Optimization Techniques in Engineering
ME575/CE575: Optimization Techniques in Engineering (3 credit hours). This course covers theory and applications for optimization in engineering design. Topics include:
 Optimization Introduction
 Mathematical Modeling
 Unconstrained Optimization
 Discrete Optimization
 Genetic Algorithms
 Constrained Optimization
 Robust Optimization
 Dynamic Optimization
Both MATLAB and Python are used throughout the course as computational tools for implementing homework and exam problems and for the course projects. Tutorials in MATLAB and Python are provided as part of a separate computational tools course.
Professor: John D. Hedengren
Office: 8014222590, 350R CB Cell: 8014777341 Contact: john.hedengren [at] byu.edu

John Hedengren worked 5 years with ExxonMobil Chemical on Optimization solutions for the petrochemical industry. He conducts research in optimization methods, modeling systems, and applications in Chemical Engineering. The PRISM group is actively working on oil and gas drilling automation, reservoir engineering, process optimization, unmanned aerial vehicles, and systems biology. 
Book
Everyone will have access to the book (download PDFs). You will need to thoroughly understand everything in the chapters. Please read the appropriate section before coming to class as indicated on the 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 throughout 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 crosslisted 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.
Grading
Homework/Quizzes 
15% 
Participation 
5% 
Projects 
30% (15% Each) 
MidTerm Exam 
20% 
Final Exam 
30% 
Reading
Reading is essential to succeeding in this class. There are a number of resources that are available on this website 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 midterm and the final exam. These exams may be closed book and/or open book, inclass 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 offcampus 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 stepbystep 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.
Disability Resources
If you suspect or are aware that you have a disability, you are strongly encouraged to contact the University Accessibility Center (UAC) located at 2170 WSC (8014222767) as soon as possible. A disability is a physical or mental impairment that substantially limits one or more major life activities. Examples include vision or hearing impairments, physical disabilities, chronic illnesses, emotional disorders (e.g., depression, anxiety), learning disorders, and attention disorders (e.g., ADHD). When registering with the UAC, the disability will be evaluated and eligible students will receive assistance in obtaining reasonable University approved accommodations.