Course Description

Introduction to Engineering Optimization Techniques, ENGR 160

Introduction to formulating and solving optimization problems in engineering. Includes single-variable and multi-variable optimization; linear programming - simplex method; nonlinear optimization - gradient, steepest descent, Newton methods, and gradient projection methods. Solves various engineering optimization examples using MATLAB. Does not meet the technical elective requirement for Electrical Engineering students

Key Information

Fall Quarter 2017
Instruction start date: September 28, 2017
Instruction end date: December 8, 2017
Credit: 4 quarter units / 2.67 semester units credit
UC Riverside, Engineering

Course Credit:

Upon successful completion, all online courses offered through cross-enrollment provide UC unit credit. Some courses are approved for GE, major preparation and/or, major credit or can be used as a substitute for a course at your campus.

If "unit credit" is listed by your campus, consult your department, academic adviser or Student Affairs division to inquire about the petition process for more than unit credit for the course.

UC Berkeley:
Unit Credit



UC Davis:
Unit Credit

UC Irvine:
Unit Credit

UC Los Angeles:
Unit Credit

UC Merced:
Units toward Degree (see your adviser)

UC Riverside:
Major Requirement: Satisfies Technical Elective for most Electrical Engineering Majors

UC San Diego:
Unit Credit

UC San Francisco:
Unit Credit

UC Santa Barbara:
Unit Credit

UC Santa Cruz:
Unit Credit

Prerequisites

MATH 010A; either CS 010 or CS 010V or EE 020 or ME 018, or instructor approval.

More About The Course

Introduction to formulating and solving optimization problems in engineering. Single- and multi-variable optimization. Decision making and mathematical problem formulation. Formulating and solving linear optimization problems. Formulating and solving integer and mixed-integer optimization problems. Uncertainty and understanding decision making under uncertainty. Formulating and solving nonlinear optimization problems. Applications of optimization in engineering problems. Solving various optimization examples using MATLAB.

Course Creator

Hamed Mohsenian-Rad

Dr. Hamed Mohsenian-Rad is an Associate Professor of Electrical Engineering, an Associate Director of the Winston Chung Global Energy Center, and the Director of the Smart Grid Research Lab at the University of California, Riverside, CA, USA. His research interests include modeling, data analytics, control, and optimization of power systems and smart grids. He has received the National Science Foundation (NSF) CAREER Award, a Best Paper Award from the IEEE Power and Energy Society (PES) General Meeting, and a Best Paper Award from the IEEE International Conference on Smart Grid Communications. Two of his journal papers are among the top five most cited articles in the field of Smart Grid, each with over 1000 citations. Dr. Mohsenian-Rad received his Ph.D. degree in Electrical and Computer Engineering from the University of British Columbia, Vancouver, Canada, in 2008. He currently serves as an Editor for the IEEE Transactions on Smart Grid and IEEE Power Engineering Letters.

Dr. Hamed Mohsenian-Rad is an Associate Professor of Electrical Engineering, an Associate Director of the Winston Chung Global Energy Center, and the Director of the Smart Grid Research Lab at the University of California, Riverside, CA, USA. His research interests include modeling, data analytics, control, and optimization of power systems and smart grids. He has received the National ...

Dr. Hamed Mohsenian-Rad is an Associate Professor of Electrical Engineering, an Associate Director of the Winston Chung Global Energy Center, and the Director of the Smart Grid Research Lab at the University of California, Riverside, CA, USA. His research interests include modeling, data analytics, control, and optimization of power systems and smart grids. He has received the National Science Foundation (NSF) CAREER Award, a Best Paper Award from the IEEE Power and Energy Society (PES) General Meeting, and a Best Paper Award from the IEEE International Conference on Smart Grid Communications. Two of his journal papers are among the top five most cited articles in the field of Smart Grid, each with over 1000 citations. Dr. Mohsenian-Rad received his Ph.D. degree in Electrical and Computer Engineering from the University of British Columbia, Vancouver, Canada, in 2008. He currently serves as an Editor for the IEEE Transactions on Smart Grid and IEEE Power Engineering Letters.


Instructor of Term

Hamed Mohsenian-Rad
hamed@ee.ucr.edu

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