DEREE COLLEGE SYLLABUS FOR:
MG 4246 MANAGEMENT SCIENCE UK Level: 6
(same as LM 4246) UK Credits:15 15
US Credits: 3/0/3
(Revised: Spring 2015)
PREREQUISITES: MA 1009 Mathematics for Business, Economics and Sciences
MA 2021 Applied Statistics
CATALOG
DESCRIPTION:
RATIONALE:
Quantitative techniques used to provide insight into business decisions.
Topics include linear programming, sensitivity analysis, networks, decision analysis, waiting lines, Markov analysis and simulation.
The complexity of modern business has given rise to complex managerial problems. Expressing these problems quantitatively facilitates their solution through the application of the proper model. Knowledge of management science enables managers, consultants and auditors to obtain a documented approach to managerial problems solutions. In addition, modern business concepts, like customer relationships management and business analytics, require a basic understanding of quantitative methods. This course also provides an analytical framework to better comprehend the functional areas of management (accounting, finance, personnel, marketing, operations and information systems).
LEARNING OUTCOMES:
METHOD OF TEACHING AND
LEARNING:
As a result of taking this course, the student should be able to:
1. Analyze and evaluate important management science theories and models, and explain their impact on managerial decision making.
(analysis, evaluation)
2. Analyze real life managerial problems in order to select, adjust and assess the mathematical model that best suits the challenges faced.
(application, analysis, evaluation)
3. Apply management science models, analyze their outputs and implications, and recommend an appropriate course of action.
(application, analysis, evaluation)
In congruence with the learning and teaching strategy of the college, the following tools are used:
· Lectures, problem solving exercises, model applications, small case studies, the carrying out of a research project and in-class presentation.
· Office hours held by the instructor to provide further assistance to students.
· Use of the Blackboard Learning platform to further support communication, by posting lecture notes, assignment instruction, timely announcements, and online submission of assignments.
ASSESSMENT:
INDICATIVE
READING:
Summative :
Written project; Individual; 1,800-2,200 words
Final examination (2-hour, problem-solving)
Formative:
Two in-class diagnostic examinations and problem-solving exercises
40%
60%
0%
The formative coursework aims to prepare students for the written project and the final examination.
The written project tests Learning Outcome 1
The final examination tests Learning Outcomes 2 and 3
REQUIRED MATERIAL :
Render, Barry and Ralph M. Stair, Jr. Quantitative Analysis for Management.
Allyn & Bacon, latest edition
LIBRARY REFERENCES (on reserve):
1

1. Render, Stair and Greenberg. Cases and Readings in Management
Science. Allyn and Bacon, latest edition
2. Levin, R.I., D.S. Rubin, J.P. Stinson and E.S. Gardner, Jr. Quantitative
Approaches to Management. McGraw-Hill, latest edition, ISBN 0-07-
909187-3
RECOMMENDED READING:
Alexander, A., Walker, H., and Naim, M. (2014) "Decision theory in sustainable supply chain management: a literature review", Supply Chain
Management: An International Journal , Vol. 19 No. 5/6, pp. 504 – 522
Anderson, D., Sweeney D. and Williams T., An Introduction to Management
Science: Quantitative Approaches to Decision Mak ing, Thomson Learning .
Bernot, M., Caselles, V., Morel, J.M., Optimal Transportation Network s:
Models and Theory, Springer, 2009
Boudreau, K.J., Lacetera, N., and, Lakhani, K.R. (2011), “Incentives and
Problem Uncertainty in Innovation Contests: An Empirical Analysis”,
Management Science , Vol. 57 No. 5, pp. 843–863.
Cachon, G.P., and Swinney, R. (2011), “The Value of Fast Fashion: Quick
Response, Enhanced Design, and Strategic Consumer Behavior”.
Management Science , Vol. 57 No. 4, pp. 778–795.
David R. Anderson, Contemporary Management Science, Thomson
Custom Solutions Center, 2004
David R. Anderson, Dennis J. Sweeney and Thomas A. Williams,
Introduction to Management Science , South-Western Publishing Co., 2005
Delage, E., Arroyo, S., and Ye, Y. (2014), “The Value of Stochastic Modeling in Two-Stage Stochastic Programs with Cost Uncertainty”, Operations
Research , Vol. 62 No. 6, pp. 1377–1393
Drew Fudenberg and Jean Tirole, Game Theory, MIT Press, 1991
Etner, J., Jeleva, M., and Tallon, J-M. (2012), “Decision Theory Under
Ambiguity”, Journal of Economic Surveys , Vol. 26 No. 2, pp. 234–270
Frederick S. Hillier and Gerald J. Lieberman, Introduction to Management
Science, Richard D. Irwin, Inc, 2007
Gallien, J., Mersereau, A.J., Garro, A., Mora, A.D., and Vidal, M.N. (2015),
“Initial Shipment Decisions for New Products at Zara”, Operations
Research, Vol. 63 No. 2, pp. 269–286
Gen, Cheng and Lin, Network Models and Optimization, Springer, 2008
Gunter Bolch, Queuing network s and Mark ov chains , Wiley & Sons, 2006
Hillier – Lieberman, Introduction to Operations Research , McGraw-Hill, latest edition
Jerath, K., Netessine, S., and Veeraraghavan, S.K. (2010), “Revenue
Management with Strategic Customers: Last-Minute Selling and Opaque
Selling”, Management Science , Vol. 56 No. 3, pp. 430–448.
John A. Lawrence and Barry A. Pasternack, Applied Management Science
: A Computer-Integrated Approach for Decision Mak ing, John Wiley & Sons
2000
Lawrence L. Lapin and William D. Whisler, Cases in Management Science,
2

