Main Page: Difference between revisions

From Cornell University Computational Optimization Open Textbook - Optimization Wiki
Jump to navigation Jump to search
No edit summary
No edit summary
(42 intermediate revisions by 2 users not shown)
Line 1: Line 1:
{| id="mp-topbanner" style="width:100%; background:#f6f6f6; margin-top:1.2em; border:1px solid #ddd;"
<!-- Header table. Introduction. -->
| style="width:61%; color:#000;" |
'''Welcome to the Northwestern University Process Optimization Open Textbook.''' <br />
{| style="width:100%; border:none; background:none;"
This electronic textbook is a student-contributed open-source text covering a variety of topics on process optimization.
| style="text-align:center; white-space:nowrap; color:#000;" |
<br />
<div style="font-size:162%; border:none; margin:0; padding:.1em; color:#000;">Welcome to the Cornell University Computational Optimization Open Textbook</div>
If you have any comments or suggestions on this open textbook, please contact [//www.orie.cornell.edu/orie/people/field-profile.cfm?netid=fy86_field  Professor Fengqi You].
<br />
----
<br /><br />
<font size="6">Northwestern University Open Text Book on Process Optimization</font>


This electronic textbook is a student-contributed open-source text covering a variety of topics on process optimization.<br />
{| class="wikitable" style="padding: 1em; text-align:left"
'''If you have any comments or suggestions on this open textbook, please contact [https://www.engineering.cornell.edu/faculty-directory/fengqi-you  Professor Fengqi You].'''
|- valign="top"
|}
|width = "400pt"|<br />'''&nbsp;&nbsp;Linear Programming (LP)'''
|}
# [[Computational complexity]]
# [[Matrix game (LP for game theory)]]
# [[Network flow problem]]
# [[Interior-point method for LP]]
# [[Optimization with absolute values]]
<br />
 
|width = "400pt"|<br />'''&nbsp;&nbsp;Mixed-Integer Linear Programming (MILP)'''
# [[Facility location problems]]
# [[Traveling salesman problems]]
# [[Mixed-integer cuts]]
# [[Disjunctive inequalities]]
# [[Lagrangean duality]]
# [[Column generation algorithms]]
# [[Heuristic algorithms]]
# [[Branch and cut]]
<br />
 
|- valign="top"
|<br />'''&nbsp;&nbsp;NonLinear Programming (NLP)'''
# [[Line search methods]]
# [[Trust-region methods]]
# [[Interior-point method for NLP]]
# [[Conjugate gradient methods]]
# [[Quasi-Newton methods]]
# [[Quadratic programming]]
# [[Sequential quadratic programming]]
# [[Subgradient optimization]]
# [[Mathematical programming with equilibrium constraints]]
# [[Dynamic optimization]]
# [[Geometric programming]]
# [[Nondifferentiable Optimization]]
<br />
 
|<br />'''&nbsp;&nbsp;Mixed-Integer NonLinear Programming (MINLP)'''
# [[Signomial problems]]
# [[Mixed-integer linear fractional programming (MILFP)]]
# [[Convex Generalized disjunctive programming (GDP)]]
# [[Nonconvex Generalized disjunctive programming (GDP)]]
# [[Branch and bound (BB)]]
# [[Branch and cut for MINLP]]
# [[Generalized Benders decomposition (GBD)]]
# [[Outer-approximation (OA)]]
# [[Extended cutting plane (ECP)]]
<br />
 
|- valign="top"
 
|<br />'''&nbsp;&nbsp;Global Optimization'''
# [[Exponential transformation]]
# [[Logarithmic transformation]]
# [[McCormick envelopes]]
# [[Piecewise linear approximation]]
# [[Spatial branch and bound method]]
<br />
 
|<br />'''&nbsp;&nbsp;Optimization under Uncertainty'''
# [[Stochastic programming]]
# [[Chance-constraint method]]
# [[Fuzzy programming]]
# [[Classical robust optimization]]
# [[Adaptive robust optimization]]
# [[Data driven robust optimization]]
<br />
 
 
|- valign="top"


