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Operations Management
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Introduction
Strengths of the Program
Admission to the Program
PhD Courses
Program Structure and Requirements
Current Students
Faculty and Research Interests
Graduates
Introduction
Operations Management (OM) involves the study of management concerns related to the design, decision-making, and implementation of operating systems. Operations Management is a major strength of the Rotman School, whose doctoral programs were ranked 19th in the 2009 Financial Times listings, ahead of such top-tier schools as Yale, Oxford and INSEAD.
The Rotman PhD Program in Operations Management is designed to prepare students for academic and research careers in universities and industry. Our faculty includes PhDs from Columbia, Indiana, John Hopkins, MIT, and Stanford, and their interests include Supply Chain Management and Logistics, OM in Services, Inventory Management, Call Centre Management, OM/Marketing Interface, and other areas.
A unique feature of the Rotman Operations Management Program is the flexibility it provides students in developing a course of study to meet their goals. The area supplements the School's resources in management education by drawing on the resources of several other departments within the University of Toronto (such as Computer Science, Economics, Electrical Engineering, Industrial Engineering, Mathematics, Mechanical Engineering and Statistics). Students can take courses in these departments by selecting the appropriate areas as minor fields or by taking additional course work to meet their specific needs.
Admitted students will typically have a MS-level degree in engineering, mathematics, computer science, natural sciences or business (however, exceptional students with only undergraduate-level education will also be admitted). The admissions are highly competitive and are based on the following key components: transcripts, letters of reference (at least three are required), standardized test scores (students must take either the GRE, which is preferred, or the GMAT; foreign students must also take the TOEFL/TWE). Please refer to www.rotman.utoronto.ca/phd/ for further information on program admission requirements and procedures.
• Full funding for all PhD students through a financial aid package that fully covers tuition and provides an attractive stipend that can continue for up to five years in the program.
• Location: the Rotman School is in the heart of North America’s third-largest financial centre, just blocks from the heart of Canada’s business community.
• Strong ties and frequent collaboration with distinguished faculty members in related programs.
• Opportunities and funding to support student presentations at national academic conferences.
PhD Courses
RSM 3041 Seminar in Operations Management
This course consists of presentations by invited speakers on current issues in Operations Management, as well as student presentations on the research projects they are involved in. A variety of applied and theoretical topics are covered. Normally students attend this course throughout their tenure in the program, however it is only taken for credit once, usually in the second year of studies. In the term when the course is taken for credit the student is required to turn in a substantial research paper and to present the results in class.
RSM 3045 Advanced Topics in Operations Management - I
RSM 3046 Advanced Topics in Operations Management – II
These courses provides students with in-depth analysis of some of the theory and methods of Operations Management and form the primary “foundation” courses for the PhD studies. The topics covered vary from year to year. They are typically drawn from the following list:
• Theory of Production Planning and Control • Inventory Theory • Logistics • Modelling Service Operations • Facility Location
Students who have already taken RMS3045 for credit, but wish to study the special topic offered in a particular year are encouraged to take the course again (using the RMS3090 course number for the second registration).
Program Structure and Requirements
Program Structure
The main components for the successful completion of the program are:
· Required Courses
· Research Project
· Comprehensive Examination
· Dissertation
Each of these components, as well as the annual performance review procedure, is described in more detail below. A typical program of studies takes four to five years. The bulk of the course requirements, as well as the research project are completed during the first two years. The comprehensive examination is taken in the summer of the second year. The last two to three years of the program are focused on the thesis research.
Required Courses
Program course requirements are subdivided into several categories described below. The following list of courses is not exhaustive:- substitutions with other similar courses within each category may be arranged. Certain requirements may be waived based on the courses taken at other institutions.
At the beginning of each academic year, the students should schedule a meeting with the Program Coordinator to work out a detailed program of courses for the coming year specialized to their needs and interests. The program course requirements are summarized in the OM Program of Studies Form, which is updated annually by the student and the Program Coordinator.
