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Operations Research Honours
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. The Faculty of Science stipulates that a minimum of 48 units must be in upper division, and that additional upper division units will be required to total a minimum of 60.
The specific requirements for this particular program 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 regulations must be met.
A minimum program 3.00 cumulative grade point average (CGPA) must be obtained on the overall major program requirements, as well as a minimum program 3.00 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, e.g. Python. The students will be exposed to diverse fields within, and applications of computing science. Topics will include: pseudocode; data types and control structures; fundamental algorithms; recursion; reading and writing files; measuring performance of algorithms; debugging tools; basic terminal navigation using shell commands. 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 
Hazra Imran 
Mo
8:30 AM – 10:20 AM
We 8:30 AM – 9:20 AM 
SSCB 9201, Burnaby AQ 3181, 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 computability and specification and program correctness. Prerequisite: CMPT 102 or CMPT 120, with a minimum grade of C. 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
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, with a minimum grade of C). 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 with a minimum grade of C. Students with credit for CMPT 125, 126, or 129 may not take this course for further credit. Quantitative.
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, CMPT 129 or CMPT 135)) or (ENSC 251 and ENSC 252), all with a minimum grade of C. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Toby Donaldson 
Tu
12:30 PM – 2:20 PM
Fr 12:30 PM – 1:20 PM 
SSCB 9201, Burnaby WMC 3520, Burnaby 
D101 
We
11:30 AM – 12:20 PM

ASB 9838, Burnaby 

D102 
We
11:30 AM – 12:20 PM

ASB 9838, Burnaby 

D103 
Th
9:30 AM – 10:20 AM

ASB 9838, Burnaby 

D104 
Th
9:30 AM – 10:20 AM

ASB 9838, Burnaby 

D105 
Th
10:30 AM – 11:20 AM

ASB 9838, Burnaby 

D106 
Th
10:30 AM – 11:20 AM

ASB 9838, Burnaby 

D107 
We
12:30 PM – 1:20 PM

ASB 9838, Burnaby 

D108 
We
12:30 PM – 1:20 PM

ASB 9838, Burnaby 

D200 
John Edgar 
Mo, We, Fr
8:30 AM – 9:20 AM

SRYE 1002, Surrey 
D201 
Mo
10:30 AM – 11:20 AM

SRYE 4013, Surrey 

D202 
Mo
10:30 AM – 11:20 AM

SRYE 4013, Surrey 

D203 
Mo
11:30 AM – 12:20 PM

SRYE 4013, Surrey 

D204 
Mo
11:30 AM – 12:20 PM

SRYE 4013, Surrey 

D205 
Mo
12:30 PM – 1:20 PM

SRYE 4013, Surrey 

D206 
Mo
12:30 PM – 1:20 PM

SRYE 4013, Surrey 

D207 
Mo
1:30 PM – 2:20 PM

SRYE 4013, Surrey 

D208 
Mo
1:30 PM – 2:20 PM

SRYE 4013, Surrey 
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 
Brad Bart 
Mo, We, Fr
11:30 AM – 12:20 PM

SSCB 9200, Burnaby 
D101 
Tu
2:30 PM – 3:20 PM

AQ 5005, Burnaby 

D102 
Tu
2:30 PM – 3:20 PM

AQ 5006, Burnaby 

D103 
Tu
3:30 PM – 4:20 PM

AQ 5005, Burnaby 

D104 
Tu
3:30 PM – 4:20 PM

AQ 5006, Burnaby 

D105 
Tu
4:30 PM – 5:20 PM

AQ 5006, Burnaby 

D106 
Tu
4:30 PM – 5:20 PM

AQ 5005, Burnaby 

D107 
Tu
5:30 PM – 6:20 PM

AQ 5005, Burnaby 

D108 
Tu
5:30 PM – 6:20 PM

AQ 5006, Burnaby 
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, with a minimum grade of C. Students with credit for MATH 208 may not take this course for further credit. Writing/Quantitative.
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 with a minimum grade of C; 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 
Hansol Park 
Mo, We, Fr
1:30 PM – 2:20 PM

SSCB 9201, Burnaby 
D400 
Justin Chan 
Mo, We, Fr
9:30 AM – 10:20 AM

SRYC 5280, Surrey 
OP01  TBD  
OP02  TBD 
Basic laws of probability, sample distributions. Introduction to statistical inference and applications. Prerequisite: or Corequisite: MATH 152 or 155 or 158, with a minimum grade of C. 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 
Wei Lin 
We
11:30 AM – 12:20 PM
Fr 10:30 AM – 12:20 PM 
SSCB 9201, Burnaby AQ 3182, Burnaby 
OL01 
Gamage Perera 
TBD  
OP01  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 and one of MATH 152, MATH 155, or MATH 158, all with a minimum grade of C. Quantitative.
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 

