MATH 164
Optimization
Description: Lecture, three hours; discussion, one hour. Enforced requisites: courses 115A, 131A. Not open for credit to students with credit for former Electrical Engineering 136. Fundamentals of optimization. Linear programming: basic solutions, simplex method, duality theory. Unconstrained optimization, Newton method for minimization. Nonlinear programming, optimality conditions for constrained problems. Additional topics from linear and nonlinear programming. P/NP or letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
Spring 2020 - Professor Li is not the best lecturer and I often found myself a little confused on where in the book we were. However, his tests are extremely similar to the homework and definitely manageable. The homework is in general pretty doable although you do have to code it with LaTeX which can be a little tedious and time consuming. In addition, some problems require you to use MATLAB which was a little difficult for me as someone who had never used MATLAB before. I would say expect to dedicate some time to this class early on in the quarter if you need a review on linear algebra or aren't familiar with LaTeX or MATLAB.
Spring 2020 - Professor Li is not the best lecturer and I often found myself a little confused on where in the book we were. However, his tests are extremely similar to the homework and definitely manageable. The homework is in general pretty doable although you do have to code it with LaTeX which can be a little tedious and time consuming. In addition, some problems require you to use MATLAB which was a little difficult for me as someone who had never used MATLAB before. I would say expect to dedicate some time to this class early on in the quarter if you need a review on linear algebra or aren't familiar with LaTeX or MATLAB.
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