1433 Course Syllabus

Topics: Decision theory, Risk, Decision making software Pages: 9 (2160 words) Published: January 11, 2015
NATIONAL TAIWAN UNIVERSITY OF SCIENCE AND TECHNOLOGY
DEPARTMENT OF INDUSTRIAL MANAGEMENT
IM5508701 Decision Analysis – Fall 2013
Time Tuesday, 1:30pm – 4:20pm, Room MA101
Instructor: Shi-Woei Lin (林希偉), Office: MA424, (02)2737-6329, shiwoei@mail.ntust.edu.tw

Course Outline: For coping with problems of uncertainty, multiple objectives, and complexity, decision analysis provide a logical framework for structuring and formulating a decision scenario, characterizing variability and uncertainty, and leading to an action plan which incorporating the decision make’s value and preferences. This course is intended for students who are interested in using formal models to support decision making regardless of functional area. It introduces students to the theory and practice application of decision analysis. Topics covered include decision trees, influence diagrams, Bayesian networks, utility theory, multiattribute value theory (MAVT), analytic hierarchy process (AHP), data envelopment analysis (DEA), and behavioral decision making (including heuristics and biases).

Course Objectives: This course introduces students to the quantitative decision models for managerial decision making, and has three specific learning goals: (1) Understand basic decision analysis tools and methods.

(2) Improve quantitative reasoning ability.
(3) Gain an appreciation for the current state of the field and current research issues. Pre-requisites: Undergraduate Statistics or equivalent. Previous courses in Decision Analysis would be helpful, but not required. Any exceptions or special circumstances must be cleared with the instructor.

Main Text: Clemen, R.T and T. Reilly (2000) Making Hard Decisions with DecisionTools, Duxbury Press, Belmont, CA. (雙葉書廊書局代理)
Reference Texts:
(1) Keeney, R. L. and H. Raiffa (1993) Decisions with Multiple Objectives, Cambridge University Press, Cambridge, England. (2) 簡禎富 (2005) 決策分析與管理 : 全面決策品質提升之架構與方法, 雙葉書廊書局出版, 台北。 Software: The textbook should include a CD-ROM with software to help you solve some decision analysis problems. Other learning version software can be download from company or course web site.

Assignments: Each student need to complete three major assignments: (1) There will be some homework assignments announced in class (and possibly provided on our course web site). You are allow to work in groups if you choose. However, you must submit your own work if you are asked to turn in your homework. Homework assignments will generally include some of the analytical (mostly quantitative) problems. Unless otherwise mentioned, you will NOT need to turn in your solutions for the homework assignments. (Partial) solutions to the homework assignment may be posted on the course web site one week after the assignment is handed out. (2) Present and discuss one article for the class. Each team will chose one article from the syllabus. The presentation may include a summary and discussion of the paper’s contributions, derivation of key results if it is critical, and a critique or comment of the 1

analysis or model used in the article. You are welcome to provide notes to your classmates. As a follow-up, you will need to hand in a written critique of the article. The length of the critique should be around 2 to 3 double-spaced pages. You are also suggested to follow the general format of a referee report: Part 1 should summarize the key results and highlights of the article. Part 2 should describe major issues that you have with this article, and Part 3 might include less crucial issues. The critique will be due to me within a week after your in-class presentation.

(3) Complete a term paper, done in a team of two or three, on a topic of interest to you that is related to decision analysis. The topic could be an application of decision analysis, a review or essay on a specific research area or types of applications, or a prospective discussion of a specific research topic in decision analysis that you think...
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