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Operations Research Major
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
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 highlevel 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 problemsolving 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/BreadthScience.
Section  Instructor  Day/Time  Location 

D100 
Angelica Lim 
Mo, Fr 9:30 AM – 10:20 AM We 9:30 AM – 10:20 AM 
AQ 3181, Burnaby AQ 3182, Burnaby 
D101 
Angelica Lim 
Th 9:30 AM – 10:20 AM 
ASB 9838, Burnaby 
D102 
Angelica Lim 
Th 10:30 AM – 11:20 AM 
ASB 9838, Burnaby 
D103 
Angelica Lim 
Th 11:30 AM – 12:20 PM 
ASB 9838, Burnaby 
D104 
Angelica Lim 
Th 12:30 PM – 1:20 PM 
ASB 9838, Burnaby 
D105 
Angelica Lim 
Th 1:30 PM – 2:20 PM 
ASB 9838, Burnaby 
D106 
Angelica Lim 
Th 2:30 PM – 3:20 PM 
ASB 9838, Burnaby 
D107 
Angelica Lim 
Th 3:30 PM – 4:20 PM 
ASB 9838, Burnaby 
D108 
Angelica Lim 
Th 3:30 PM – 4:20 PM 
ASB 9838, Burnaby 
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 objectoriented 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.
Section  Instructor  Day/Time  Location 

D100 
Brad Bart 
Mo, We 1:30 PM – 2:20 PM Fr 1:30 PM – 2:20 PM 
WMC 3260, Burnaby WMC 3210, Burnaby 
D101 
Brad Bart 
Th 12:30 PM – 1:20 PM 
ASB 9838, Burnaby 
D102 
Brad Bart 
Th 1:30 PM – 2:20 PM 
ASB 9838, Burnaby 
D103 
Brad Bart 
Th 2:30 PM – 3:20 PM 
ASB 9838, Burnaby 
D104 
Brad Bart 
Th 3:30 PM – 4:20 PM 
ASB 9838, Burnaby 
(or equivalent: CMPT 125 (3) or CMPT 126 (3) or CMPT 128 (3))
or both of
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/BreadthScience.
A second course in systemsoriented programming and computing science that builds upon the foundation set in CMPT 130 using a systemsoriented language such as C or C++. Topics: a review of the basic elements of programming; introduction to objectoriented 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.
Section  Instructor  Day/Time  Location 

D100 
John Edgar 
We 1:30 PM – 2:20 PM Fr 12:30 PM – 2:20 PM 
SUR 3310, Surrey SUR 3310, Surrey 
D101 
John Edgar 
We 2:30 PM – 3:20 PM 
SUR 4080, Surrey 
D102 
John Edgar 
We 3:30 PM – 4:20 PM 
SUR 4080, Surrey 
D103 
John Edgar 
We 4:30 PM – 5:20 PM 
SUR 4080, Surrey 
D104 
John Edgar 
We 12:30 PM – 1:20 PM 
SUR 4080, Surrey 
and all of
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; objectoriented 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 1:30 PM – 2:20 PM We 1:30 PM – 2:20 PM Fr 1:30 PM – 2:20 PM 
DFA 300, Burnaby SSCB 9201, Burnaby SSCB 9201, Burnaby 
D101 
David Mitchell 
Mo 10:30 AM – 11:20 AM 
ASB 9838, Burnaby 
D102 
David Mitchell 
Mo 10:30 AM – 11:20 AM 
ASB 9838, Burnaby 
D103 
David Mitchell 
Mo 11:30 AM – 12:20 PM 
ASB 9838, Burnaby 
D104 
David Mitchell 
Mo 11:30 AM – 12:20 PM 
ASB 9838, Burnaby 
D105 
David Mitchell 
Fr 2:30 PM – 3:20 PM 
ASB 9838, Burnaby 
D106 
David Mitchell 
Fr 2:30 PM – 3:20 PM 
ASB 9838, Burnaby 
D107 
David Mitchell 
Fr 3:30 PM – 4:20 PM 
ASB 9838, Burnaby 
D108 
David Mitchell 
Fr 3:30 PM – 4:20 PM 
ASB 9838, Burnaby 
E100 
Leonid Chindelevitch 
Tu 5:30 PM – 8:20 PM 
HCC 1900, Vancouver 
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/BreadthScience.
Section  Instructor  Day/Time  Location 