{| id="mp-upper" style="width: 100%; margin:6px 0 0 0; background:none; border-spacing: 0px;"
|<br />'''&nbsp;&nbsp;Featured Applications'''
| class="MainPageBG" style="width:50%; border:1px solid #cef2e0; background:#f5fffa; vertical-align:top; color:#000;" |
# [[Wing Shape Optimization]]
{| id="mp-left" style="width:100%; vertical-align:top; background:#f5fffa;"
# [[Applying Optimization in Game Theory]]
! style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#cef2e0; font-size:120%; font-weight:bold; border:1px solid #a3bfb1; text-align:left; color:#000; padding:0.2em 0.4em;">Linear Programming (LP)</h2>
<br />
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px 5px 15px">
      <li>[[Duality]]</li>
      <li>[[Simplex algorithm]]</li>
      <li>[[Computational complexity]]</li>
      <li>[[Network flow problem]]</li>
      <li>[[Interior-point method for LP]]</li>
      <li>[[Optimization with absolute values]]</li>
      <li>[[Matrix game (LP for game theory)]]</li>
</div>
|-
! style="padding:2px" | <h2 id="mp-dyk-h2" style="margin:3px; background:#cef2e0; font-size:120%; font-weight:bold; border:1px solid #a3bfb1; text-align:left; color:#000; padding:0.2em 0.4em;">NonLinear Programming (NLP)</h2>
|-
| style="color:#000;padding:2px 5px 5px 15px" | <div id="mp-dyk">
      <li>[[Line search methods]]</li>
      <li>[[Trust-region methods]]</li>
      <li>[[Interior-point method for NLP]]</li>
      <li>[[Conjugate gradient methods]]</li>
      <li>[[Quasi-Newton methods]]</li>
      <li>[[Quadratic programming]]</li>
      <li>[[Sequential quadratic programming]]</li>
      <li>[[Subgradient optimization]]</li>
      <li>[[Mathematical programming with equilibrium constraints]]</li>
      <li>[[Dynamic optimization]]</li>
      <li>[[Geometric programming]]</li>
      <li>[[Nondifferentiable Optimization]]</li>
</div>
|-
! style="padding:2px" | <h2 id="mp-dyk-h2" style="margin:3px; background:#cef2e0; font-size:120%; font-weight:bold; border:1px solid #a3bfb1; text-align:left; color:#000; padding:0.2em 0.4em;">Deterministic Global Optimization</h2>
|-
| style="color:#000;padding:2px 5px 5px 15px" | <div id="mp-dyk">
      <li>[[Exponential transformation]]</li>
      <li>[[Logarithmic transformation]]</li>
      <li>[[McCormick envelopes]]</li>
      <li>[[Piecewise linear approximation]]</li>
      <li>[[Spatial branch and bound method]]</li>
</div>
|-
! style="padding:2px" | <h2 id="mp-dyk-h2" style="margin:3px; background:#cef2e0; font-size:120%; font-weight:bold; border:1px solid #a3bfb1; text-align:left; color:#000; padding:0.2em 0.4em;">Dynamic Programming</h2>
|-
| style="color:#000;padding:2px 5px 5px 15px" | <div id="mp-dyk">
      <li>[[Markov decision process]]</li>
      <li>[[Bellman equation]]</li>
      <li>[[Eight step procedures]]</li>
      <li>[[Stochastic dynamic programming]]</li>
</div>
|-
! style="padding:2px" | <h2 id="mp-dyk-h2" style="margin:3px; background:#cef2e0; font-size:120%; font-weight:bold; border:1px solid #a3bfb1; text-align:left; color:#000; padding:0.2em 0.4em;">Traditional Applications</h2>
|-
| style="color:#000;padding:2px 5px 5px 15px" | <div id="mp-dyk">
      <li>[[Facility location problem]]</li>
      <li>[[Traveling salesman problem]]</li>
      <li>[[Set covering problem]]</li>
      <li>[[Quadratic assignment problem]]</li>
      <li>[[Job shop scheduling]]</li>
      <li>[[Newsvendor problem]]</li>
      <li>[[Unit commitment problem]]</li>
      <li>[[Portfolio optimization]]</li>
</div>