Major Field (Core): Four PhD level courses in OM
Each year the Area offers two PhD level courses (numbered RMS3045 and RMS3046). The course topics are rotated so that different topics are offered every other year; they depend on the current research initiatives of faculty and students. Students should take both courses in each of their first two years of study. (NOTE: in the second year students should register for RMS3090, Research in OM, since, with the exception of this course number, only one course with a specific course number can appear on the transcript.) In recent years, the following topics were offered under this category:
· OM in Services
· Logistics
· Queuing Theory
· Inventory Theory
· Combinatorial Techniques with Applications to OM
· Auction Theory
Quantitative Methods I (Stochastic Models): Minimum of Two Courses
Courses in this category are intended to give students an in-depth introduction to the areas of probability theory, stochastic processes, and stochastic optimization techniques. These courses are typically offered in the departments of Statistics (STA) and Mechanical and Industrial Engineering (MIE). Students take STA2111H and select at least 1 additional course from the following list:
· STA2111H - Graduate Probability I (*required)
· STA2006H - Applied Stochastic Processes
· STA2101H - Methods of Applied Statistics I
· STA2201H - Methods of Applied Statistics II
· STA2104H - Statistical Methods for Machine Learning and Data Mining
· MIE1605 - Stochastic Processes
· MIE1606 - Queuing Theory
· MIE1607 - Stochastic Modeling and Optimization
· MIE1615 - Stochastic Dynamic Programming
Quantitative Methods II (Mathematical Methods and Optimization Models): Minimum of Three Courses
Courses in this category are designed to provide students with the knowledge of key Operations Research methods and related mathematical techniques. These courses are typically offered in the departments of Mechanical and Industrial Engineering (MIE), Computer Science (CSC), and Economics (ECO), but can be found in other departments as well.
· MIE1620 – Mathematical Programming I
· MIE1621 - Mathematical Programming II
· MIE1606 - Integer Programming
· MIE1722 - Supply Chain Management and Logistics
· ECO1011 – Math/Stat Review (PhD), August 21-Sept 1 (*strongly recommended)
· CSC2305 - Numerical Methods for Optimization Problems
· CSC2406 - Algorithms in Graph Theory
· CIV1599 - Special Studies in Civil Engineering (Topic: Operations Research Methods for Logistical and Transportation Applications)
· Economics: 1 graduate course
Students should acquire knowledge of basic techniques of economics, including equilibrium analysis and game theory. Either ECO2020 or ECO2060 (depending on background) is recommended, but students with advanced knowledge of economics may consider other courses.
· ECO2020 – Micro Theory I (PhD)
· ECO2060 - Micro Theory I (M.A.)
· ECO2021 - Macro Theory I (PhD)
· ECO2061 - Econometrics (M.A.)
Professional Requirement: Minimum of Two Courses
These courses are designed to familiarize the students with the Operations Management function and important business applications of quantitative techniques in OM.
· RMS2405 - Supply Chain Management
· RMS2406 - OM Strategy
· RMS2415 - Service Operations
· RMS2800 – Management Science
Minor Field I: Minimum of Two Courses
A sequence of at least two advanced courses is required that are thematically linked and that are not offered by the OM Area. They can be taken either from other areas within the Rotman School or from other departments (note: courses taken within Rotman must be 2000 level or higher). Typical examples include: Finance (2 courses), Marketing (2 courses), Industrial Engineering (2 courses), Optimization Methods (2 advanced courses, not necessarily from the same department).
Minor Field II: Minimum of Two Courses
Structured similarly to Minor I. For students with M.S.-level degrees, the second minor can often be waived. For students taking two minors, one should be internal to the Rotman School and one external.
Teaching Proficiency
Students must demonstrate preparedness to serve as an instructor in business courses. This can be demonstrated through the successful completion of the course listed below, or successful hands-on teaching experience. For students with extensive prior teaching experience at the MBA level this requirement can be waived.
