NYU Stern School of Business

Undergraduate College

MULT-UB.0007.001 (C70.0007): DECISION MODELS

Fall 2012

Instructor Details

Asadpour, Arash


Thursdays 5PM-6PM

KMC 8-60


Course Meetings

TR, 3:30pm to 4:45pm

Tisch T-UC15

Final Exam:

Schedule exceptions
    Class will not meet on:
    Class will meet on:


Course Description and Learning Goals

This course introduces the basic principles and techniques of applied mathematical modeling for managerial decision-making. You will learn to use some of the more important analytic methods (e.g. spreadsheet modeling, optimization, Monte Carlo simulation), to recognize their assumptions and limitations, and to employ them in decision-making. 

Students will: 

The emphasis will be on model formulation and interpretation of results, not on mathematical theory. The emphasis is on models that are widely used in diverse industries and functional areas, including finance, operations, and marketing. 


Course Outline

Spreadsheet Modeling – formulating optimization problems, using solver and interpreting the solver table.

Linear Programming– LP formulation, dual problem, multi-period modeling.

Non-linear Optimization – Evolutionary solver, portfolio optimization and other applications.

Integer Programming – Integer variables, integer solver, binary variables, logical relationships, linearizing non-linear functions, project selection, facility location, crew scheduling.

Network Optimization – Assignment problem, transportation problem, minimum-cost flow, funds-flow model, project management, currency exchange.

Simulation – Basic concepts, Crystal Ball software, option pricing, inventory applications, project management.

Note: This outline is tentative and subject to change.


Assessment Components

Homework Assignments: 40%

Quiz: 25%

Final Project: 25%

Class Participation: 10%


Group Projects

Guidelines for Group Projects

Business activities involve group effort. Consequently, learning how to work effectively in a group is a critical part of your business education.

Every member is expected to carry an equal share of the group’s workload. As such, it is in your interest to be involved in all aspects of the project. Even if you divide the work rather than work on each piece together, you are still responsible for each part. The group project will be graded as a whole:   its different components will not be graded separately. Your exams may contain questions that are based on aspects of your group projects.

It is recommended that each group establish ground rules early in the process to facilitate your joint work including a problem-solving process for handling conflicts. In the infrequent case where you believe that a group member is not carrying out his or her fair share of work, you are urged not to permit problems to develop to a point where they become serious. If you cannot resolve conflicts internally after your best efforts, they should be brought to my attention and I will work with you to find a resolution.

You will be asked to complete a peer evaluation form to evaluate the contribution of each of your group members (including your own contribution) at the conclusion of each project. If there is consensus that a group member did not contribute a fair share of work to the project, I will consider this feedback during grading.



At NYU Stern we seek to teach challenging courses that allow students to demonstrate their mastery of the subject matter. Assigning grades that reward excellence and reflect differences in performance is important to ensuring the integrity of our curriculum.

In general, students in this elective course can expect a grading distribution where about 50% of students will receive A’s for excellent work and the remainder will receive B’s for good or very good work. In the event that a student performs only adequately or below, he or she can expect to receive a C or lower.

Note that the actual distribution for this course and your own grade will depend upon how well each of you actually performs in this course.



The process of assigning grades is intended to be one of unbiased evaluation. Students are encouraged to respect the integrity and authority of the professor’s grading system and are discouraged from pursuing arbitrary challenges to it.

If you believe an inadvertent error has been made in the grading of an individual assignment or in assessing an overall course grade, a request to have the grade re-evaluated may be submitted. You must submit such requests in writing to me within 7 days of receiving the grade, including a brief written statement of why you believe that an error in grading has been made.


Professional Responsibilities For This Course




In-class contribution is a significant part of your grade and an important part of our shared learning experience. Your active participation helps me to evaluate your overall performance.
You can excel in this area if you come to class on time and contribute to the course by:




Classroom Norms


Stern Policies

General Behavior
The School expects that students will conduct themselves with respect and professionalism toward faculty, students, and others present in class and will follow the rules laid down by the instructor for classroom behavior.  Students who fail to do so may be asked to leave the classroom. 


Collaboration on Graded Assignments
Students may not work together on graded assignment unless the instructor gives express permission. 


Course Evaluations
Course evaluations are important to us and to students who come after you.  Please complete them thoughtfully.


Academic Integrity

Integrity is critical to the learning process and to all that we do here at NYU Stern. As members of our community, all students agree to abide by the NYU Stern Student Code of Conduct, which includes a commitment to:

The entire Stern Student Code of Conduct applies to all students enrolled in Stern courses and can be found here:

Undergraduate College: http://www.stern.nyu.edu/uc/codeofconduct
Graduate Programs: http://w4.stern.nyu.edu/studentactivities/involved.cfm?doc_id=102505

To help ensure the integrity of our learning community, prose assignments you submit to Blackboard will be submitted to Turnitin.  Turnitin will compare your submission to a database of prior submissions to Turnitin, current and archived Web pages, periodicals, journals, and publications.  Additionally, your document will become part of the Turnitin database.


Recording of Classes

Your class may be recorded for educational purposes


Students with Disabilities

If you have a qualified disability and will require academic accommodation of any kind during this course, you must notify me at the beginning of the course and provide a letter from the Moses Center for Students with Disabilities (CSD, 998-4980, www.nyu.edu/csd) verifying your registration and outlining the accommodations they recommend.  If you will need to take an exam at the CSD, you must submit a completed Exam Accommodations Form to them at least one week prior to the scheduled exam time to be guaranteed accommodation.


Required Course Materials

The textbook is recommended, but not required.



Course Pre-Requisites

Operations Management is the pre-requisitie for this course.

Moreover, Since the course relies on spreadsheets as a platform for model building, basic familiarity with Microsoft Excel is assumed. These include developing and copying formulas with relative and absolute cell addresses, and using the function and chart wizards. We will augment Excel with add-ins for the different modules of the course. In each case, full instructions regarding software access and use will be provided at the opportune time.

Knowledge of basic algebra (including functions such as the quadratic, exponential, and logarithmic), simple logic (as expressed in an IF statement or the MAX function), and basic probability (distributions and sampling, for example) will usually suffice.

Finally, one should not be averse to analytical thinking and quantitative analysis in general.


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