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! 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>
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       <li>[[Duality]]</li>
       <li>[[Duality]]</li>
       <li>[[Simplex algorithm]]</li>
       <li>[[Simplex algorithm]]</li>
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       <li>[[Line search methods]]</li>
       <li>[[Line search methods]]</li>
       <li>[[Trust-region methods]]</li>
       <li>[[Trust-region methods]]</li>
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       <li>[[Exponential transformation]]</li>
       <li>[[Exponential transformation]]</li>
       <li>[[Logarithmic transformation]]</li>
       <li>[[Logarithmic transformation]]</li>
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       <li>[[Markov decision process]]</li>
       <li>[[Markov decision process]]</li>
       <li>[[Bellman equation]]</li>
       <li>[[Bellman equation]]</li>
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! 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>
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       <li>[[Facility location problem]]</li>
       <li>[[Facility location problem]]</li>
       <li>[[Traveling salesman problem]]</li>
       <li>[[Traveling salesman problem]]</li>
      <li>[[Portfolio optimization]]</li>
       <li>[[Set covering 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>[[Unit commitment problem]]</li>
       <li>[[Quadratic assignment problem]]</li>
       <li>[[Portfolio optimization]]</li>
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       <li>[[Mixed-integer cuts]]</li>
       <li>[[Mixed-integer cuts]]</li>
       <li>[[Disjunctive inequalities]]</li>
       <li>[[Disjunctive inequalities]]</li>
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       <li>[[Heuristic algorithms]]</li>
       <li>[[Heuristic algorithms]]</li>
       <li>[[Branch and cut]]</li>
       <li>[[Branch and cut]]</li>
       <li>[[Local branching]]</li>
       <li>[[Local branching]]</li></div>
      <li>[[Feasibility pump]]</li>
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       <li>[[Signomial problems]]</li>
       <li>[[Signomial problems]]</li>
       <li>[[Mixed-integer linear fractional programming (MILFP)]]</li>
       <li>[[Mixed-integer linear fractional programming (MILFP)]]</li>
       <li>[[Convex Generalized disjunctive programming (GDP)]]</li>
       <li>[[Convex generalized disjunctive programming (GDP)]]</li>
       <li>[[Nonconvex Generalized disjunctive programming (GDP)]]</li>
       <li>[[Nonconvex generalized disjunctive programming (GDP)]]</li>
       <li>[[Branch and bound (BB) for MINLP]]</li>
       <li>[[Branch and bound (BB) for MINLP]]</li>
       <li>[[Branch and cut for MINLP]]</li>
       <li>[[Branch and cut for MINLP]]</li>
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       <li>[[Stochastic programming]]</li>
       <li>[[Stochastic programming]]</li>
       <li>[[Chance-constraint method]]</li>
       <li>[[Chance-constraint method]]</li>
       <li>[[Fuzzy programming]]</li>
       <li>[[Fuzzy programming]]</li>
       <li>[[Classical robust optimization]]</li>
       <li>[[Classical robust optimization]]</li>
      <li>[[Distributionally robust optimization]]</li>
       <li>[[Adaptive robust optimization]]</li>
       <li>[[Adaptive robust optimization]]</li>
       <li>[[Data driven robust optimization]]</li>
       <li>[[Data driven robust optimization]]</li>
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       <li>[[Stochastic gradient descent]]</li>
       <li>[[Stochastic gradient descent]]</li>
       <li>[[Momentum]]</li>
       <li>[[Momentum]]</li>
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       <li>[[RMSProp]]</li>
       <li>[[RMSProp]]</li>
       <li>[[Adam]]</li>
       <li>[[Adam]]</li>
      <li>[[Alternating direction method of multiplier (ADMM)]]</li>
       <li>[[Frank-Wolfe]]</li>
       <li>[[Frank-Wolfe]]</li>
      <li>[[Sparse Reconstruction with Compressed Sensing]]</li>
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      <li>[[Protein folding problem]]</li>
       <li>[[Wing shape optimization]]</li>
       <li>[[Wing Shape Optimization]]</li>
       <li>[[Optimization in game theory]]</li>
       <li>[[Optimization in Game Theory]]</li>
       <li>[[Quantum computing for optimization]]</li>
       <li>[[Quantum computing for optimization]]</li>
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Latest revision as of 21:45, 9 October 2023

Welcome to the Cornell University Computational 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.

Linear Programming (LP)

NonLinear Programming (NLP)

Deterministic Global Optimization

Dynamic Programming

Traditional Applications

Mixed-Integer Linear Programming (MILP)

Mixed-Integer NonLinear Programming (MINLP)

Optimization under Uncertainty

Optimization for Machine Learning and Data Analytics

Emerging Applications

Cornell Prof. Fengqi You Research Group