Teaching Business in Colleges and Universities – Training Future Academics, offered annually to PhD students in Rotman (limited enrolment)
Comprehensive Examinations
The Comprehensive Examination in Operations Management is normally taken after the completion of the first two years of PhD studies. It is assumed that by this time the student has completed all (or nearly all) of the course requirements and has participated in some research projects.
The main purpose of the examination is to assess whether the student has attained sufficient general knowledge of key topics and tools in the Operations Management / Operations Research Area and is ready to begin independent research work. The student is expected to exhibit an in-depth understanding and mastery of the major analytical tools necessary for successful research in Operations Management.
The questions for the examination are drawn from two major areas: Operations Research (linear, integer, non-linear, and dynamic programming; stochastic models, probability and statistics, etc.), and Operations Management (production scheduling, inventory analysis, facility location, logistics, etc.). The questions are based on some of the courses listed in the PhD calendar, particularly the four “core” PhD courses offered by the Area during the student’s first two years in the program. The questions may also be based on other general topics in the areas mentioned above and on textual references provided separately (please contact the Program Coordinator).
The format of the examination is: four-hour written, open-book exam. The students will be allowed to bring in up to five books of their choice and any personal notes. Copies of the exams from previous years may be obtained from the Program Coordinator.
The questions for the examination are contributed by the members of the examination committee, normally consisting of the PhD Coordinator for the Area, as well as several faculty members involved in the program. The same committee will evaluate each student's performance on the examination. The results of the examination will be reported back to the student within several weeks of the examination, along with the committee's general assessment of the student's progress in the program.
Successful passing of the Comprehensive Examination is a necessary requirement for the advancement to the thesis research portion of the program. The possible examination results are:
Unconditional Pass
Conditional Pass: The letter describing your results will specify the additional conditions you must fulfill (typically consisting of additional courses to be taken); the conditions must usually be fulfilled within one year.
Fail with Invitation to Retake: If your performance on the exam was below the passing threshold, but, in the opinion of the committee, your performance in other aspects of the program to date has been sufficiently strong, you may be invited to retake the examination. The examination can usually be retaken in the following summer (with next year's class). Please note that the examination can be taken a maximum of two times – the second failure automatically signals that the student must withdraw from the program. During the post-exam meeting, the committee will recommend the additional steps you should take to increase your chances of success on the second attempt.
Fail without Invitation to Retake: In the opinion of the committee, your performance on the exam and other aspects of the program to date indicate that the chances for the successful retake of the exam are minimal. Students receiving this mark are expected to withdraw from the program.
During the first two years of study, students must successfully complete a research project, possibly in collaboration with OM faculty, and present the results at the OM Seminar. In the second year of studies students are expected to register for RMS3041: OM Seminar and successfully complete the course requirements, as described below.
. RMS3041 – OM Seminar. Students taking this class for credit are expected to present a one-hour talk on the results of their research project and submit a paper describing these results. The grade is assigned based on the quality of the presentation, the research, and the submitted paper. For successful completion of the course, the research results must have clear potential to lead to a publication in a good-quality academic journal.
NOTE: All PhD students in OM are expected to attend OM Seminars during their tenure in the program, whether they are taking this course for credit or not.
Dissertation
Successful passing of the Comprehensive Exam signals that the students are ready to enter the thesis research portion of their studies. Students are expected to identify the research topic and the potential advisor during the first term of the academic year following the passing of the Comprehensive Exam, typically the third year of studies. Initial results should be obtained during the second term and the summer. Students are strongly encouraged to submit a paper for publication early in their fourth year since one or more publications in high-quality journals greatly improves the chances of success on the academic job market.
During the fourth year of studies, students are expected to prepare and present a dissertation proposal. This document typically takes the form of a ‘mini-thesis’ – containing all chapters you intend to have in the final thesis, the initial results in each chapter and a description of the additional results needed to complete the thesis. The supervisory committee (consisting of your academic advisor and at least two additional faculty members) will provide written feedback on your proposal, outlining the steps necessary to complete your thesis research. Thesis completion and defence are expected to take place in the fourth or fifth year of studies.
