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To view the Summer 2020 Academic Calendar go to www.sfu.ca/students/calendar/2020/summer.html

Department of Mathematics | Faculty of Science Simon Fraser University Calendar | Fall 2020

Operations Research Major

Bachelor of Science

This program prepares students for careers in industry or a variety of graduate and professional programs.

Prerequisite Grade Requirement

To enroll in a course offered by the Department of Mathematics, a student must obtain a grade of C- or better in each prerequisite course. Some courses may require higher prerequisite grades. Check the MATH course’s Calendar description for details.

Students will not normally be permitted to enroll in any course for which a D grade or lower was obtained in any prerequisite. No student may complete, for further credit, any course offered by the Department of Mathematics which is a prerequisite for a course the student has already completed with a grade of C- or higher, without permission of the department.

Program Requirements

The program requires the completion of 120 units which includes a Faculty of Science requirement of a minimum of 28 upper division units, and additional upper division units to total a minimum of 44 upper division units (excluding EDUC 401, 407).

The specific program requirements are divided into three parts: required lower division courses, required upper division courses, and completion of an interdisciplinary requirement.

In addition to the program requirements set out below, general university and Faculty of Science regulations must be met.

Computing science courses that are completed in the operations research major program will count towards the requirement that 12 units must be completed from outside of the Faculty of Science.

A minimum program 2.00 cumulative grade point average (CGPA) must be obtained on the overall major program requirements, as well as a minimum program 2.00 grade point average in the upper division major courses.

Lower Division Requirements

Students complete

both of

CMPT 120 - Introduction to Computing Science and Programming I (3)

An elementary introduction to computing science and computer programming, suitable for students with little or no programming background. Students will learn fundamental concepts and terminology of computing science, acquire elementary skills for programming in a high-level language and be exposed to diverse fields within, and applications of computing science. Topics will include: pseudocode, data types and control structures, fundamental algorithms, computability and complexity, computer architecture, and history of computing science. Treatment is informal and programming is presented as a problem-solving tool. Prerequisite: BC Math 12 or equivalent is recommended. Students with credit for CMPT 102, 128, 130 or 166 may not take this course for further credit. Students who have taken CMPT 125, 129, 130 or 135 first may not then take this course for further credit. Quantitative/Breadth-Science.

Section Instructor Day/Time Location
D100 Diana Cukierman
Mo, We, Fr 10:30 AM – 11:20 AM
REMOTE LEARNING, Burnaby
D200 Angelica Lim
Mo 3:30 PM – 4:20 PM
We, Fr 3:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
REMOTE LEARNING, Burnaby
D300 Harinder Khangura
Valentine Kabanets
Mo, We, Fr 10:30 AM – 11:20 AM
REMOTE LEARNING, Burnaby
D301 Mo 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby
D302 Harinder Khangura
Mo 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby
D303 Harinder Khangura
Mo 2:30 PM – 3:20 PM
REMOTE LEARNING, Burnaby
D304 Harinder Khangura
Mo 2:30 PM – 3:20 PM
REMOTE LEARNING, Burnaby
D305 Harinder Khangura
Mo 3:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
D306 Harinder Khangura
Mo 3:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
D307 Harinder Khangura
Mo 4:30 PM – 5:20 PM
REMOTE LEARNING, Burnaby
D308 Harinder Khangura
Mo 4:30 PM – 5:20 PM
REMOTE LEARNING, Burnaby
D400 Victor Cheung
Mo, We, Fr 11:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
CMPT 129 - Introduction to Computing Science and Programming for Mathematics and Statistics (3)

A second course in computing science and programming intended for students studying mathematics, statistics or actuarial science and suitable for students who already have some background in computing science and programming. Topics include: a review of the basic elements of programming: use and implementation of elementary data structures and algorithms; fundamental algorithms and problem solving; basic object-oriented programming and software design; computation and computabiiity and specification and program correctness. Prerequisite: CMPT 102 or CMPT 120. Students with credit for CMPT 125 or 135 may not take this course for further credit. Quantitative.

