University of Alberta School of Business Department of AOIS
Operations Management 461/686 Syllabus – Fall 2014
Instructor: Chris Neuman Phone: 780-442-6426 (work) E-Mail: [email protected]
Office Hours: Afternoons after 4:30 or by appointment. Instead of formal office hours I rely heavily on online communication.
Lectures: Wednesdays, 6:00 – 8:50, BUS 3-06
Course webpage: Access from https://ulearn.ualberta.ca . You should all be
automatically enrolled in the course webpage. If you are not, please contact me ASAP.
Course Description
This course examines the distribution of products and services from some initial point(s) of origin to customers. Distribution problems are critical to the provision of goods and services and are found in almost every corporate enterprise, as well as government, non-profit agencies, and the military. We cover many topics at the operational level, such as the selection of delivery routes and vehicle dispatching systems. However, we will also step back and consider strategic decisions, such as warehouse location and aggregate distribution plans.
The emphasis in this course is on analytical modeling, design, and problem solving. Each topic will begin with a theoretical discussion, and then move to a model formulation and examples. In some cases, we will spend time on heuristic techniques in addition to or instead of exact solution methods. Homework assignments and projects allow you to explore the topics in more detail, while quizzes will be used to test your understanding of the material. By the end of this course you should have an overall knowledge of most distribution problems as well as the skills to approach, setup, solve, and speak
knowledgably about those problems.
This course has a significant computer component. We will be using Microsoft Excel and the Solver tool extensively. The Business labs and classrooms use Excel 2010, but if you have Excel 2007 or 2003 there should be no problems accessing course content. You will also be exposed to Geographic Information System (GIS) technology and data.
Textbook
There is no official textbook for this course. All course content will be posted on the course webpage in a format suitable for printing if desired (i.e. PDF, Word, PPT).
Lectures will rely heavily on spreadsheet models, which will also be available through the website. I do not typically print lecture materials.
There are a number of good reference materials that explain the theory and application of the topics covered this course. Most are available in the University Library. I have personal copies of a number of these texts, and can arrange for short-term lending. A list will be posted on the course website.
Lectures
The regular meeting room for the class is BUS 3-06. This classroom enables us to use spreadsheets and access online course materials.
Please make your best effort to arrive to class on time, to minimize disruptions.
Please turn off cell phones and pagers, remove headphones, and mute your laptops when in class.
There will be a 10-15 minute break halfway through the class, and the lecture will always end at 8:50 or earlier to ensure nobody misses a bus or their ride.
Learning Outcomes
This course incorporates the Learning Goals of the BCom program, in particular:
• Quantitative Skills – throughout the course, you will learn new tools for solving quantitative problems, while also learning the technical limitations of those tools);
• Written Communication – homework assignments, quizzes, and projects will all have a written component, where you will be challenged to communicate ideas in a clear and concise manner, with proper report structure and grammar, and with the right tone and technical level for the intended audience.
• Teamwork – project work will be completed in groups, giving you an opportunity to exercise your teamwork skills.
There is a similar set of MBA learning goals, which also align with this course.
Grading
This course will be graded in accordance with the School of Business’s Grading Guideline. The breakdown of marks for the course is as follows:
Homework Assignments (30% total)
I will assign 4-5 homework assignments through the term, to be completed individually. You will have approximately one week from when the assignment is posted to submit. Submissions are online through the course web and
grades/comments will be returned to you the same way. Each assignment will have equal weight in your final grade, regardless of the raw score.
I try to have assignments back to the class within a week of submission. If you have questions or concerns about your grade, please e-mail me so I have a record of our conversation. The official record of grades is the online grade book; it is your responsibility to make sure this record is accurate.
Quizzes (20% each, total 40%)
There will be two quizzes, which will be held during scheduled class time. The quizzes will be held in the Business computer labs (details to come), and will require you to set up and solve problems in Excel using the Solver tool. You will have access to all class materials and may be required to run existing VBA code that is provided for you (you will not be required to code VBA). Each quiz will be weighted equally.
Group Projects (15% each, total 30%)
There will be two projects assigned during the course, with one due in mid-October and the other due at the end of the term. The projects will be completed in groups of 2-4 at my discretion, based on final enrolment numbers.
The first project will require you to implement a “real-sized” problem we discuss in class. By “real-sized” I mean you will be given a large dataset and constraints that make the problem harder to solve than the problems we discuss during lecture. You will submit your model and a writeup of your method and will be graded on how well the model performs and your ability to explain in plain English the approach you took to solve the problems.
The second project will continue to use the same data set from the first project but will focus on routing models. As with Project 1, your deliverable will be a writeup of your method and results.
At the end of the term, all term marks will be converted to a final score out of 100 that uses the weightings set out above. When converting from this final score to a letter grade I look for natural breakpoints that define clusters of students, so that a change in
Academic Integrity
This is what we must say in every syllabus about academic integrity:
The University of Alberta is committed to the highest standards of academic integrity and honesty. Students are expected to be familiar with these standards regarding academic honesty and to uphold the policies of the University in this respect. Students are particularly urged to familiarize themselves with the provisions of the Code of Student Behaviour (online at http://www.governance.ualberta.ca) and avoid any behaviour which could potentially result in suspicions of cheating, plagiarism, misrepresentation of facts and/or participation in an offence. Academic dishonesty is a serious offence and can result in suspension or expulsion from the University. (Section 23.4(2)c)
Plagiarism is a serious violation of both written and unwritten codes of academic conduct. It degrades the value of your future degrees and, since I am an alumnus of the School, it affects the value of my own degree as well. I will pursue formal proceedings if I suspect anyone of violating these rules.
Conversation about assignments and peer help in the class is not plagiarism. I expect that, as 3rd and 4th-year students, you all know the difference between working together and copying another’s work and will govern yourselves accordingly.
Schedule
This schedule is tentative. Any changes will be announced in advance and posted on the course website. Lecture attendance is strongly encouraged; the slides and notes on the course webpage are not a good substitute for lectures.
Date Content
Sep 03 Intro to DM; Distance Metrics
Sep 10 Algebraic Notation; Shortest Path Problems and Dijkstra’s Algorithm Sep 17 Set Covering and Max Covering
Sep 24 P-Center; P-Median Problems
Oct 01 P-Median Problems; Intro to Routing
Oct 08 Geographic Information Systems (GIS) – Class in GSB Lab Oct 15 Quiz 1; In-class time for Project 1
Oct 22 Travelling Salesman Problems Oct 29 TSP Heuristics
Nov 05 Vehicle Routing Problems Nov 12 Class Cancelled
Nov 19 Metaheuristics; Arc Routing
Nov 26 Course Evaluations; Wrap-up; In-class time for Project 2 Dec 03 Quiz 2
