Optimization Methods | Sloan School of Management | MIT OpenCourseWare
This course introduces the principal algorithms for linear, network, discrete, nonlinear, dynamic optimization and optimal control. Emphasis is on methodology and the underlying mathematical structures. Topics include the simplex method, network flow methods, branch and bound and cutting plane methods for discrete optimization, optimality conditions for nonlinear optimization, interior point methods for convex optimization, Newton's method, heuristic methods, and dynamic programming and optimal control methods.
Course Description This course introduces the principal algorithms for linear, network, discrete, nonlinear, dynamic optimization and optimal control. Emphasis is on methodology and the underlying mathematical structures. Topics include the simplex method, network flow methods, branch and bound and cutting plane methods for discrete … This course introduces the principal algorithms for linear, network, discrete, nonlinear, dynamic optimization and optimal control. Emphasis is on methodology and the underlying mathematical structures. Topics include the simplex method, network flow methods,…
saved by
related reading
- Mathematical optimization - Wikipediaen.wikipedia.org
- bv_cvxbook.pdfweb.stanford.edu
- bv_cvxbook.pdfstanford.edu
- eecs127_reader.pdfeecs127.github.io
- SIAG on Optimization Views and News 33(1)siagoptimization.github.io
- Pareto front - Wikipediaen.wikipedia.org
- Tim Roughgarden's Lecture Notestimroughgarden.org
- EE364a: Convex Optimization Iweb.stanford.edu
- Games and Decision Makingecon.uiuc.edu
- 142_Luenberger.pdfsites.science.oregonstate.edu
- Control theory - Wikipediaen.wikipedia.org
- Convex Optimizationstat.cmu.edu