Modeling and Optimization in Systems Engineering

ENSC 460 (99-3)

Course Description

This course provides an introduction to mathematical models and optimization methods in systems engineering. Topics include algebraic and geometric representation of optimization models, gradient methods for unconstrained optimization, computational methods for nonlinear and linear constrained optimization models, stochastic system models based on Markov chains, models and computational techniques for discrete optimization, and multi-agent models based on holonic systems. Examples are selected from robotics, manufacturing, telecommunications, transportation, and other systems engineering disciplines. Laboratory exercises provide familiarization with the use of optimization software.

Course Objectives

This course is an upper division elective in the Systems Option of Engineering Science. It is intended to provide students with a knowledge of methods for formulating and solving optimization models in systems engineering. It provides background for the design and analysis of complex systems studied in ENSC 320, ENSC 383, ENSC 429, ENSC 483, ENSC 488, and related engineering science courses.

Prerequisites

Required: MATH 232, MATH 251, and STAT 270

Instructor

William A. Gruver

E-mail: gruver@cs.sfu.ca

Tel: 291-4339

Office: ASB 9807

Office hours: by appointment (contact by e-mail)

Lecture Time and Place

Tue 1330-1420 in WMX 3255

Thu 1230-1420 in AQ 5007

References

1. *F. Hillier and G. Lieberman, Introduction to Operations Research, McGraw-Hill, 1990.
2. *R. Rardin, Optimization in Operations Research, Prentice Hall, 1998.
3. A. Ravindran, D. Phillips, and J. Solberg, Operations Research, Principles and Practice, John Wiley & Sons, 1987.
4. A. Belegundu and T. R. Chandrapatla, Optimization Concepts and Applications in Engineering, PRence Hall, 1999.
5. D. G. Luenberger, Introduction to Linear and Nonlinear Programming, Addison Wesley, 1984.
6. G. V. Reklaitis, A. Ravindran, and K. M. Ragsdell, Engineering Optimization: Methods and Applications, John Wiley & Sons, 1983.
7. T. Coleman, M. Brace, and A. Grace, User’s Guide for the Optimization Toolbox, Math Works, Inc., 1999.

References 1, 2 and 3 will be held on reserve in the SFU Library. Reference 6 is available in the lab.

Reference 1 and 2 are recommended texts that are available at the SFU Bookstore.

Grading Policy

General Information

Class and Exam Attendance: You are responsible for all business conducted during the scheduled class period, including announcements that may be given. Failure to take the mid term exams or the final exam during the assigned class period will result in a grade of zero being recorded unless you have personally contacted me by e-mail before the exam. Make-up exams may be given only under exceptional circumstances.

Homework Assignments: The homework is intended to reinforce the major concepts and to serve as a measure of how well you understand the course. The homework, however, is not necessarily representative of questions that will be asked on the exams.

Laboratory Exercises: The homework will include optimization problems that require the use of computational algorithms. To solve these problems you may use preprogrammed software, write your own program using MATLAB commands, code the problems in a general purpose high-level programming language. MATLAB Optimization Toolbox. MATLAB Release 11 Version 5.3 is accessible from the LabNet NT workstations and it is also available on the CSSNet. Students registered in ENSC 460 may install MATLAB temporarily on their home PCs. See http://www.ensc.sfu.ca/reference/matlab/matlab.html for details. The General Algebraic Modeling System (GAMS), a high-level modeling system for mathematical programming problems, is available for free download from http://www.gams.com/. Optimization software also can be obtained from the Optimization Technology Center, http://www-fp.mcs.anl.gov/otc/Guide/SoftwareGuide/.

Exams: Two mid term exams will be held in class. The exams will be one hour in length and emphasize comprehension of the material not memorization. You may bring to the exams a single 8.5"x11" page of handwritten notes on either side. You must show all work performed on an exam to receive full credit. If I cannot follow or read your work, you may receive no credit.

Project Report: This course will require that you complete a project that involves finding and elaborating upon an application of optimization methods studied in this course, including model development, preparing data, and solving the application. The application may be based on a co-op assignment or it may be adapted from a journal article in the library. You may work jointly with at most one other student on the project, however, individual reports will be required from each person. A short 1-2 page description of your project must be submitted as a homework assignment. The final project report should be 8-12 pages.

Office Hours: By appointment. To arrange a meeting, contact me by e-mail gruver@cs.sfu.ca. I often reply on the same day.

E-Mail Announcements: It is essential that you check your e-mail frequently for messages about the course. Important messages concerning changes in class meetings, topics and schedule of exams, and help on homework assignments may be waiting for you.

Web page: Revisions of the course schedule and assignments will be posted on the ENSC460 web page http://www.ensc.sfu.ca/research/idea/courses/ENSC460.htm. Please check this page frequently for updates.

Syllabus

Updated: November 15, 1999