Nonlinear Optimization
6.7220J · Electrical Engineering and Computer Science, Sloan School of Management · Graduate · Spring 2025
Prof. Gabriele Farina
This course offers a unified analytical and computational approach to nonlinear optimization problems. Unconstrained optimization methods include gradient, conjugate direction, Newton, sub-gradient, and first-order methods. Constrained optimization methods include feasible directions, projection, interior point methods, and Lagrange multiplier methods. The curriculum covers convex analysis, Lagrangian relaxation, and nondifferentiable optimization, as well as applications in integer programming…
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Prof. Gabriele Farina. 6.7220J Nonlinear Optimization. Spring 2025. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: CC BY-NC-SA 4.0.
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