D100 
Binay Bhattacharya 
Mo, Fr 10:30 AM – 11:20 AM We 10:30 AM – 11:20 AM 
SWH 10081, Burnaby SSCB 9201, Burnaby 
D101 
Binay Bhattacharya 
Tu 9:30 AM – 10:20 AM 
AQ 5008, Burnaby 
D102 
Binay Bhattacharya 
Tu 9:30 AM – 10:20 AM 
RCB 5125, Burnaby 
D103 
Binay Bhattacharya 
Tu 2:30 PM – 3:20 PM 
AQ 5035, Burnaby 
D104 
Binay Bhattacharya 
Tu 2:30 PM – 3:20 PM 
AQ 5047, Burnaby 
D105 
Binay Bhattacharya 
Tu 3:30 PM – 4:20 PM 
AQ 5014, Burnaby 
D106 
Binay Bhattacharya 
Tu 3:30 PM – 4:20 PM 
AQ 5035, Burnaby 
D107 
Binay Bhattacharya 
Tu 4:30 PM – 5:20 PM 
AQ 5020, Burnaby 
D108 
Binay Bhattacharya 
Tu 4:30 PM – 5:20 PM 
AQ 5039, Burnaby 
D200 
Steve Pearce 
Tu 1:30 PM – 2:20 PM Th 12:30 PM – 2:20 PM 
SWH 10081, Burnaby SSCB 9201, Burnaby 
D201 
Steve Pearce 
We 9:30 AM – 10:20 AM 
AQ 2104, Burnaby 
D202 
Steve Pearce 
We 9:30 AM – 10:20 AM 
BLU 11901, Burnaby 
D203 
Steve Pearce 
We 2:30 PM – 3:20 PM 
BLU 11911, Burnaby 
D204 
Steve Pearce 
We 2:30 PM – 3:20 PM 
WMC 2260, Burnaby 
D205 
Steve Pearce 
We 3:30 PM – 4:20 PM 
WMC 2268, Burnaby 
D206 
Steve Pearce 
We 3:30 PM – 4:20 PM 
BLU 11911, Burnaby 
D207 
Steve Pearce 
We 4:30 PM – 5:20 PM 
BLU 11911, Burnaby 
D208 
Steve Pearce 
We 4:30 PM – 5:20 PM 
WMC 2268, Burnaby 
D300 
Toby Donaldson 
Mo, We, Fr 11:30 AM – 12:20 PM 
SUR 5140, Surrey 
D301 
Toby Donaldson 
Mo 12:30 PM – 1:20 PM 
SUR 3120, Surrey 
D302 
Toby Donaldson 
Mo 1:30 PM – 2:20 PM 
SUR 3120, Surrey 
D303 
Toby Donaldson 
Mo 2:30 PM – 3:20 PM 
SUR 3120, Surrey 
D304 
Toby Donaldson 
Mo 3:30 PM – 4:20 PM 
SUR 3120, Surrey 
A continuation of MACM 101. Topics covered include graph theory, trees, inclusionexclusion, 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 
Bojan Mohar 
Mo 12:30 PM – 1:20 PM We, Fr 12:30 PM – 1:20 PM 
DFA 300, Burnaby DFA 300, Burnaby 
D200 
Mahsa Faizrahnemoon 
Mo, We, Fr 8:30 AM – 9:20 AM 
SUR 5280, Surrey 
OPO1 

TBD  
OP02 

TBD 
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.
Section  Instructor  Day/Time  Location 

D100 
Tamon Stephen 
Mo 2:30 PM – 4:20 PM We 2:30 PM – 3:20 PM 
SUR 2710, Surrey SUR 2710, Surrey 
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 

E100 
Steven Ruuth 
Mo, We 4:30 PM – 5:50 PM 
WMC 3520, Burnaby 
OP01 

TBD 
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 

C100  Distance Education  
D100 
Boxin Tang 
Mo 9:30 AM – 10:20 AM We, Fr 9:30 AM – 10:20 AM 
SSCB 9201, Burnaby SWH 10081, Burnaby 
D900 
Maryam DehghaniEstarki 
Tu 8:30 AM – 10:20 AM Th 8:30 AM – 9:20 AM 
SUR 3170, Surrey SUR 3170, Surrey 
OP01 

TBD  
OP09 

TBD 
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. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Liangliang Wang 
Mo 2:30 PM – 4:20 PM We 2:30 PM – 3:20 PM 
BLU 10021, Burnaby BLU 10011, Burnaby 
D101 
Liangliang Wang 
Mo 8:30 AM – 9:20 AM 
AQ 5008, Burnaby 
D102 
Liangliang Wang 
Mo 9:30 AM – 10:20 AM 
AQ 5008, Burnaby 
D104 
Liangliang Wang 
We 12:30 PM – 1:20 PM 
AQ 5007, Burnaby 
and one of
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: PreCalculus 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 

C100  Distance Education  
D100 
Yusuf Tuncer 
Mo, Tu, We, Fr 8:30 AM – 9:20 AM 
WMC 3520, Burnaby 
D200 
Justine Gauthier 
Mo, We, Fr 11:30 AM – 12:20 PM We 1:30 PM – 2:20 PM 
SUR 2750, Surrey SUR 2750, Surrey 
OP01 

