ME 575 - Optimization

• Syllabus
• Book
• Schedule

Mechanical Engineering 575 / Civil Engineering 575

 Optimization Techniques in Engineering
 MWF - 3:00-3:50 pm, 254 CB

Professor

 John D. Hedengren
 Office: 801-422-2590, 350R CB,
 Cell: 801-477-7341
 john.hedengren [at] byu.edu
 Office hours M, W, Fr 4-5 PM, 350R Clyde Building

About the Professor: John Hedengren worked 5 years with ExxonMobil Chemical on optimization and process control solutions for the petrochemical industry. He conducts research in optimization methods, modeling systems, and applications in Mechanical, Civil, Electrical, and Chemical Engineering.

TA/Graders:

 Jose Mojica
 jlmojica [at] gmail.com
 Office hours Tu / Th 10-11 AM in 308 CB

 Nathan Edwards
 nathanedwards8 [at] gmail.com
 Office hours We / Fr 2-3 PM in 308 CB

OptdesX Support

 Abraham Lee
 tisimst [at] gmail.com

Book

We will use a set of course notes that take the place of the book. Everyone will have access to these notes through this web-site. You will need to thoroughly understand everything in the notes. Please read the notes before coming to class and I will indicate the reading on the course schedule.

References

• Belegundu A. and T. Chandrupatla Optimization Concepts and Applications in Engineering, Prentice Hall, 1999.
• Gen, M. and R. Cheng, Genetic Algorithms and Engineering Optimization, Wiley, 2000.
• Edgar, T.F., Himmelblau, D.M., and L.S. Lasdon, Optimization of Chemical Processes, McGraw Hill, 2001. Download PDF
• Fletcher R., Practical Methods of Optimization Volumes 1,2, John Wiley 1980, 1981.
• Luenberger and Ye, Linear and Nonlinear Programming Third Edition, Springer, 2008.

Recitation Sessions

As needed through-out the semester. The Teaching Assistants will conduct the recitation sessions. Generally they will be held:

• Before exams
• To help work through difficult project issues
• For additional class time

Catalog Description

ME 575: Optimization Techniques in Engineering (3 credit hours). Also cross-listed as CE EN 575. Application of computer optimization techniques to constrained engineering design. Theory and application of unconstrained and constrained nonlinear algorithms. Genetic algorithms. Robust design methods. Prerequisite: MATH 302; C, C++, or similar computer language.

Course Objectives

Grading

Reading

Reading is essential to succeeding in this class. There are a number of resources that are available on this web-site or through external sources.

Quizzes

Unannounced quizzes will be given on the assigned reading material for that day. The number of quizzes will increase as student preparation for classes decreases. Motto: BE PREPARED! Quizzes will not be rescheduled, and extra credit is not available. Quizzes count for a homework grade each. The quizzes are intended to: 1) provide an opportunity for you to practice responding to questions under time pressure, 2) provide encouragement for you to keep up with the course material, 3) encourage attendance.

Exams

There will be a mid-term and the final exam. These exams may be closed book and/or open book, in-class or in the testing center, as specified by the instructor prior to the exam. Exams will only be given after the scheduled date by special permission. Students with conflicts should arrange to take the exam prior to the scheduled date.

Project

You will be required to complete two group projects. Groups will consist of 3 students and one report will be submitted for the group. Each group member is to fully participate. I will provide suggestions or you can do something of your own interest or something that is integrated with a campus or off-campus research project.

Computer Tools

One of the most common questions that I receive from students who would like to take this class is, "How much programming experience is required to succeed in the class?"

To address this concern, we have prepared software tutorials that assume very little knowledge of programming. There are also many excellent resources on the internet that give tutorial introductions to programming. Those students who have no or little programming experience can review these step-by-step instructional videos to gain some of the required background. We can also hold recitation sessions in a computer lab outside of normal class times if there is need.

This is an optimization course, not a programming course, but some familiarity with MATLAB, Python, C++, or equivalent programming language is required to perform assignments, projects, and exams. Students who complete the course will gain experience in at least one of these programming languages.

Citizenship

I will come prepared to each class, ready to help explain the material covered in the reading. I appreciate attentive students who respect my time and the time of other students.

Study Habits

Grade Expectations

A Read material in advance, be attentive and ask questions in lectures, understand and do all homework on time, study hard for exams well before the exam starts, work hard and perform well on exams and the class projects.

B Skim material in advance, attend lectures and try to stay awake, depend on TA for homework help, casually study for the exam by working the practice exam instead of learning concepts.

C Never read book, work on other homework during class, skip some homework assignments, start cramming for the exam the night before the exam.

D Skip class, don't turn in homework or turn it in late, start learning during the exam.