(Students transferring into a math program should contact the math undergraduate advisor if they have already completed equivalent courses.)

or both of

CMPT 130 - Introduction to Computer Programming I (3)

An introduction to computing science and computer programming, using a systems oriented language, such as C or C++. This course introduces basic computing science concepts. Topics will include: elementary data types, control structures, functions, arrays and strings, fundamental algorithms, computer organization and memory management. Prerequisite: BC Math 12 (or equivalent, or any of MATH 100, 150, 151, 154, or 157). Students with credit for CMPT 102, 120, 128 or 166 may not take this course for further credit. Students who have taken CMPT 125, 129 or 135 first may not then take this course for further credit. Quantitative/Breadth-Science.

Section Instructor Day/Time Location
D100 John Edgar
Mo, We, Fr 11:30 AM – 12:30 PM
REMOTE LEARNING, Burnaby
D101 John Edgar
Tu 11:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
D102 John Edgar
Tu 11:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
D103 John Edgar
Tu 12:30 PM – 1:20 PM
REMOTE LEARNING, Burnaby
D104 John Edgar
Tu 12:30 PM – 1:20 PM
REMOTE LEARNING, Burnaby
D105 John Edgar
Tu 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby
D106 John Edgar
Tu 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby
D200 Brian Fraser
Mo, We, Fr 2:30 PM – 3:20 PM
REMOTE LEARNING, Burnaby
D201 Brian Fraser
Fr 10:30 AM – 11:20 AM
REMOTE LEARNING, Burnaby
D202 Brian Fraser
Fr 10:30 AM – 11:20 AM
REMOTE LEARNING, Burnaby
D203 Brian Fraser
Fr 11:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
D204 Brian Fraser
Fr 11:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
D205 Brian Fraser
Fr 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby
D206 Brian Fraser
Fr 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby
CMPT 135 - Introduction to Computer Programming II (3)

A second course in systems-oriented programming and computing science that builds upon the foundation set in CMPT 130 using a systems-oriented language such as C or C++. Topics: a review of the basic elements of programming; introduction to object-oriented programming (OOP); techniques for designing and testing programs; use and implementation of elementary data structures and algorithms; introduction to embedded systems programming. Prerequisite: CMPT 130. Students with credit for CMPT 125, 126, or 129 may not take this course for further credit. Quantitative.

and all of

CMPT 225 - Data Structures and Programming (3)

Introduction to a variety of practical and important data structures and methods for implementation and for experimental and analytical evaluation. Topics include: stacks, queues and lists; search trees; hash tables and algorithms; efficient sorting; object-oriented programming; time and space efficiency analysis; and experimental evaluation. Prerequisite: (MACM 101 and ((CMPT 125 and 127), CMPT 129 or CMPT 135)) or (ENSC 251 and ENSC 252). Quantitative.

Section Instructor Day/Time Location
D100 David Mitchell
Mo 9:30 AM – 10:20 AM
We, Fr 9:30 AM – 10:20 AM
REMOTE LEARNING, Burnaby
REMOTE LEARNING, Burnaby
D101 David Mitchell
We 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby
D102 David Mitchell
We 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby
D103 David Mitchell
We 2:30 PM – 3:20 PM
REMOTE LEARNING, Burnaby
D104 David Mitchell
We 2:30 PM – 3:20 PM
REMOTE LEARNING, Burnaby
D105 David Mitchell
We 3:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
D106 David Mitchell
We 3:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
D107 David Mitchell
We 4:30 PM – 5:20 PM
REMOTE LEARNING, Burnaby
D108 David Mitchell
We 4:30 PM – 5:20 PM
REMOTE LEARNING, Burnaby
D200 Thomas Shermer
Mo, We, Fr 3:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
D201 Thomas Shermer
We 8:30 AM – 9:20 AM
REMOTE LEARNING, Burnaby
D202 Thomas Shermer
We 8:30 AM – 9:20 AM
REMOTE LEARNING, Burnaby
D203 We 9:30 AM – 10:20 AM
REMOTE LEARNING, Burnaby
D204 Thomas Shermer
We 9:30 AM – 10:20 AM
REMOTE LEARNING, Burnaby
D205 Thomas Shermer
We 10:30 AM – 11:20 AM
REMOTE LEARNING, Burnaby
D206 Thomas Shermer
We 10:30 AM – 11:20 AM
REMOTE LEARNING, Burnaby
D207 Thomas Shermer
We 11:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
D208 Thomas Shermer
We 11:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
MACM 101 - Discrete Mathematics I (3)

Introduction to counting, induction, automata theory, formal reasoning, modular arithmetic. Prerequisite: BC Math 12 (or equivalent), or any of MATH 100, 150, 151, 154, 157. Quantitative/Breadth-Science.

