Operations Management 33:623:386
(sections 5 & 6)
Andrzej
Ruszczynski
Objectives
The main
purpose of this course is to present basic ideas of rigorous models of planning
and decision-making problems arising in certain business contexts.
This
mindset is called Management Science (MS) or Operations Research (OR).
It involves forming (imperfect) mathematical models of business situations,
analysing these models, and then deciding on some course of action.
MS/OR is
most helpful in situations where quantitative information is plentiful, and
there are relatively few intangible or psychological considerations, making it
easier to produce rigorous models. It is also particularly beneficial when the
decision or planning situation is complex, making it hard for managers to
simply eyeball the decision. Such situations arise most often at the operational level of
the management hierarchy.
We shall
discuss basic classes of most useful models, describe their properties, present
corresponding solution methods, and illustrate various applications of the
theory to manifold practical problems. Much stress will be put on the use of
spreadsheets for modeling and solution techniques.
Time and Place
|
Section 05: |
TF (12:00-1:20) |
|
|
BE-253 |
|
Section 06: |
TTh (1:40-3:00) |
|
|
BE-251 |
Office Hours
Thursday
3:20—5:00 PM in 251 J.H. Levin Building, 94 Rockefeller Road, Livingston Campus;
tel.: (732) 445 3422; E-mail: rusz@business.rutgers.edu
Course Materials
``Operations
Management'' course pack (based on our earlier course materials and exams and
edited by J. Eckstein). Homework assignments and other information can be
obtained from the course Web page http://www.rusz.rutgers.edu/omsyl.htm
Graded Work
Homework
will be assigned in most weeks as a means to help you understand the concepts
and to give you practice in applying them. It will be due in on specified days,
and it will be graded and returned to the student. Late homework will not be accepted.
There
will also be two 80 min. midterm in-class examinations and a 3 hour final
examination.
A
student's course grade will be based on the final course average, in computing
which the graded work will be weighted as follows:
|
Homework |
20% |
|
Midterm 1 |
20% |
|
Midterm 2 |
20% |
|
Final exam |
40% |
All
examinations are closed-book and students may use only a two-page ``cram
sheet" in their own handwriting.
Computer Lab
If you
have not yet been introduced to the School of Business Microcomputer Facility (in
the Levin building basement) it is your responsibility to take the required
introductory seminar and obtain an account, which is now necessary for all
students using the lab. You may use your own computer if it has Excel with Solver add-in
installed. In that case, however, all compatibility problems are your own
responsibility.
Plan of Lectures
|
Lecture |
Time |
Topic
|
|
|
|
|
|
1 |
Jan 22 |
Motivation.
Product Mix. |
|
2 |
Jan 24/25 |
Spreadsheet
review [in lab]. |
|
3 |
Jan 29 |
Geometry
of Linear Programs. , 12Diet Problem. |
|
4 |
Jan 31/Feb 1 |
Process
Models. |
|
5 |
Feb 5 |
Linear
Programming Models: Blending |
|
6 |
Feb 7/8 |
Linear
Programming Models: Multiperiod Planning |
|
7 |
Feb 12 |
Linear
Programming Models: Investment Planning |
|
8 |
Feb 14/15 |
Network
Models. |
|
9 |
Feb 19 |
Combined
Network--Production Models |
|
10 |
Feb 21/22 |
The
Critical Path Model. Crash |
|
11 |
Feb 26 |
Introduction
to Integer Programming. Knapsack. |
|
12 |
Feb 28/29 |
Review. |
|
13 |
Mar 4 |
Midterm
1. |
|
14 |
Mar 6/7 |
0--1
Variable Grids. |
|
15 |
Mar 11 |
Set
Covering Problems. Logical Constraints. |
|
16 |
Mar 13/14 |
Fixed
Charge Models. |
|
17 |
Mar 25 |
Large-scale
Mixed-Integer Models. |
|
18 |
Mar 27/28 |
Introduction
to Stochastic Models. |
|
19 |
Apr 1 |
Simulation
Tools in Excel [in lab]. |
|
20 |
Apr 3/4 |
Binomial
and Poisson Distribution. |
|
21 |
Apr 8 |
Simulating
Continuous Variables. |
|
22 |
Apr 10/11 |
Review. |
|
23 |
Apr
15 |
Midterm
2. |
|
24 |
Apr 17/18 |
Central
Limit Theorem. |
|
25 |
Apr 22 |
Introduction
to Dynamic Simulation. Inventory |
|
26 |
Apr 24/25 |
Multidimensional
Stochastic Dynamic Systems. |
|
27 |
Apr 29 |
Queues. |
|
28 |
May 1/2 |
Class
Overview. |
|
|
May 12 |
Final Examination (all topics), Lucy Stone Auditorium 12:00—3:00 PM |