|}
|}


| style="border:1px solid transparent;" |
| class="MainPageBG" style="width:50%; border:1px solid #cedff2; background:#f5faff; vertical-align:top;"|
{| id="mp-right" style="width:100%; vertical-align:top; background:#f5faff;"
! style="padding:2px" | <h2 id="mp-otd-h2" style="margin:3px; background:#cedff2; font-size:120%; font-weight:bold; border:1px solid #a3b0bf; text-align:left; color:#000; padding:0.2em 0.4em;">Mixed-Integer Linear Programming (MILP)</h2>
|-
| style="color:#000;padding:2px 5px 5px 15px" | <div id="mp-otd">
      <li>[[Mixed-integer cuts]]</li>
      <li>[[Disjunctive inequalities]]</li>
      <li>[[Lagrangean duality]]</li>
      <li>[[Column generation algorithms]]</li>
      <li>[[Heuristic algorithms]]</li>
      <li>[[Branch and cut]]</li>
      <li>[[Local branching]]</li></div>
|-
! style="padding:2px" | <h2 id="mp-otd-h2" style="margin:3px; background:#cedff2; font-size:120%; font-weight:bold; border:1px solid #a3b0bf; text-align:left; color:#000; padding:0.2em 0.4em;">Mixed-Integer NonLinear Programming (MINLP)</h2>
|-
| style="color:#000;padding:2px 5px 5px 15px" | <div id="mp-otd">
      <li>[[Signomial problems]]</li>
      <li>[[Mixed-integer linear fractional programming (MILFP)]]</li>
      <li>[[Convex generalized disjunctive programming (GDP)]]</li>
      <li>[[Nonconvex generalized disjunctive programming (GDP)]]</li>
      <li>[[Branch and bound (BB) for MINLP]]</li>
      <li>[[Branch and cut for MINLP]]</li>
      <li>[[Generalized Benders decomposition (GBD)]]</li>
      <li>[[Outer-approximation (OA)]]</li>
      <li>[[Extended cutting plane (ECP)]]</li>
</div>
|-
! style="padding:2px" | <h2 id="mp-otd-h2" style="margin:3px; background:#cedff2; font-size:120%; font-weight:bold; border:1px solid #a3b0bf; text-align:left; color:#000; padding:0.2em 0.4em;">Optimization under Uncertainty</h2>
|-
| style="color:#000;padding:2px 5px 5px 15px" | <div id="mp-dyk">
      <li>[[Stochastic programming]]</li>
      <li>[[Chance-constraint method]]</li>
      <li>[[Fuzzy programming]]</li>
      <li>[[Classical robust optimization]]</li>
      <li>[[Adaptive robust optimization]]</li>
      <li>[[Data driven robust optimization]]</li>
</div>
|-
! style="padding:2px" | <h2 id="mp-otd-h2" style="margin:3px; background:#cedff2; font-size:120%; font-weight:bold; border:1px solid #a3b0bf; text-align:left; color:#000; padding:0.2em 0.4em;">Optimization for Machine Learning and Data Analytics</h2>
|-
| style="color:#000;padding:2px 5px 5px 15px" | <div id="mp-dyk">
      <li>[[Stochastic gradient descent]]</li>
      <li>[[Momentum]]</li>
      <li>[[AdaGrad]]</li>
      <li>[[RMSProp]]</li>
      <li>[[Adam]]</li>
      <li>[[Frank-Wolfe]]</li>
      <li>[[Sparse Reconstruction with Compressed Sensing]]</li>
</div>
|-
! style="padding:2px" | <h2 id="mp-otd-h2" style="margin:3px; background:#cedff2; font-size:120%; font-weight:bold; border:1px solid #a3b0bf; text-align:left; color:#000; padding:0.2em 0.4em;">Emerging Applications</h2>
|-
| style="color:#000;padding:2px 5px 5px 15px" | <div id="mp-dyk">
      <li>[[Wing shape optimization]]</li>
      <li>[[Optimization in game theory]]</li>
      <li>[[Quantum computing for optimization]]</li>
</div>
|}
|}


