Max-Cut Problem: SDP Relaxation and Randomized Rounding

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Explores the Stein algorithm for polynomial identity testing and the minimization of a cut problem.

Covers fundamental concepts of optimization and operations research, exploring real-world examples and key topics over a semester.

Covers optimization principles, including linear optimization, networks, and concrete research examples in transportation.

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Explains the process of finding an initial Basic Feasible Solution for linear optimization problems using the Simplex Algorithm.

Explores Semidefinite Programming formulations, SDP relaxations, and optimization strategies with convergence guarantees.