Section Instructor Day/Time Location
D100 Kay C Wiese
Mo, We, Fr 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby
D101 Kay C Wiese
Th 8:30 AM – 9:20 AM
REMOTE LEARNING, Burnaby
D102 Kay C Wiese
Th 8:30 AM – 9:20 AM
REMOTE LEARNING, Burnaby
D103 Kay C Wiese
Th 9:30 AM – 10:20 AM
REMOTE LEARNING, Burnaby
D104 Kay C Wiese
Th 9:30 AM – 10:20 AM
REMOTE LEARNING, Burnaby
D105 Kay C Wiese
Th 10:30 AM – 11:20 AM
REMOTE LEARNING, Burnaby
D106 Kay C Wiese
Th 10:30 AM – 11:20 AM
REMOTE LEARNING, Burnaby
D107 Kay C Wiese
Th 11:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
D108 Kay C Wiese
Th 11:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
D200 Binay Bhattacharya
Valentine Kabanets
Mo, We, Fr 12:30 PM – 1:20 PM
REMOTE LEARNING, Burnaby
D201 Binay Bhattacharya
We 2:30 PM – 3:20 PM
REMOTE LEARNING, Burnaby
D202 Binay Bhattacharya
We 2:30 PM – 3:20 PM
REMOTE LEARNING, Burnaby
D203 Binay Bhattacharya
We 3:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
D204 Binay Bhattacharya
We 3:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
D205 Binay Bhattacharya
We 4:30 PM – 5:20 PM
REMOTE LEARNING, Burnaby
D206 Binay Bhattacharya
We 4:30 PM – 5:20 PM
REMOTE LEARNING, Burnaby
D207 Binay Bhattacharya
We 5:30 PM – 6:20 PM
REMOTE LEARNING, Burnaby
D208 Binay Bhattacharya
We 5:30 PM – 6:20 PM
REMOTE LEARNING, Burnaby
D300 Andrei Bulatov
Mo, We 2:30 PM – 3:20 PM
Fr 2:30 PM – 3:20 PM
REMOTE LEARNING, Burnaby
REMOTE LEARNING, Burnaby
D301 Andrei Bulatov
Th 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby
D302 Andrei Bulatov
Th 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby
D303 Andrei Bulatov
Th 2:30 PM – 3:20 PM
REMOTE LEARNING, Burnaby
D304 Andrei Bulatov
Th 2:30 PM – 3:20 PM
REMOTE LEARNING, Burnaby
D305 Andrei Bulatov
Th 3:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
D306 Andrei Bulatov
Th 3:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
D307 Andrei Bulatov
Th 4:30 PM – 5:20 PM
REMOTE LEARNING, Burnaby
D308 Andrei Bulatov
Th 4:30 PM – 5:20 PM
REMOTE LEARNING, Burnaby
MACM 201 - Discrete Mathematics II (3)

A continuation of MACM 101. Topics covered include graph theory, trees, inclusion-exclusion, generating functions, recurrence relations, and optimization and matching. Prerequisite: MACM 101 or (ENSC 251 and one of MATH 232 or MATH 240). Quantitative.

Section Instructor Day/Time Location
D100 Jamie Mulholland
Mo, We, Fr 12:30 PM – 1:20 PM
REMOTE LEARNING, Burnaby
D200 Michael Monagan
Mo, We, Fr 12:30 PM – 1:20 PM
REMOTE LEARNING, Burnaby
OP01 TBD
OP02 TBD
MATH 208W - Introduction to Operations Research (3)

Introduction to methods of operations research: linear and nonlinear programming, simulation, and heuristic methods. Applications to transportation, assignment, scheduling, and game theory. Exposure to mathematical models of industry and technology. Emphasis on computation for analysis and simulation. Prerequisite: MATH 150 or 151 or 154 or 157. Students with credit for MATH 208 may not take this course for further credit. Writing/Quantitative.