D100 
MacKenzie Carr 
Mo, We, Fr
1:30 PM – 2:20 PM

BLU 9660, Burnaby 
D101 
Tu
8:30 AM – 9:20 AM

SWH 10061, Burnaby 

D102 
Tu
9:30 AM – 10:20 AM

SWH 10061, Burnaby 

D103 
Tu
10:30 AM – 11:20 AM

SWH 10061, Burnaby 

OP01  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 life sciences. Topics include: limits, growth rate and the derivative; elementary functions, optimization and approximation methods, and their applications, integration, and differential equations; mathematical models of biological processes and their implementation and analysis using software. 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.
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: 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 
Mahsa Faizrahnemoon 
Mo, We, Fr
11:30 AM – 12:20 PM

AQ 3154, Burnaby 
OP01  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, with a minimum grade of C; 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 
Alexander Rutherford 
Mo, We, Fr
8:30 AM – 9:20 AM

SSCB 9200, Burnaby 
OP01  TBD 
Designed for students specializing in the life sciences. Topics include: vectors and matrices, partial derivatives, multidimensional integrals, systems of differential equations, compartment models, graphs and networks, and their applications to the life sciences; mathematical models of multicomponent biological processes and their implementation and analysis using software. Prerequisite: MATH 150, 151 or 154, with a minimum grade of C; 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 
Vijaykumar Singh 
Mo, We, Fr
8:30 AM – 9:20 AM

AQ 3182, Burnaby 
OPO1  TBD 
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 firstorder equations and their applications; sequences and series. Prerequisite: MATH 150 or 151 or 154 or 157, with a minimum grade of C. Students with credit for MATH 152 or 155 may not take MATH 158 for further credit. Quantitative.
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, with a minimum grade of C; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 240 may not take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D400 
Navpreet Kaur 
Mo, We, Fr
1:30 PM – 2:20 PM

SRYE 1002, Surrey 
OP01  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, with a minimum grade of C; 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 
Jonathan Jedwab 
Mo, We, Fr
11:30 AM – 12:20 PM

AQ 3149, Burnaby 
D101 
Th
9:30 AM – 10:20 AM

AQ 5005, Burnaby 

D102 
Th
2:30 PM – 3:20 PM

AQ 5005, Burnaby 

D103 
Th
3:30 PM – 4:20 PM

AQ 5005, Burnaby 
* with a B grade or better
Upper Division Requirements
Students complete a total of 48 units, including 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, all with a minimum grade of C. Quantitative.
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), all with a minimum grade of C. 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 with a minimum grade of C. Writing/Quantitative.
and five of
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, all with a minimum grade of C. Quantitative.
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 with a minimum grade of C. Quantitative.
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, all with a minimum grade of C. Quantitative.
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, all with a minimum grade of C. Quantitative.
and at least one of
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 or STAT 271), all with a minimum grade of C.
Design and analysis of efficient data structures and algorithms. General techniques for building and analyzing algorithms (greedy, divide & conquer, dynamic programming, network flows). Introduction to NPcompleteness. Prerequisite: CMPT 225, (MACM 201 or CMPT 210), (MATH 150 or MATH 151), and (MATH 232 or MATH 240), all with a minimum grade of C. MATH 154 or MATH 157 with a grade of at least B+ may be substituted for MATH 150 or MATH 151.
Section  Instructor  Day/Time  Location 

D100 
Valentine Kabanets 
We
3:30 PM – 4:20 PM
Fr 2:30 PM – 4:20 PM 
SSCK 9500, 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 
Jane MacDonald 
Mo, We, Fr
10:30 AM – 11:20 AM

SSCB 9200, Burnaby 
D101 
We
2:30 PM – 3:20 PM

WMC 2830, Burnaby 

D102 
We
3:30 PM – 4:20 PM

WMC 2830, Burnaby 

D103 
We
4:30 PM – 5:20 PM

WMC 2830, Burnaby 

D104 
Th
9:30 AM – 10:20 AM

WMC 2830, Burnaby 

D105 
Th
10:30 AM – 11:20 AM

WMC 2830, Burnaby 

D106 
Th
11:30 AM – 12:20 PM

WMC 2830, Burnaby 

D107 
We
4:30 PM – 5:20 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
The application of econometric techniques to the empirical investigation of economic issues. Prerequisite: ECON 201 and ECON (or BUEC) 333, all with a minimum grade of C. Entry into this course requires a minimum CGPA of 3.0 or permission of the department. Quantitative.
Any upper division STAT course except for STAT 302, STAT 305, STAT 310, STAT 311, STAT 320, and STAT 403.
To complete the required 48 upper division units, students complete additional coursework, of which at least two courses must be 400level MATH or MACM courses with the possibility of substituting a 400level course from another department subject to advisor approval. Courses used to fulfil this upper division requirement cannot be used to satisfy the interdisciplinary requirement. All courses pertaining to the required 48 upper division units must be approved by the program advisor in the Department of Mathematics.
NOTE: SFU students accepted in the accelerated master’s 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 electives of the bachelor's program and the requirements of the master's degree. For more information go to: https://www.sfu.ca/gradstudies/apply/programs/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, CMPT, 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 honours 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 Honours 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.