TBD  
OP02 

TBD 
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: PreCalculus 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.
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: PreCalculus 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 
Ladislav Stacho 
Mo 8:30 AM – 9:20 AM We, Fr 8:30 AM – 9:20 AM 
SSCB 9200, Burnaby SSCB 9200, Burnaby 
OP01 

TBD 
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; functions of several variables. Prerequisite: PreCalculus 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 
Luis Goddyn 
Mo, Fr 11:30 AM – 12:20 PM We 11:30 AM – 12:20 PM 
SWH 10081, Burnaby DFA 300, Burnaby 
D200 
Natalia Kouzniak 
Mo, We, Fr 12:30 PM – 1:20 PM 
SUR 3090, Surrey 
OP01 

TBD  
OP02 

TBD 
and one of
Riemann sum, Fundamental Theorem of Calculus, definite, indefinite and improper integrals, approximate integration, integration techniques, applications of integration. Firstorder 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 
SSCC 9001, Burnaby 
D200 
Sepehr Foroushani 
Mo, We, Fr 11:30 AM – 12:20 PM 
SUR 5280, Surrey 
D300 
Jamie Mulholland 
Mo, We, Fr 8:30 AM – 9:20 AM 
WMC 2810, Burnaby 
OP01 

TBD  
OP02 

TBD 
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.
Section  Instructor  Day/Time  Location 

D100 
Petr Lisonek 
Mo, We, Fr 8:30 AM – 9:20 AM 
RCB IMAGTH, Burnaby 
D200 
Natalia Kouzniak 
Mo, We, Fr 9:30 AM – 10:20 AM 
SUR 5280, Surrey 
OP01 

TBD  
OP02 

TBD 
Theory of integration and its applications; introduction to multivariable calculus with emphasis on partial derivatives and their applications; introduction to differential equations with emphasis on some special firstorder equations and their applications to economics and social sciences; continuous probability models; 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.
Section  Instructor  Day/Time  Location 

E100 
Michael Monagan 
Mo 4:30 PM – 5:20 PM We 4:30 PM – 6:20 PM 
SSCC 9001, Burnaby SSCC 9001, Burnaby 
OP01 

TBD 
and one of
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 
Cedric Chauve 
Mo, We, Fr 11:30 AM – 12:20 PM 
SSCC 9001, Burnaby 
D200 
Randall Pyke 
Mo, We, Fr 2:30 PM – 3:20 PM 
SUR 3090, Surrey 
OP01 

TBD  
OP02 

TBD 
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 
Simone Brugiapaglia 
Mo, We, Fr 11:30 AM – 12:20 PM 
BLU 10921, Burnaby 
OP01 

TBD 
* with a B grade or better
Upper Division Requirements
Students complete all of
Linear programming modelling. The simplex method and its variants. Duality theory. Postoptimality 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 
Luis Goddyn 
Mo 2:30 PM – 3:20 PM We 2:30 PM – 3:20 PM Fr 2:30 PM – 3:20 PM 
AQ 3005, Burnaby WMC 3260, Burnaby SWH 10041, Burnaby 
D101 

Tu 2:30 PM – 3:20 PM 
AQ 4120, Burnaby 
D102 

Tu 3:30 PM – 4:20 PM 
AQ 4120, Burnaby 
D103 

Tu 4:30 PM – 5:20 PM 
AQ 5037, Burnaby 
Inventory theory, Markov decision process and applications, queuing theory, forecasting models, decision Analysis and games, probabilistic dynamic programming, simulation modeling, project planning using PERT/CPM, sequencing and scheduling. Prerequisite: STAT 270. Pre/Corequisite: MATH 308. Quantitative.
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.
Section  Instructor  Day/Time  Location 

D100 
Tamon Stephen 
Tu, Th 10:30 AM – 12:20 PM 
SUR 2980, Surrey 
and four of
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.
Applications of network flow models; flow decomposition; polynomial algorithms for shortest paths, maximum flows and minimum costs flows; convex cost flows; generalized flows, multicommodity flows. Prerequisite: MATH 308. Recommended: MATH 345. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Abraham Punnen 
Mo 2:30 PM – 4:20 PM We 2:30 PM – 3:20 PM 
SUR 3240, Surrey SUR 3240, Surrey 
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 

