2021 Cornell Optimization Open Textbook Feedback: Difference between revisions

From Cornell University Computational Optimization Open Textbook - Optimization Wiki
Jump to navigation Jump to search
VisualWikitext
Line 83: Line 83:
==  [[Bayesian Optimization]] ==
==  [[Bayesian Optimization]] ==
* Introduction
* Introduction
# Discussion on applications should be moved to a separate section.
 
* Theory, methodology, and/or algorithmic discussions
* Theory, methodology, and/or algorithmic discussions
# Captions need reformatting.
# Consider italicizing keywords rather than bolding.
# Consider italicizing keywords rather than bolding.
# Please add a citation to the first sentence.  
# Please add a citation to the first sentence.  
Line 91: Line 90:
# Acquisition function figure could be made larger and clearer to improve readability.
# Acquisition function figure could be made larger and clearer to improve readability.
* At least one numerical example
* At least one numerical example
# Any references to functions or methods in code ‘e.g. fmin’ should be properly formatted as code-stylized text.
# Please use the equation editor for min, st., etc.
# Please use the equation editor for min, st., etc.
# Avoid including a figure of the code for this example and explicitly describe the steps to the modeling and solution process instead.  
# Avoid including a figure of the code for this example and explicitly describe the steps to the modeling and solution process instead.  
# Avoid pronouns such as “our” and “we”.
* References
* References
# References should be properly formatted, not just hyperlinks. Refer to the link below for an example: [[Quantum computing for optimization|https://optimization.cbe.cornell.edu/index.php?title=Quantum_computing_for_optimization]]
# References should be properly formatted, not just hyperlinks. Refer to the link below for an example: [[Quantum computing for optimization|https://optimization.cbe.cornell.edu/index.php?title=Quantum_computing_for_optimization]]
Line 101: Line 98:
* Theory, methodology, and/or algorithmic discussions
* Theory, methodology, and/or algorithmic discussions
# All equations need to be better formatted.
# All equations need to be better formatted.
# Please indent equation blocks.
# Please properly format pseudocode.
# Please properly format pseudocode.
* A conclusion section
* A conclusion section
Line 185: Line 181:
* Theory, methodology, and/or algorithmic discussions
* Theory, methodology, and/or algorithmic discussions
# Organization of ideas in this section needs work.
# Organization of ideas in this section needs work.
# You have not defined explicitly why the Cauchy point is important to compute beyond a vague allusion to performance improvements, which is also wrong (it is useful because of its guarantees for convergence, not performance) It is also misspelled.
# Please format the algorithm in proper algorithmic pseudocode format.
# Please format the algorithm in proper algorithmic pseudocode format.
* References
# Incorrect reference style.
*There are numerous misspellings, grammatical errors, and incorrect claims. Please fix these.
== [[Momentum]] ==
== [[Momentum]] ==
* An introduction of the topic
* An introduction of the topic
Line 214: Line 204:


* An introduction of the topic  
* An introduction of the topic  
# See formatting guideline below
 
# Avoid opinionated statements such as “MINLP problems are usually the hardest to solve”.
# Rearrange the text such that the MINLP formulation is in the theory section and keep the introduction in words only.  
* Theory, methodology, and/or algorithmic discussions
* Theory, methodology, and/or algorithmic discussions
# Consider left aligning equations and optimization problem formulations by the “=”. See [[Stochastic programming|https://optimization.cbe.cornell.edu/index.php?title=Stochastic_programming]] for an example
# “Minimize” and “subject to” should be “min” and “s.t.” in MathType (inconsistent formatting)
# The sentence “The Outer-Approximation (OA) algorithm was first proposed by Duran and and Grossmann in 1986 to solve MINLP problems.” needs a reference.
* At least one numerical example
# Every iteration should be clearly presented, and solved "step-by-step".
# “Minimize” and “subject to” should be “min” and “s.t.” in MathType
* A section to discuss and/or illustrate the applications
* A section to discuss and/or illustrate the applications
# Does not explicitly point out why OA is applicable (and/or preferred) in these applications, rather than other MINLP approaches (show that the problem formulations are amenable to a solution approach through OA)
 
# The sentence “... an active research area and there exists a vast number of applications in fields such as engineering, computational chemistry, and finance.” needs references.
# Posting GAMS code on the page is generally inappropriate and discouraged. Please check with the TAs or me if you have a strong desire to post GAMS codes on the Wiki page. A typical textbook should not be limited to a specific software package. If the GAMS code must be posted, please also post ALL other software implementation versions, such as Pyomo and JuliaOPT, among others.
# Consider reformatting to make steps more readable. Inserting spaces and breaking down steps would help.
* A conclusion section
* A conclusion section
# Too short. Consider discussion on future research direction and discussion on uncertainty
 