MATH 251 - Calculus III (3)

Rectangular, cylindrical and spherical coordinates. Vectors, lines, planes, cylinders, quadric surfaces. Vector functions, curves, motion in space. Differential and integral calculus of several variables. Vector fields, line integrals, fundamental theorem for line integrals, Green's theorem. Prerequisite: MATH 152; or MATH 155 or MATH 158 with a grade of at least B. Recommended: It is recommended that MATH 240 or 232 be taken before or concurrently with MATH 251. Quantitative.

Section Instructor Day/Time Location
D100 Weiran Sun
Mo, We, Fr 8:30 AM – 9:20 AM
REMOTE LEARNING, Burnaby
D200 Vijaykumar Singh
Mo, We, Fr 8:30 AM – 9:20 AM
REMOTE LEARNING, Burnaby
D300 David Muraki
Mo, We, Fr 8:30 AM – 9:20 AM
REMOTE LEARNING, Burnaby
OP01 TBD
OP02 TBD
OP03 TBD
STAT 270 - Introduction to Probability and Statistics (3)

Basic laws of probability, sample distributions. Introduction to statistical inference and applications. Prerequisite: or Corequisite: MATH 152 or 155 or 158. Students wishing an intuitive appreciation of a broad range of statistical strategies may wish to take STAT 100 first. Quantitative.

Section Instructor Day/Time Location
D100 Jinko Graham
Mo, We, Fr 9:30 AM – 10:20 AM
REMOTE LEARNING, Burnaby
OP01 TBD
STAT 285 - Intermediate Probability and Statistics (3)

This course is a continuation of STAT 270. Review of probability models. Procedures for statistical inference using survey results and experimental data. Statistical model building. Elementary design of experiments. Regression methods. Introduction to categorical data analysis. Prerequisite: STAT 270 and one of MATH 152, MATH 155, or MATH 158. Quantitative.

Section Instructor Day/Time Location
D100 Liangliang Wang
Tu 10:30 AM – 12:20 PM
Fr 10:30 AM – 11:20 AM
REMOTE LEARNING, Burnaby
REMOTE LEARNING, Burnaby
D101 Liangliang Wang
Fr 2:30 PM – 3:20 PM
REMOTE LEARNING, Burnaby
D102 Liangliang Wang
Fr 3:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
D103 Liangliang Wang
Fr 4:30 PM – 5:20 PM
REMOTE LEARNING, Burnaby

and one of

MATH 150 - Calculus I with Review (4)

Designed for students specializing in mathematics, physics, chemistry, computing science and engineering. Topics as for Math 151 with a more extensive review of functions, their properties and their graphs. Recommended for students with no previous knowledge of Calculus. In addition to regularly scheduled lectures, students enrolled in this course are encouraged to come for assistance to the Calculus Workshop (Burnaby), or Math Open Lab (Surrey). Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least B+, or MATH 100 with a grade of at least B-, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 151, 154 or 157 may not take MATH 150 for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Veselin Jungic
Mo, Tu, We, Fr 8:30 AM – 9:20 AM
REMOTE LEARNING, Burnaby
D200 Natalia Kouzniak
Mo, Tu, We, Fr 8:30 AM – 9:20 AM
REMOTE LEARNING, Burnaby
OP01 TBD
OP02 TBD
MATH 151 - Calculus I (3)

Designed for students specializing in mathematics, physics, chemistry, computing science and engineering. Logarithmic and exponential functions, trigonometric functions, inverse functions. Limits, continuity, and derivatives. Techniques of differentiation, including logarithmic and implicit differentiation. The Mean Value Theorem. Applications of differentiation including extrema, curve sketching, Newton's method. Introduction to modeling with differential equations. Polar coordinates, parametric curves. Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least A, or MATH 100 with a grade of at least B, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 150, 154 or 157 may not take MATH 151 for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Nils Bruin
Mo, We, Fr 8:30 AM – 9:20 AM
REMOTE LEARNING, Burnaby
D200 Randall Pyke
Mo, We, Fr 9:30 AM – 10:20 AM
REMOTE LEARNING, Burnaby
OP01 TBD
OP02 TBD
MATH 154 - Calculus I for the Biological Sciences (3) *