E200 
Gamage Perera 
Mo 6:00 PM – 7:50 PM We 5:30 PM – 6:20 PM 
SUR 5140, Surrey SUR 5140, Surrey 
E201 
Gamage Perera 
We 8:30 AM – 9:20 AM 
SUR 2710, Surrey 
E202 
Gamage Perera 
We 9:30 AM – 10:20 AM 
SUR 2710, Surrey 
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 208, and MATH 251. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Richard Lockhart 
Mo, We, Fr 9:30 AM – 10:20 AM 
AQ 5016, Burnaby 
D101 
Richard Lockhart 
Fr 10:30 AM – 11:20 AM 
AQ 5009, Burnaby 
D102 
Richard Lockhart 
Fr 11:30 AM – 12:20 PM 
AQ 5009, Burnaby 
and at least one of
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.
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 
Valentine Kabanets 
Mo 10:30 AM – 11:20 AM We, Fr 10:30 AM – 11:20 AM 
WMC 3260, Burnaby AQ 3005, Burnaby 
D300 
Valentine Kabanets 
Mo 2:30 PM – 3:20 PM We 2:30 PM – 3:20 PM Fr 2:30 PM – 3:20 PM 
AQ 3159, Burnaby SSCC 9002, Burnaby SSCK 9500, Burnaby 
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 
Brenda Davison 
Mo, We, Fr 12:30 PM – 1:20 PM 
AQ 3182, Burnaby 
D101 

We 2:30 PM – 3:20 PM 
AQ 5016, Burnaby 
D102 

We 3:30 PM – 4:20 PM 
AQ 5016, Burnaby 
D103 

We 4:30 PM – 5:20 PM 
AQ 5016, Burnaby 
D104 

Th 9:30 AM – 10:20 AM 
AQ 5018, Burnaby 
D105 

Th 10:30 AM – 11:20 AM 
AQ 5030, Burnaby 
D106 

Th 11:30 AM – 12:20 PM 
RCB 6125, Burnaby 
D107 

We 5:30 PM – 6:20 PM 
AQ 5016, Burnaby 
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.
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.
and at least 6 additional units from the following list
Introduces the R statistical package. Data management; reading, editing and storing statistical data; data exploration and representation; summarizing data with tables, graphs and other statistical tools; and data simulation. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333 or equivalent. Students with credit for STAT 340 may not take STAT 341 for further credit.
Section  Instructor  Day/Time  Location 

D100 
Brad McNeney 
Th 12:30 PM – 2:20 PM 
EDB 7618, Burnaby 
D101 
Brad McNeney 
Fr 12:30 PM – 1:20 PM 
SECB 1014, Burnaby 
D102 
Brad McNeney 
Fr 1:30 PM – 2:20 PM 
SECB 1014, Burnaby 
D103 
Brad McNeney 
We 12:30 PM – 1:20 PM 
SECB 1014, Burnaby 
D104 
Brad McNeney 
We 1:30 PM – 2:20 PM 
SECB 1014, Burnaby 
Introduces the SAS statistical package. Data management; reading, editing and storing statistical data; data exploration and representation; summarizing data with tables, graphs and other statistical tools; and data simulation. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333. Students with credit for STAT 340 may not take STAT 342 for further credit.
An introduction to the major sample survey designs and their mathematical justification. Associated statistical analyses. Prerequisite: STAT 350. Quantitative.
Section  Instructor  Day/Time  Location 

E100 
Jack Davis 
Mo 4:30 PM – 6:20 PM We 4:30 PM – 5:20 PM 
RCB 8100, Burnaby AQ 4150, Burnaby 
E101 
Michael Davis 
We 3:30 PM – 4:20 PM 
AQ 5036, Burnaby 
E102 
Michael Davis 
We 5:30 PM – 6:20 PM 
AQ 5027, Burnaby 
Introduction to standard methodology for analyzing categorical data including chisquared tests for two and multiway contingency tables, logistic regression, and loglinear (Poisson) regression. Prerequisite: STAT 302 or STAT 305 or STAT 350 or BUEC 333 or equivalent. Students with credit for the former STAT 402 or 602 may not take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Joan Hu 
Tu 10:30 AM – 11:20 AM Th 9:30 AM – 11:20 AM 
AQ 3005, Burnaby AQ 3005, Burnaby 
D101 
Joan Hu 
We 9:30 AM – 10:20 AM 
AQ 4125, Burnaby 
D102 
Joan Hu 
We 3:30 PM – 4:20 PM 
AQ 5028, Burnaby 
D103 
Joan Hu 
We 4:30 PM – 5:20 PM 
AQ 5038, Burnaby 
D104 
Joan Hu 
We 5:30 PM – 6:20 PM 
AQ 5015, Burnaby 
Introduction to linear time series analysis including moving average, autoregressive and ARIMA models, estimation, data analysis, forecasting errors and confidence intervals, conditional and unconditional models, and seasonal models. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333 or equivalent. This course may not be taken for further credit by students who have credit for ECON 484. Quantitative.
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 universitywide 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: BSoc 6 units Humanities: BHum 6 units Sciences: BSci 
6 
Additional Breadth  6 units outside the student’s major subject (may or may not be Bdesignated 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.