数据模型与决策
An Introduction to Management Science
HSBC School of Business, Peking University
Fall 2008
Instructor: Dongming Zhu
Required textbook: An Introduction to Management Science: Quantitative Approaches to Decision Mak-
ing, 11th Edition, David R. Anderson, Dennis J. Sweeney & Thomas A.Williams. English version is available
in the library.
References: Introduction to Operations Research, F.S. Hillier and G.J. Lieberman.
Grading: All case problems in the text and a …nal exam will count toward the grade as follows:
Case problems 50%
Final 50%.
Course Outline:
This course is an introduction to Management Science with focus on applications of the most widely
used management science techniques, including linear programming, integer programming, network models,
simulation, and so on. Students are strongly recommended to read the text throughout and carefully. Most
of assignments and projects will be computer exercises so that students are required to learn computer
software such as Microsoft Excel and Management Scientist.
Topics
1. Introduction: Origins of Management Science / Operations Research / Decision Science, Problem
Solving and Decision Making, Qualitative and Quantitative Analysis, Management Science Techniques
2. Linear Programming (LP)
(a) Graphical solution procedure
(b) Sensitivity Analysis and Interpretation of Solution
(c) Linear Programming Applications
(d) Simplex Method
(e) Simplex-Based Sensitivity Analysis and Duality
3. Transportation, Assignment, and Transshipment Problems
4. Integer Linear Programming: Applications Involving 0–1 Variables
5. Network Models: Shortest-Route Problem, Minimal Spanning Tree Problem, Maximal Flow Problem
6. Project Scheduling: Program Evaluation and Review Technique (PERT) and Critical Path Method
(CPM)
7. Inventory Models: Economic Order Quantity (EOQ) Models, Inventory Models with Probabilistic
Demand
8. Simulation: Inventory Simulation, Waiting Line Models and Simulation
9. Decision Analysis: without / with Probabilities, with Sample Information, and with Utility
10. Multicriteria Decision Problems: Goal Programming, Scoring Models, Analytic Hierarchy Process
(AHP)
11. Markov Processes: Market Share Analysis, Accounts Receivable Analysis
12. Dynamic Programming