Designed for students specializing in the biological and medical sciences. Topics include: limits, growth rate and the derivative; elementary functions, optimization and approximation methods, and their applications; mathematical models of biological processes. Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least B, or MATH 100 with a grade of at least C, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 150, 151 or 157 may not take MATH 154 for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Justin Chan
Mo, We, Fr 8:30 AM – 9:20 AM
REMOTE LEARNING, Burnaby
D200 Luis Goddyn
Mo, We, Fr 9:30 AM – 10:20 AM
REMOTE LEARNING, Burnaby
OP01 TBD
OP02 TBD
MATH 157 - Calculus I for the Social Sciences (3) *

Designed for students specializing in business or the social sciences. Topics include: limits, growth rate and the derivative; logarithmic, exponential and trigonometric functions and their application to business, economics, optimization and approximation methods; introduction to functions of several variables with emphasis on partial derivatives and extrema. Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least B, or MATH 100 with a grade of at least C, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 150, 151 or 154 may not take MATH 157 for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Stephen Choi
Mo, We, Fr 11:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
D200 Randall Pyke
Mo, We, Fr 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby
OP01 TBD
OP02 TBD

and one of

MATH 152 - Calculus II (3)

Riemann sum, Fundamental Theorem of Calculus, definite, indefinite and improper integrals, approximate integration, integration techniques, applications of integration. First-order separable differential equations and growth models. Sequences and series, series tests, power series, convergence and applications of power series. Prerequisite: MATH 150 or 151; or MATH 154 or 157 with a grade of at least B. Students with credit for MATH 155 or 158 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Brenda Davison
Mo, We, Fr 8:30 AM – 9:20 AM
REMOTE LEARNING, Burnaby
OP01 TBD
MATH 155 - Calculus II for the Biological Sciences (3) *

Designed for students specializing in the biological and medical sciences. Topics include: the integral, partial derivatives, differential equations, linear systems, and their applications; mathematical models of biological processes. Prerequisite: MATH 150, 151 or 154; or MATH 157 with a grade of at least B. Students with credit for MATH 152 or 158 may not take this course for further credit. Quantitative.

MATH 158 - Calculus II for the Social Sciences (3) *

Designed for students specializing in business or the social sciences. Topics include: theory of integration, integration techniques, applications of integration; functions of several variables with emphasis on double and triple integrals and their applications; introduction to differential equations with emphasis on some special first-order equations and their applications; sequences and series. Prerequisite: MATH 150 or 151 or 154 or 157. Students with credit for MATH 152 or 155 may not take MATH 158 for further credit. Quantitative.

and one of

MATH 232 - Applied Linear Algebra (3) *

Linear equations, matrices, determinants. Introduction to vector spaces and linear transformations and bases. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. An emphasis on applications involving matrix and vector calculations. Prerequisite: MATH 150 or 151; or MACM 101; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 240 make not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Brenda Davison
Mo, We, Fr 11:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
D200 Randall Pyke
Mo, We, Fr 3:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
OP01 TBD
OP02 TBD
MATH 240 - Algebra I: Linear Algebra (3)

Linear equations, matrices, determinants. Real and abstract vector spaces, subspaces and linear transformations; basis and change of basis. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. Applications. Subject is presented with an abstract emphasis and includes proofs of the basic theorems. Prerequisite: MATH 150 or 151; or MACM 101; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 232 cannot take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Sophie Burrill
Mo, We, Fr 11:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
OP01 TBD

* with a B grade or better

Upper Division Requirements

Students complete all of

MATH 308 - Linear Optimization (3)

Linear programming modelling. The simplex method and its variants. Duality theory. Post-optimality analysis. Applications and software. Additional topics may include: game theory, network simplex algorithm, and convex sets. Prerequisite: MATH 150, 151, 154, or 157 and MATH 240 or 232. Quantitative.

Section Instructor Day/Time Location
D100 Abraham Punnen
Mo 2:30 PM – 4:20 PM
We 2:30 PM – 3:20 PM
REMOTE LEARNING, Burnaby
REMOTE LEARNING, Burnaby
D101 Th 3:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
D102 Th 9:30 AM – 10:20 AM
REMOTE LEARNING, Burnaby
MATH 348 - Introduction to Probabilistic Models (3)

Review of the basics of probability, including sample space, random variables, expectation and conditioning. Applications of Markov chains, the exponential distribution and the Poisson process from science and industry. Applications may include inventory theory, queuing, forecasting, scheduling and simulation. Prerequisite: STAT 270 and (MATH 232 or MATH 240). Quantitative.