Additional information about the policies and guidelines related to thesis supervision, thesis preparation and thesis defence can be found on the website of the School of Graduate Studies at www.sgs.utoronto.ca.
Program Timeline
The typical stages of the program are as follows:
First Year
Students complete two PhD level courses in OM, as part of their Major Field requirement
Student complete the two required courses in Quantitative Methods I (stochastic models)
Students complete two of three required course in Quantitative Methods II (applied mathematics and optimization models)
Students complete one or more Professional Requirements courses
Students complete one or more courses from a Minor Field
Summer of the First Year
Research Project
First year evaluation of student progress (end of summer)
Second Year
Students complete two PhD level courses in OM (second part of Major Field requirement)
Students complete the remaining required courses in Quantitative Methods II (applied mathematics and optimization models)
Students complete the remaining required courses in the Professional Requirements area
Students complete the remaining required courses in Minor Fields
Students complete the required course in Economics
Students complete their research project and present the results in the OM Seminar
Summer of the Second Year
Students successfully complete the Comprehensive Examination
Second year evaluation of student progress (end of summer)
Third Year
Students identify the academic supervisor and thesis research topic
Students take the course to complete their Teaching Proficiency requirement
Students take additional specialized courses, as needed
Students begin their dissertation proposal
Summer of the Third Year
Students continue their thesis research
Third year evaluation of student progress (end of summer)
Fourth Year (including summer)
Students present their dissertation proposal
Students continue their research. Early results are submitted for publication.
Students participate in hands-on teaching activities (course instructor, tutorial leader)
Fourth year student evaluation (end of summer)
Fourth or Fifth Year (including summer)
Students complete their thesis research
Students prepare their job talks seminars and present them in OM Seminars (fall)
Students defend their dissertations
Student Performance Reviews
The performance review of all active doctoral students is conducted annually by the Rotman School. In order to remain eligible for funding, the student must maintain the ‘good academic standing’ classification. The key guidelines for the student evaluation in each year of study are listed below:
First Year Review: primarily based on performance in the required courses and the research project
• Students receiving a grade of B or below in either RMS3045 or RMS3046 will automatically be classified as ‘not in good standing’.
• Students who fail to show any evidence of progress in the research project will be classified as ‘not in good standing’.
Second Year Review: primarily based on the successful completion of the comprehensive examination, course requirements and the research project.
• Students receiving a mark of ‘Fail Without Invitation to Retake’ will automatically be classified as ‘not in good standing’.
Third Year Review: primarily based on the progress the student has made in identifying the thesis research topic and supervisor.
• Students who are retaking the comprehensive exam and fail to achieve ‘Unconditional Pass’ or ‘Conditional Pass’ will automatically be classified as ‘not in good standing’.
• Students showing no evidence of progress in their thesis research will be classified as ‘not in good standing’.
Fourth and Fifth Year Reviews: primarily based on the progress students are making towards completing their thesis.
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Current Students
Q&A with a Current Student
Iman Hajizadeh A fifth-year Operations Management PhD student specializing in supply chain management
Recent Publications involving Ph.D. Students
Berman, Oded and Huang, Rongbing (2004), “The minimum weighted covering location problem with distance constraints", Computers and Operations Research, to appear
Berman, Oded and Huang, Rongbing (2004), “The minimum collection depots location problem with multiple facilities on a network", Journal of the Operational Research Society, 55, 769-779.
A. Ovtchinnikov and D. Krass (2006), “University of Toronto's Rotman School of Management Uses Management Science to Create MBA Study Groups”, Interfaces, 36(2), pp.126-137.
R. Aboolian, O. Berman, and D. Krass (2007), “Competitive Facility Location Model with Concave Demand”, European Journal of Operations Research, 181, 598-619.
R. Aboolian, O. Berman, and D. Krass, “Efficient Solution Approaches for Discrete Multi-Facility Competitive Interaction Model”, Annals of Operations Research, to appear.
