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
*# Remove colon in the subsection title
+
*# Remove colon in the subsection title.
  
 
==[[Simplex algorithm]]==
 
==[[Simplex algorithm]]==
 +
No comment.
  
 
==[[Computational complexity]]==
 
==[[Computational complexity]]==
  
* At least one numerical example
+
* Numerical Example
 
*# Finding subsets of a set is NOT O(2<sup>n</sup>).
 
*# Finding subsets of a set is NOT O(2<sup>n</sup>).
* A section to discuss and/or illustrate the applications
+
* Application
*# The applications mentioned need to be discussed further.  
+
*# The applications mentioned need to be discussed further.
  
 
==[[Network flow problem]]==
 
==[[Network flow problem]]==
  
* At least one numerical example
+
* Real Life Applications
 
*# There is NO need to include code. Simply mention how the problem was coded along with details on the LP solver used.
 
*# 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.
 
*# 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.

Revision as of 11:24, 15 December 2020

Duality

  • Theory, methodology, and/or algorithmic discussions
    1. Remove colon in the subsection title.

Simplex algorithm

No comment.

Computational complexity

  • Numerical Example
    1. Finding subsets of a set is NOT O(2n).
  • Application
    1. The applications mentioned need to be discussed further.

Network flow problem

  • Real Life Applications
    1. There is NO need to include code. Simply mention how the problem was coded along with details on the LP solver used.
    2. 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
    1. Fix typos “where A ε R” in Lagrange Function subsection.
    2. Please type “minimize” and “subject to” in formal optimization problem form throughout the whole page.
  • A section to discuss and/or illustrate the applications
    1. Please type optimization problem in the formal form.

Optimization with absolute values

  • An introduction of the topic
    1. Add few sentences on how absolute values convert optimization problem into a nonlinear optimization problem
  • A section to discuss and/or illustrate the applications
    1. 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
    1. aij are not defined in this section.

Quasi-Newton methods

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

Markov decision process

  • An introduction of the topic
    1. Please fix typos such as “discreet”.
  • Theory, methodology, and/or algorithmic discussions
    1. If abbreviations are defined like MDP, use the abbreviations throughout the Wiki

Eight step procedures

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

Facility location problem

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

Set covering problem

  • Theory, methodology, and/or algorithmic discussions
    1. Use proper math notations for “greater than equal to”.
  • At least one numerical example
    1. Please leave some space between equation and equation number.

Quadratic assignment problem

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

Newsvendor problem

  • Theory, methodology, and/or algorithmic discussions
    1. 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.
    2. 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
    1. 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
    1. References at the end of the sentence should be placed after the period.
  • Theory, methodology, and/or algorithmic discussions
    1. Some minor typos/article agreement issues exist “is not partical in real-world”.

Heuristic algorithms

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

Branch and cut

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

Mixed-integer linear fractional programming (MILFP)

  • At least one numerical example
    1. Please check the index notation in Mass Balance Constraint

Convex generalized disjunctive programming (GDP)

  • An introduction of the topic
    1. Please refrain from defining the same abbreviations multiple times.
    2. Please use abbreviations throughout the page if they have been defined.
  • At least one numerical example
    1. There is a duplicate figure 3.

Fuzzy programming

  • A section to discuss and/or illustrate the applications
    1. 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
    1. Please check typos such as "Let u bee a vector".
    2. The abbreviation KKT is not previously defined.

Stochastic gradient descent

  • At least one numerical example
    1. 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
    1. Deep learning can become a subsection on its own.

RMSProp

  • An introduction of the topic
    1. References at the end of the sentence should be placed after the period.
  • Theory, methodology, and/or algorithmic discussions
    1. Please check grammar in this section.
  • A section to discuss and/or illustrate the applications
    1. 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
    1. References at the end of the sentence should be placed after the period.