INDICATIVE MATERIAL:
(e.g. audiovisual, digital material, etc.)
INDICATIVE CONTENT:
Duxbury Press Cover, 1996
Michael Pinedo, Planning and Scheduling in Manufacturing and Services ,
Springer, 2009
Michael Pinedo, Scheduling: Theory, Algorithms and Systems , Springer,
2008
Moshe Sniedovich, Dynamic Programming: Foundations and Principles, 2e,
Routledge, 2010
Robert B. Cooper, Encyclopedia of Computer Science, John Wiley & Sons,
4th edition, 2003
Robert J. Vanderbei, Linear Programming: foundations and extentions,
Springer, 2008
Saul I. Gass, Linear Programming: methods and applications, Dover, 2003
Stephen G. Powell and Kenneth R. Baker, Management Science : The Art of Modeling with Spreadsheets, John Wiley & Sons 2007
Taylor, Introduction to Management Science , Pearson, latest edition
Timothy Kloppenborg, Contemporary Project Management, South-Western
Publishing Co., 2009
Wang, X. (2015), “A comprehensive decision making model for the evaluation of green operations initiatives”, Technological Forecasting &
Social Change
Wolsey Lawrence, Integer Programming, John Wiley & Sons, 1998
Wu, Z., and Pagell, M. (2011), “Balancing priorities: Decision-making in sustainable supply chain management”, Journal of Operations
Management , Vol. 29 No. 6, pp. 577-590
WWW RESOURCES: www.maths.mu.oz.au (Worms–World Wide Web for operations research
and management science) www.lumina.com (Decision / Risk Analysis) www.mcs.anl.gov www.managementscience.org
Use of spread sheet (e.g. MS-XL), Use of quantitative management software that comes with text book.
1. MS/OR and Information Systems
2. Decision Theory
3. Linear Programming
3.1. Graphical Methods
3.2 Simplex Method: Maximization and Minimization
4. Building LP Models and Interpreting Solutions
4.1. Problem Formulation
4.2. Duality
4.3. Sensitivity Analysis
4.4 LP Applications
5. Specially Structured Linear Programs
5.1. Transportation Problems
5.2 Assignment Problems
6. Networks
6.1. Scheduling with Resource Limitations
6.2. Maximal Flow Problems
3

6.3. Minimal-Spanning-Tree Problems
6.4. Shortest Route Problems
7. Waiting Lines
8. Simulation
9. Markov Analysis
10. Recent Approaches to MS/OR
10.1 Predictive Models in Business Intelligence
10.2 Risk Analysis
4