O. Berman, M. Menezes, and D. Krass “Reliability Issues, Strategic Co-Location and Centralization in m-Median Problems”, Operations Research, to appear.
R. Aboolian, O. Berman, and D. Krass, "Competitive Facility Location and Design Problem", European Journal of Operations Research, to appear.
R. Huang, S. Kim and M. Menezes, “Optimal Workforce Size and Allocation for Urban Retail Chains,” European Journal of Operational Research, to appear.
O. Berman, R. Huang, S. Kim and M. Menezes. “Locating Capacitated Facilities to Maximize Captured Demand,” IIE Transactions, to appear.
Hajizadeh, Iman and Lee, Chi-Guhn (2005), “Alternative Configurations for Cutting Machines in a Tube Cutting Mill”, Submitted to the European Journal of Operational Research.
Faculty and Research Interests
Area Coordinator
Joseph Milner
Associate Professor of Operations Management
Phone: 416-978-5552
E-mail:Joseph.Milner@rotman.utoronto.ca
PhD Coordinator
Dmitry Krass
Professor of Operations Management and Statistics
Phone: 416-978-7180
E-mail:Krass@rotman.utoronto.ca
Full-Time Faculty
Philipp Afèche
PhD, Stanford University
Research Interests: Supply Chain Management, Dynamic Pricing, Mechanism Design, Queuing Models
Igor Averbakh
PhD, Moscow Institute of Physics and Technology
Research Interests: robust optimization, facility location, complexity analysis, integer programming
Opher Baron
PhD, Massachusetts Institute of Technology
Research Interests: Pricing, Queuing Models, Applied Probability, Large Deviations
Oded Berman
PhD, Massachusetts Institute of Technology
Research Interests: Logistics, Operations Management in Service Industry, Workforce Management, Software Reliability
Dimitry Krass
PhD, John Hopkins University
Research Interests: Facility Location / Transportation, Inventory Analysis, Stochastic Dynamic Programming, Environmental Modeling, Marketing Models
Joseph Milner
PhD, Massachusetts Institute of Technology
Research Interests: Supply Chain Management, Dynamic Pricing, Service Operations Management
Ulrich Menzefricke
MBA, Indiana University
Primary research interests centre on the extension of models and methodology in the areas of decision theory and quantitative analysis, in particular, models of a statistical and probabilistic nature, and their application to business situations. Currently working on statistical quality control and analysis of scanner data
Bayesian Statistics and Statistical Quality Control
Ulrich Menzefricke
Decision-Making Models
Igor Averbakh
Opher Baron
Oded Berman
Dimitry Krass
Ulrich Menzefricke
Facility Location
Igor Averbakh
Oded Berman
Dimitry Krass
Logistics and Distribution
Opher Baron
Oded Berman
Joseph Milner
Operations Management in the Service Industry
Igor Averbakh
Oded Berman
Dimitry Krass
Joseph Milner
Operations Marketing Interface
Oded Berman
Dimitry Krass
Production Scheduling and Inventory Management
Opher Baron
Oded Berman
Michael Carter (Industrial Engineering)
Dimitry Krass
Joseph Milner
Risk Analysis and Environmental Management
Dimitry Krass
Stochastic Models
Opher Baron
Oded Berman
Dimitry Krass
Joseph Milner
Recent Graduates
Robert Aboolian (PhD ‘02) Associate Professor of Operations and Supply Chain Management,
College of Business Administration, California State University San Marcos
Mustafa Karakul (PhD ‘04) Associate Professor of Management Science, School of Administrative Studies, York University
Mozart Menezes (PhD ’04), Assistant Professor, Department Logistics and Operations Management, HEC Paris
Graduate Q&A
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Click here to read a Graduate Q&A with Anton Ovchinnikov (PhD in Operations Management, 2007) Assistant Professor of Business Administration, Darden School of Business, University of Virginia
Click here to read more Q&As with recent graduates.
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