2020 Cornell Optimization Open Textbook Feedback: Difference between revisions
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==[[Computational complexity]]== | ==[[Computational complexity]]== | ||
* | * 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>). | ||
* | * Application | ||
*# The applications mentioned need to be discussed further. | *# The applications mentioned need to be discussed further. | ||
==[[Network flow problem]]== | ==[[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. | *# 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]]== | ==[[Interior-point method for LP]]== | ||
* | * Introduction | ||
*# Please type “minimize” and “subject to” in formal optimization problem form throughout the whole page. | *# Please type “minimize” and “subject to” in formal optimization problem form throughout the whole page. | ||
* A section to discuss and/or illustrate the applications | * A section to discuss and/or illustrate the applications | ||
Line 31: | Line 22: | ||
* An introduction of the topic | * An introduction of the topic | ||
*# Add few sentences on how absolute values convert optimization problem into a nonlinear optimization problem | *# 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. | *# 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)]]== | ==[[Matrix game (LP for game theory)]]== | ||
* Theory | * Theory and Algorithmic Discussion | ||
*# aij are not defined in this section. | *# aij are not defined in this section. | ||
==[[Quasi-Newton methods]]== | ==[[Quasi-Newton methods]]== | ||
* Theory | * Theory and Algorithm | ||
*# Please ensure that few spaces are kept between the equations and equation numbers. | *# Please ensure that few spaces are kept between the equations and equation numbers. | ||
==[[Eight step procedures]]== | ==[[Eight step procedures]]== | ||
* | * Numerical Example | ||
*# Data for the example Knapsack problem (b,w) are missing. | *# Data for the example Knapsack problem (b,w) are missing. | ||
*# How to arrive at optimal solutions is missing. | *# How to arrive at optimal solutions is missing. | ||
==[[Set covering problem]]== | ==[[Set covering problem]]== | ||
* | * Numerical Example | ||
*# Please leave some space between equation and equation number. | *# Please leave some space between equation and equation number. | ||
Line 76: | Line 53: | ||
==[[Newsvendor problem]]== | ==[[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 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. | *# A mathematical presentation of the solution technique is expected. Please consider any distribution for R and present a solution technique for that specific problem. | ||
Line 82: | Line 59: | ||
==[[Mixed-integer cuts]]== | ==[[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. | *# 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]]== | ==[[Heuristic algorithms]]== | ||
* | * Methodology | ||
*# Greedy method to solve minimum spanning tree seems to be missing. | *# Greedy method to solve minimum spanning tree seems to be missing. | ||
==[[Branch and cut]]== | ==[[Branch and cut]]== | ||
* | * Methodology & Algorithm | ||
*# 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. | *# Step 5 contains latex code terms that are not properly formatted. | ||
== [[Mixed-integer linear fractional programming (MILFP)]] == | == [[Mixed-integer linear fractional programming (MILFP)]] == | ||
* | * Application and Modeling for Numerical Examples | ||
*# Please check the index notation in Mass Balance Constraint | *# Please check the index notation in Mass Balance Constraint | ||
==[[Fuzzy programming]]== | ==[[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 | *# 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]] == | == [[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. | *# 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]]== | ==[[RMSProp]]== | ||
* Theory and Methodology | |||
* Theory | |||
*# Please check grammar in this section. | *# 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. | *# 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. | |||
* | |||
*# |
Latest revision as of 07:12, 21 December 2020
Computational complexity
- Numerical Example
- Finding subsets of a set is NOT O(2n).
- 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.