Companies in many industries can employ stochastic OR to improve
their business practices and increase profitability. For example, in the
financial services sector, planners, analysts, and portfolio managers use
stochastic modeling to manage their assets and liabilities and optimize their
portfolios. When choosing investment vehicles, it is critical to be able to
view a variety of outcomes under multiple factors and conditions, some of which
are stochastic. Another example is that the insurance industry relies heavily
on stochastic modeling to predict how company balance sheets will look at a
given point in the future.
Imagine that you are a store manager. How do you manage your
inventory level? High inventory implies higher costs. On the other hand, low
inventory usually leads to out of stock. What is your optimal inventory
decision while considering the uncertainty of future demand?
Another example we will explore in the class: imagine that you are
the manager of an airline call center. If you expect the number of calls to
increase by 20~50% since a holiday is coming, how many additional agents should
you add to handle the higher demand? More agents imply higher costs, while less
agents may increase customer waiting. We will model the call center as a
queueing system and apply queueing theory to find a good decision.
In this class, we will cover several important stochastic models
in Operations Research:
In the term project, students will develop Monte Carlo simulation
(using basic Excel) to analyze how various investment portfolios may perform
based on the probability distribution of individual stock returns and determine
good investment decisions.
Instructor: Professor
Chun-Hung Chen
Email: cchen9@gmu.edu
Office: Engineering Building,
Room 2213
Zoom link: provided in the BB
Phone: 703-993-3572
Fax: 703-993-1521
Office Hours: Wednesday 3:30 - 4:30PM; Friday 9:30-10:30AM
Teaching Assistant: TBA
Required Text: W. L. Winston, "Operations Research:
Applications and Algorithms" 4th edition, 2004. Two copies of the textbook
have been placed on reserve at the Johnson Center Library. It may be borrowed
for 2 hours at a time. To borrow the book, you will need the call number:
T57.6.W645 2004.
Grading: There are two options:
In either option, a typical scale
will be applied to determine the final letter grade, i.e., B- for >80; B for
>83; B+ for >87; A- for >90; A for >93; etc.
In-class quiz:
Two quizzes will be given each week: one before the
middle break and another one near the end of the class.
Examinations: The two exams will be held in class. Make-up exam questions will be MUCH HARDER than
regular exam questions.
There is no
final exam. We will do a term project near the end of the semester.
Term Project is about the use of Monte Carlo simulation.
Students will develop simulation (using basic Excel) to analyze how various
investment portfolios may perform and determine good investment decisions.
Details will be given during the semester. The goal is to learn how a
stochastic modeling tool can be easily applied to real-life problems, and to
appreciate the power of simulation.
Canvas (to
log in, please click here):
Homework
assignments, solutions, ppt files of lectures, lecture recording, and sample
exam questions can be downloaded at Canvas.
Specifically,
1. You can download ppt files of lectures in the
"Modules" section.
2.
Lecture recordings
from previous years are
available in the "Modules" section.
3. Homework
assignments and term project are available in the "Assignments" section.
4. Solutions to
homework will be posted in the "Modules" section after
submission deadline.
5. Sample exam
questions and their solutions can be downloaded in
the "Modules" section.
General Rules:
1. Homework must be submitted as a single pdf file through
Blackboard.
2.
Late
homework is always allowed. No need to get advanced permission. However, the
penalty for late homework is 25% for the first day and then 5%
per day. No exemption.
3.
No
collaborations are allowed for homework, although discussions are encouraged.
4.
Comments are
strongly encouraged.
5.
No cheating.