== Sponsor ==
Consult the [https://www.mediawiki.org/wiki/Special:MyLanguage/Help:Contents User's Guide] for information on using the wiki software.
[[File:Peese-logo.jpg|Cornell Prof. Fengqi You Research Group |link=https://www.peese.org]]


</noinclude>__NOTOC____NOEDITSECTION__
== Getting started ==
* [https://www.mediawiki.org/wiki/Special:MyLanguage/Manual:Configuration_settings Configuration settings list]
* [https://www.mediawiki.org/wiki/Special:MyLanguage/Manual:FAQ MediaWiki FAQ]
* [https://lists.wikimedia.org/mailman/listinfo/mediawiki-announce MediaWiki release mailing list]
* [https://www.mediawiki.org/wiki/Special:MyLanguage/Localisation#Translation_resources Localise MediaWiki for your language]
* [https://www.mediawiki.org/wiki/Special:MyLanguage/Manual:Combating_spam Learn how to combat spam on your wiki]

Revision as of 18:24, 26 August 2020

Welcome to the Northwestern University Process Optimization Open Textbook.
This electronic textbook is a student-contributed open-source text covering a variety of topics on process optimization.
If you have any comments or suggestions on this open textbook, please contact Professor Fengqi You.




Northwestern University Open Text Book on Process Optimization


  Linear Programming (LP)
  1. Computational complexity
  2. Matrix game (LP for game theory)
  3. Network flow problem
  4. Interior-point method for LP
  5. Optimization with absolute values



  Mixed-Integer Linear Programming (MILP)
  1. Facility location problems
  2. Traveling salesman problems
  3. Mixed-integer cuts
  4. Disjunctive inequalities
  5. Lagrangean duality
  6. Column generation algorithms
  7. Heuristic algorithms
  8. Branch and cut



  NonLinear Programming (NLP)
  1. Line search methods
  2. Trust-region methods
  3. Interior-point method for NLP
  4. Conjugate gradient methods
  5. Quasi-Newton methods
  6. Quadratic programming
  7. Sequential quadratic programming
  8. Subgradient optimization
  9. Mathematical programming with equilibrium constraints
  10. Dynamic optimization
  11. Geometric programming
  12. Nondifferentiable Optimization



  Mixed-Integer NonLinear Programming (MINLP)
  1. Signomial problems
  2. Mixed-integer linear fractional programming (MILFP)
  3. Convex Generalized disjunctive programming (GDP)
  4. Nonconvex Generalized disjunctive programming (GDP)
  5. Branch and bound (BB)
  6. Branch and cut for MINLP
  7. Generalized Benders decomposition (GBD)
  8. Outer-approximation (OA)
  9. Extended cutting plane (ECP)



  Global Optimization
  1. Exponential transformation
  2. Logarithmic transformation
  3. McCormick envelopes
  4. Piecewise linear approximation
  5. Spatial branch and bound method



  Optimization under Uncertainty
  1. Stochastic programming
  2. Chance-constraint method
  3. Fuzzy programming
  4. Classical robust optimization
  5. Adaptive robust optimization
  6. Data driven robust optimization




  Featured Applications
  1. Wing Shape Optimization
  2. Applying Optimization in Game Theory



Consult the User's Guide for information on using the wiki software.

Getting started