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       <li>[[Geometric programming]]</li>
       <li>[[Geometric programming]]</li>
       <li>[[Nondifferentiable Optimization]]</li>
       <li>[[Nondifferentiable Optimization]]</li>
      <li>[[Evolutionary multimodal optimization]]</li>
      <li>[[Stackelberg leadership model]]</li>
      <li>[[Quadratic constrained quadratic programming]]</li>
      <li>[[Derivative free optimization]]</li>
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       <li>[[Unit commitment problem]]</li>
       <li>[[Unit commitment problem]]</li>
       <li>[[Portfolio optimization]]</li>
       <li>[[Portfolio optimization]]</li>
      <li>[[A-star algorithm]]</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;"> Emerging Applications</h2>
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      <li>[[Wing shape optimization]]</li>
      <li>[[Optimization in game theory]]</li>
      <li>[[Quantum computing for optimization]]</li>
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       <li>[[Frank-Wolfe]]</li>
       <li>[[Frank-Wolfe]]</li>
       <li>[[Sparse Reconstruction with Compressed Sensing]]</li>
       <li>[[Sparse Reconstruction with Compressed Sensing]]</li>
      <li>[[Adadelta]]</li>
      <li>[[Adafactor]]</li>
      <li>[[AdamW]]</li>
      <li>[[Adamax]]</li>
      <li>[[FTRL algorithm]]</li>
      <li>[[Lion algorithm]]</li>
      <li>[[LossScaleOptimizer]]</li>
      <li>[[Nadam]]</li>
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! 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="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;">Black-box Optimization</h2>
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| style="color:#000;padding:2px 5px 5px 15px" | <div id="mp-dyk">
       <li>[[Wing shape optimization]]</li>
       <li>[[Bayesian optimization]]</li>
       <li>[[Optimization in game theory]]</li>
       <li>[[Genetic algorithm]]</li>
       <li>[[Quantum computing for optimization]]</li>
       <li>[[Simulated annealing]]</li>
      <li>[[Particle swarm optimization]]</li>
      <li>[[Differential evolution]]</li>
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Latest revision as of 17:35, 15 December 2024

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

Emerging Applications

Mixed-Integer Linear Programming (MILP)

Mixed-Integer NonLinear Programming (MINLP)

Optimization under Uncertainty

Optimization for Machine Learning and Data Analytics

Black-box Optimization

Cornell Prof. Fengqi You Research Group