# Please review abbreviations throughout the page. Why is MINLP redefined here? “Outer-Approximation is a well known efficient approach for solving convex mixed-integer nonlinear programs (MINLP)”.
* References
* References
# Include hyperlinks to references if possible. Please consider having the references appear as in this Wiki template, [[Quantum computing for optimization|https://optimization.cbe.cornell.edu/index.php?title=Quantum_computing_for_optimization]]
# Remove "Template:Reflist"
== [[Unit commitment problem]] ==
== [[Unit commitment problem]] ==


Revision as of 08:19, 19 December 2021

Lagrangian duality

  • Author list, sections and TOC
  • An introduction of the topic
  • Theory, methodology, and/or algorithmic discussions
  1. The Lagrangian variables associated with equality constraints h(x) are unbounded but the Lagrangian dual problem states them as non-negative. Please fix the same.
  • At least one numerical example
  1. Please update the dual objective function and domain of dual variables accordingly.
  • A section to discuss and/or illustrate the applications
  • A conclusion section
  • References

Disjunctive Inequalities

  • Author list
  • 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

Stochastic Programming

  • An introduction of the topic
  1. 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 discussions
    • The symbol “xi” in the methodology subsection should be explained.
    • The inline notations (`x1`, `s1`) should also be typed using LaTex.
  • A section to discuss and/or illustrate the applications;
  1. I suggest eliminating citing the last name of the first author (i.e. Zhou et al.)

Exponential Transformation

  • Author list
  • 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

Portfolio Optimization

  • Author list
  • An introduction of the topic
  • Theory, methodology, and/or algorithmic discussions
  1. Rephrase “Cut the relevant information and conditions in the portfolio optimization, as well as the final requirements into the relevant variables, constraints and linear functions of the linear programming problem.”
  • At least one numerical example
  1. Fix misspelling “dolling decision variables”.
  • A section to discuss and/or illustrate the applications
  • A conclusion section
  1. Need some commas here (second sentence hard to read).
  • References
  1. Remove white space between end of sentences and reference numbers.

Chance constraint method

  • Author list:
  • An introduction of the topic
  • Theory, methodology, and/or algorithmic discussions
  1. Some normal text was expressed as equation.
  • At least one numerical example
  • A section to discuss and/or illustrate the applications
  • A conclusion section
  • References

Bayesian Optimization

  • Introduction
  • Theory, methodology, and/or algorithmic discussions
  1. Consider italicizing keywords rather than bolding.
  2. Please add a citation to the first sentence.
  3. Avoid pronouns such as “we”.
  4. Acquisition function figure could be made larger and clearer to improve readability.
  • At least one numerical example
  1. Please use the equation editor for min, st., etc.
  2. Avoid including a figure of the code for this example and explicitly describe the steps to the modeling and solution process instead.
  • References
  1. References should be properly formatted, not just hyperlinks. Refer to the link below for an example: https://optimization.cbe.cornell.edu/index.php?title=Quantum_computing_for_optimization

Conjugate gradient methods

  • Theory, methodology, and/or algorithmic discussions
  1. All equations need to be better formatted.
  2. Please properly format pseudocode.
  • A conclusion section
  1. Consider adding future research directions

Geometric Programming

  • Author list
  • 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

Adam

  • Author list
  • An introduction of the topic
  • Theory, methodology, and/or algorithmic discussions
  1. Avoid inserting inline citations after words like “This article..” as it is a bit informal. This could be rephrased or changed to something like “According to author,^[2] …” with author name inserted.
  • At least one numerical example
  • A section to discuss and/or illustrate the applications
  • A conclusion section
  • References

a* algorithm

  • Author list
  • An introduction of the topic:
  1. Please consider correcting a few grammatical errors: “Optimal path”, “cross country”, missing period at end of first paragraph, other random capitalizations, etc.
  2. There are no citations in the introduction. Please cite every source.
  • Theory, methodology, and/or algorithmic discussions
  1. Please add the mathematical description of the algorithm. (Insufficient)
  2. Please fix grammatical and spelling errors as (“from current position to the goal”, “There are a lot of discussions”, etc). Also, many hyphens are missing as “non playable”.
  • At least one numerical example
  1. The numerical example does not show the full computations the algorithm performs. Please show the computation on a smaller example.
  • A section to discuss and/or illustrate the applications
  • A conclusion section
  • References

Job-Shop Scheduling Problem

  • An introduction of the topic
  • Theory, methodology, and/or algorithmic discussions
  1. Since this Wiki focuses on jobshop scheduling, at least two methods are expected. Branch and bound is a general MILP technique, so, it is recommended to add a tailored technique that can only solve specific jobshop scheduling problems. Solving the numerical example with this technique is not necessary.
  • At least one numerical example
  • A section to discuss and/or illustrate the applications
  • A conclusion section
  • References

Optimization in game theory

  • Author list
  • An introduction of the topic
  • Theory, methodology, and/or algorithmic discussions
  1. Add a mathematical description of the problem and a pseudocode/flowchart for the Lemke-Howson algorithm.  
  2. Rephrase “This algorithm utilizes iterated pivoting much like the simplex algorithm used in the simplex algorithm used in linear programming”.
  3. Formatting (incomplete).
  • At least one numerical example
  • A section to discuss and/or illustrate the applications
  • A conclusion section
  • References
  1. Incorrect reference style.