Course
Outline & Reading Assignment:
|
Topics |
Time (week) |
Reading Assignment |
A |
Introduction |
1 |
|
B |
Probability review |
2 |
Chapter 12 |
C |
Inventory Models |
3 |
Chapters 15 & 16 |
D |
Markov chains |
2 |
Chapter 17 |
E |
Queueing theory |
2 |
Chapter 20 |
F |
Simulation (using basic Excel) |
2 |
Skim Chapters 21, 22, 23 |
Go to Professor Chun-Hung Chen's Page
Additional University Policies
Academic Standards:
GMU
Common Course Policies - Stearns Center for Teaching and Learning
Academic
Standards exist to promote authentic scholarship, support the institution's
goal of maintaining high standards of academic excellence, and encourage
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University Calendar:
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The George Mason University Writing Center staff provides a variety of resources and services (e.g., tutoring, workshops, writing guides, handbooks) intended to support students as they work to construct and share knowledge through writing. You can now sign up for an Online Writing Lab (OWL) session or for a face-to-face session in the Writing Center, which means you set the date and time of the appointment! Learn more about the Online Writing Lab (OWL) (found under Online Tutoring).
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If you wish, please share your name and gender pronouns with me and how best to address you in class via email or during class introductions. I use she/her for myself, and you may address me as Dr. Last Name in emails and verbally.
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George Mason University promotes a living and learning environment for outstanding growth and productivity among its students, faculty, and staff. Through its curriculum, programs, policies, procedures, services, and resources, Mason strives to maintain a quality environment for work, study, and personal growth. An emphasis on diversity and inclusion throughout the campus community is essential to achieve these goals. Diversity is broadly defined to include such characteristics as, but not limited to, race, ethnicity, gender, religion, age, disability, and sexual orientation. Diversity also entails different viewpoints, philosophies, and perspectives. Attention to these aspects of diversity will help promote a culture of inclusion and belonging and an environment where diverse opinions, backgrounds, and practices have the opportunity to be voiced, heard, and respected. The reflection of Mason's commitment to diversity and inclusion goes beyond policies and procedures to focus on behavior at the individual, group, and organizational levels. The implementation of this commitment to diversity and inclusion is found in all settings, including individual work units and groups, student organizations and groups, and classroom settings; it is also found with the delivery of services and activities, including, but not limited to, curriculum, teaching, events, advising, research, service, and community outreach. Acknowledging that the attainment of diversity and inclusion are dynamic and continuous processes and that the larger societal setting has an evolving socio-cultural understanding of diversity and inclusion, Mason seeks to continuously improve its environment. To this end, the university promotes continuous monitoring and self-assessment regarding diversity. The aim is to incorporate diversity and inclusion within the philosophies and actions of the individual, group, and organization, and to make improvements as needed.
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As a member of the George Mason University community, the Volgenau School of Engineering plays an integral role in building an educational environment that is committed to anti-racism and inclusive excellence. An anti-racist approach to higher education acknowledges the ways that individual, interpersonal, institutional, and structural manifestations of racism against Black individuals and other people of color contribute to inequality and injustice in our classrooms, on our campuses, and in our communities and it strives to provide our community members with resources to interrupt cycles of racism so as to cultivate a more equitable, inclusive, and just environment for all of our students, staff, faculty, alumni, and friends, regardless of racial background.
To be anti-racist means:
To make constant, conscious decisions to interrupt racism and cultivate equity, inclusion, and justice for people of all racial backgrounds, and in particular those from Black communities and other communities of color, who are most likely to bear the direct and indirect costs of systems of white supremacy;
To interrogate histories of white supremacy and white-dominant culture, and to examine the ways in which these histories have impacted our individual beliefs, our interpersonal relationships, our institutional and structural policies and processes, and our entire society;
To make a commitment to being responsible for our own relationships to, and actions within, systems of white supremacy; and
To cultivate a practice of self-awareness and self-reflection that allows us to critically evaluate our own role in upholding white supremacy and identify the ways we can interrupt cycles of racism at the individual, interpersonal, institutional, and structural levels.
We believe that the work of anti-racism starts with each individual and that in cultivating an anti-racist approach to research, scholarship, and practice, our students will build a skill set rooted in principles of equity, inclusion, and justice that they will carry with them throughout their lives.
For more information on how to continuously cultivate the practice of anti-racism, see this guide from the National Museum of African American History and Culture on how to be anti-racist:
https://nmaahc.si.edu/learn/talking-about-race/topics/being-antiracist