MATH 402W - Operations Research Clinic (4)

Problems from operations research will be presented and discussed in class. Students will also work on a problem of their choice and present their solution in report form as well as a presentation. Prerequisite: MATH 308 and STAT 285. Writing/Quantitative.

and four of

MATH 309 - Continuous Optimization (3)

Theoretical and computational methods for investigating the minimum of a function of several real variables with and without inequality constraints. Applications to operations research, model fitting, and economic theory. Prerequisite: MATH 232 or 240, and 251. Quantitative.

MATH 408 - Discrete Optimization (3)

Model building using integer variables, computer solution, relaxations and lower bounds, heuristics and upper bounds, branch and bound algorithms, cutting plane algorithms, valid inequalities and facets, branch and cut algorithms, Lagrangian duality, column generation of algorithms, heuristics algorithms and analysis. Prerequisite: MATH 308. Quantitative.

Section Instructor Day/Time Location
D100 Tamon Stephen
Mo, We, Fr 9:30 AM – 10:20 AM
REMOTE LEARNING, Burnaby
MATH 448 - Network Flows (3)

Applications of network flow models; flow decomposition; polynomial algorithms for shortest paths, maximum flows and minimum costs flows; convex cost flows; generalized flows, multi-commodity flows. Prerequisite: MATH 308. Recommended: MATH 345. Quantitative.

STAT 350 - Linear Models in Applied Statistics (3)

Theory and application of linear regression. Normal distribution theory. Hypothesis tests and confidence intervals. Model selection. Model diagnostics. Introduction to weighted least squares and generalized linear models. Prerequisite: STAT 285, MATH 251, and one of MATH 232 or MATH 240. Quantitative.

Section Instructor Day/Time Location
D100 Derek Bingham
Tu 10:30 AM – 12:20 PM
Fr 10:30 AM – 11:20 AM
REMOTE LEARNING, Burnaby
REMOTE LEARNING, Burnaby
D101 Derek Bingham
Tu 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby
D102 Derek Bingham
Fr 9:30 AM – 10:20 AM
REMOTE LEARNING, Burnaby
D103 Derek Bingham
Fr 11:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
STAT 380 - Introduction to Stochastic Processes (3)

Review of discrete and continuous probability models and relationships between them. Exploration of conditioning and conditional expectation. Markov chains. Random walks. Continuous time processes. Poisson process. Markov processes. Gaussian processes. Prerequisite: STAT 330, or all of: STAT 285, MATH 208W, and MATH 251. Quantitative.

and at least one of

CMPT 305 - Computer Simulation and Modelling (3)

This course is an introduction to the modelling, analysis, and computer simulation of complex systems. Topics include analytic modelling, discrete event simulation, experimental design, random number generation, and statistical analysis. Prerequisite: CMPT 225, (MACM 101 or (ENSC 251 and ENSC 252)) and STAT 270.

CMPT 307 - Data Structures and Algorithms (3)

Analysis and design of data structures for lists, sets, trees, dictionaries, and priority queues. A selection of topics chosen from sorting, memory management, graphs and graph algorithms. Prerequisite: CMPT 225, MACM 201, MATH 151 (or MATH 150), and MATH 232 or 240.

Section Instructor Day/Time Location
D100 Thomas Shermer
Mo, We, Fr 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby
MACM 316 - Numerical Analysis I (3)

A presentation of the problems commonly arising in numerical analysis and scientific computing and the basic methods for their solutions. Prerequisite: MATH 152 or 155 or 158, and MATH 232 or 240, and computing experience. Quantitative.