Trust-region methods

  • An introduction of the topic
    • Avoid pronouns such as “we”. This goes for all other sections as well.
  • Theory, methodology, and/or algorithmic discussions
  1. Organization of ideas in this section needs work.
  2. Please format the algorithm in proper algorithmic pseudocode format.

Momentum

  • 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
  • References

Stochastic Dynamic programming

  • Author list
  • 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

Outer-approximation

  • An introduction of the topic
  • Theory, methodology, and/or algorithmic discussions
  1. “Minimize” and “subject to” should be “min” and “s.t.” in MathType (inconsistent formatting)
  • A section to discuss and/or illustrate the applications
  • A conclusion section
  • References

Unit commitment problem

  • Author list
  • An introduction of the topic
  • Theory, methodology, and/or algorithmic discussions
  • At least one numerical example
  1. Fix typo “while minimize” to “while minimizing”.
  • A section to discuss and/or illustrate the applications:
  • A conclusion section
  • References

Frank-Wolfe

  • Author list:
  • 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

Line Search Method

  • Author list
  • An introduction of the topic
  • Theory, methodology, and/or algorithmic discussions
  1. Avoid pronouns such as “we” (all sections).
  • At least one numerical example:
  • A section to discuss and/or illustrate the applications:
  • A conclusion section
  • References

Piecewise Linear Approximation

  • Author list
  • 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

Mathematical Programming with Equilibrium constraints

  • 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

Wing shape Optimization

  • Author list:
  • An introduction of the topic
  • Theory, methodology, and/or algorithmic discussions
  • At least one numerical example
  1. A numerical example is simply "numerical" and does not need any application context (similar to those numerical problems in HW assignments). There is an Application section where you discuss the applications.
  • A section to discuss and/or illustrate the applications
  • A conclusion section
  1. These variables should be defined before the conclusion section, they are out of place here.
  • References
  1. Include hyperlinks to references if possible.

Interior point method for NLP

  • Theory, methodology, and/or algorithmic discussions
    • Need discussion about the concept of “central path” and the notion of self concordance
    • Please consider proper formatting of the algorithm as pseudocode. Algorithms also must be accompanied with high level summary and discussion on its most important high level ideas.
    • Fix typo “optimisation”.

Adagrad

  • At least one numerical example
  1. In the first sentence, “..take the following numerical example” should be followed by a colon.
  • A section to discuss and/or illustrate the applications
  1. This section is too short; include specific applications in which input features are sparse and Adagrad excels.
  • References
  1. References not properly formatted

McCormick Envelopes

  • Author list
  • Sections
  • An introduction of the topic
  • Theory, methodology, and/or algorithmic discussions
  1. References are not linked or expressed correctly. Please consider having the references as this Wiki template, https://optimization.cbe.cornell.edu/index.php?title=Quantum_computing_for_optimization
  • At least one numerical example
  1. Please add a few sentences to show the transition from problem to solution.
  2. The solution technique should be clearly presented, and solved "step-by-step".
  • A section to discuss and/or illustrate the applications
  • A conclusion section:
  • References
  1. Please follow the standard reference style - the current format is incorrect.

Branch and Bound for MINLP

  • Author list:
  • An introduction of the topic
  • Theory, methodology, and/or algorithmic discussions
  • At least one numerical example
  1. Please show a step-by-step solution in the example. The solution is incomplete. The Numerical Example section needs a "step-by-step" calculation process and a clear presentation of each step's results. (again, similar to the way of solving an HW problem).
  1. This example does not follow the MINLP structure discussed in the above section since binary variables are missing. Branch and bound may not be appropriate for such problems. Please provide an appropriate numerical example and solve it according to the above comments.
  • A section to discuss and/or illustrate the applications
  • A conclusion section:
  • References
  1. Too few references overall, you should aggregate information from multiple sources. A quick Google scholar search could provide relevant references.
  2. Please follow the standard reference style - the current format is incorrect.
Retrieved from "https://optimization.cbe.cornell.edu/index.php?title=2021_Cornell_Optimization_Open_Textbook_Feedback&oldid=6220"