathematical notations and equations.

- A section to discuss and/or illustrate the applications
- A conclusion section
- References
- Lecture notes may not be a credible reference. Please find the original source.

## Facility location problem

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions
- At least one numerical example
- Mention how the formulated problem is coded and solved. No need to provide GAMS code.

- A section to discuss and/or illustrate the applications
- A conclusion section
- References
- Please consider linking the references by using this as Wiki template, https://optimization.cbe.cornell.edu/index.php?title=Quantum_computing_for_optimization

## Set covering problem

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

- At least one numerical example
- Since Table 3 provides information on aij required to formulate the constraints, Table 2 serves no purpose and should be removed from the Wiki. Table 3 can be directly generated from Table 1.
- The numerical example is solved manually without using greedy method nor LP solution method. Please solve this example both by the presented greedy algorithm and the newly added LP-based method and finally compare solutions.
- Please leave some space between equation and equation number.

- A section to discuss and/or illustrate the applications
- A conclusion section
- References

## Quadratic assignment problem

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions
- Discuss dynamic programming and cutting plane solution techniques briefly.

- At least one numerical example
- A section to discuss and/or illustrate the applications
- Please format the equation for definition of yij in the hospital layout subsection.

- A conclusion section
- References

## Newsvendor problem

- An introduction of the topic
- 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.

- At least one numerical example
- A section to discuss and/or illustrate the applications
- A conclusion section
- References

## Mixed-integer cuts

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions
- At least one numerical example
- 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.

- A conclusion section
- References

## Column generation algorithms

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions.
- At least one numerical example
- A section to discuss and/or illustrate the applications
- A conclusion section
- References

## Heuristic algorithms

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions
- At least one numerical example
- A section to discuss and/or illustrate the applications
- A conclusion section
- Reference

## Branch and cut

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions
- Equation in most infeasible branching section is not properly formatted, please fix 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.
- Fix typos: e.g., repeated “for the current”, men Problem can viewed as partially” ..

- At least one numerical example
- A section to discuss and/or illustrate the applications
- A conclusion section
- References

## Mixed-integer linear fractional programming (MILFP)

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions
- At least one numerical example
- Please check the index notation in Mass Balance Constraints.

- A section to discuss and/or illustrate the applications
- A conclusion section
- References
- Please consider linking the citations to references in the reference list by using this as Wiki template, rather than using website links. https://optimization.cbe.cornell.edu/index.php?title=Quantum_computing_for_optimization

## 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.

- Theory, methodology, and/or algorithmic discussions
- At least one numerical example
- There is a duplicate figure.

- A section to discuss and/or illustrate the applications
- A conclusion section
- References

## Fuzzy programming

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

- Theory, methodology, and/or algorithmic discussions
- Very well written.

- At least one numerical example
- The numeric example should be before the applications section.

- 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.

- A conclusion section
- References

## Adaptive robust optimization

- An introduction of the topic
- 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
- At least one numerical example
- A section to discuss and/or illustrate the applications
- A conclusion section
- References
- Overall, very well written.

## Stochastic gradient descent

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions
- 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.

- A conclusion section
- References

## RMSProp

- An introduction of the topic
- Few sentences in this section are incoherent. Please use grammatically correct sentences.

- Theory, methodology, and/or algorithmic discussions
- The equation presented in the Artificial neural network subsection is valid for the perceptron and not neural net. Please fix either the title or the equation.
- In the Rprop subsection, the momentum parameter is discussed but not used in any of the corresponding equations.
- Fix typos like PMSprop, Aritifical, in the RMSprop subsection.
- The default value of parameters in the RMSprop subsection is mentioned but their relevance or their calculation is not explained.
- Please check grammar in this section.
- Please avoid using contractions (e.g. doesn’t).
- The use of “Obviously” is advised against

- At least one numerical example
- Please demonstrate the working of RMSprop by actually solving any unconstrained optimization problem. Providing links to other resources for numerical examples renders the purpose of Wiki useless.

- 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.
- Misspelling for applications.
- Please check grammar in this section.

- A conclusion section
- Formulation of ANN is incorrect terminology. ANNs are trained by RMSprop.
- It is claimed that RMSprop achieves global optimization without any reference. Please provide a reference for the same or update the said claim.

- References
- For reference #1 please find the original source of the images and cite that source, rather than citing an image hosting service.
- Please refer to the example Wikis provided to use proper citation style.

## Adam

- An introduction of the topic
- Theory, methodology, and/or algorithmic discussions
- Key challenges mentioned in the mini-batch SGD are more relevant to the batch SGD. Consider moving these to the corresponding section.

- At least one numerical example
- A section to discuss and/or illustrate the applications
- A conclusion section
- Some minor formatting issues between symbols and text should be fixed.

- References
- Overall, very well written.