Section Instructor Day/Time Location
D100 John Stockie
Mo, We, Fr 12:30 PM – 1:20 PM
REMOTE LEARNING, Burnaby
D101 We 2:30 PM – 3:20 PM
REMOTE LEARNING, Burnaby
D102 We 3:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
D103 We 4:30 PM – 5:20 PM
REMOTE LEARNING, Burnaby
D104 Th 9:30 AM – 10:20 AM
REMOTE LEARNING, Burnaby
D105 Th 10:30 AM – 11:20 AM
REMOTE LEARNING, Burnaby
D106 Th 11:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
MATH 343 - Applied Discrete Mathematics (3)

Structures and algorithms, generating elementary combinatorial objects, counting (integer partitions, set partitions, Catalan families), backtracking algorithms, branch and bound, heuristic search algorithms. Prerequisite: MACM 201 (with a grade of at least B-). Recommended: knowledge of a programming language. Quantitative.

Section Instructor Day/Time Location
D100 Cedric Chauve
Mo, We, Fr 9:30 AM – 10:20 AM
REMOTE LEARNING, Burnaby
D101 Tu 4:30 PM – 5:20 PM
REMOTE LEARNING, Burnaby
D102 Th 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby
MATH 345 - Introduction to Graph Theory (3)

Fundamental concepts, trees and distances, matchings and factors, connectivity and paths, network flows, integral flows. Prerequisite: MACM 201 (with a grade of at least B-). Quantitative.

Section Instructor Day/Time Location
D100 Matthew DeVos
Mo, We, Fr 3:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
D101 Th 2:30 PM – 3:20 PM
REMOTE LEARNING, Burnaby
D102 Th 1:30 PM – 2:20 PM
REMOTE LEARNING, Burnaby

and at least 6 additional units from the following list

ECON 435 - Econometric Methods (5)

The application of econometric techniques to the empirical investigation of economic issues. Prerequisite: ECON 201 or 301 and ECON (or BUEC) 333. Entry into this course requires a minimum CGPA of 3.0 or permission of the department. Quantitative.

Section Instructor Day/Time Location
D100 Jane Friesen
Tu 10:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby

Any upper division STAT course except for STAT 302, STAT 305, STAT 310, STAT 311, STAT 320, and STAT 403.

NOTE: SFU students enrolled in the Accelerated Master's degree program within the Department of Mathematics may apply a maximum of 10 graduate course units, taken while completing the bachelor's degree, towards the upper division undergraduate electives of the bachelor's program and the requirements of the master's degree. For more information go to: http://www.sfu.ca/dean-gradstudies/future/academicprograms/AcceleratedMasters.html.

Interdisciplinary Requirement

With advisor approval, students also complete at least 15 units from application areas. Application courses are chosen from ACMA, BUEC, BUS, ECON, MACM, MATH, REM and STAT courses. Courses used to fulfil upper division requirements cannot be used to fulfil this requirement. If the operations research major is completed as part of a second bachelor's degree, then the interdisciplinary requirement may be waived if the previous degree contains an approved major. Approvals are given individually. Those majors that are approved will not be limited to the disciplines listed above.

University Degree Requirements

Students must also satisfy University degree requirements for degree completion.

Writing, Quantitative, and Breadth Requirements

Students admitted to Simon Fraser University beginning in the fall 2006 term must meet writing, quantitative and breadth requirements as part of any degree program they may undertake. See Writing, Quantitative, and Breadth Requirements for university-wide information.

WQB Graduation Requirements

A grade of C- or better is required to earn W, Q or B credit

Requirement

Units

Notes
W - Writing

6

Must include at least one upper division course, taken at Simon Fraser University within the student’s major subject
Q - Quantitative

6

Q courses may be lower or upper division
B - Breadth

18

Designated Breadth Must be outside the student’s major subject, and may be lower or upper division
6 units Social Sciences: B-Soc
6 units Humanities: B-Hum
6 units Sciences: B-Sci

6

Additional Breadth 6 units outside the student’s major subject (may or may not be B-designated courses, and will likely help fulfil individual degree program requirements)

Students choosing to complete a joint major, joint honours, double major, two extended minors, an extended minor and a minor, or two minors may satisfy the breadth requirements (designated or not designated) with courses completed in either one or both program areas.

 

Residency Requirements and Transfer Credit

  • At least half of the program's total units must be earned through Simon Fraser University study.
  • At least two thirds of the program's total upper division units must be earned through Simon Fraser University study.

Elective Courses

In addition to the courses listed above, students should consult an academic advisor to plan the remaining required elective courses.