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COURSE
DESCRIPTION
Operations Research –
Stochastic Models (3) (3,0) (IME 461) (same as OR 441)
(Same as IME 461)
Spring and Summer Semester
2007
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2007- 2008 Catalog Data:
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461 – 3
Probabilistic models, elementary queuing theory with single or
multiple server systems, use of queues in facility designs, elementary
decision theory. Markov processes
and decision-making. Prerequisite(s): STAT 380 or STAT 480a
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Textbook(s):
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Operations Research:
Applications and Algorithms, 4th edition, 2008, Wayne L.
Winston, Duxbury Press.
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Coordinator:
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Song Foh
Chew, Associate Professor/Chair, Mathematics & Statistics
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Objectives:
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It is designed to teach modeling techniques for
solving stochastic constrained optimization problems in decision theory,
Markov models, queuing models and inventory. Forecasting is introduced.
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Topics and
Schedule:
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1. Decision
Making Under Uncertainty
2. Multiple
Objectives
3. Game Theory
4.
Deterministic EOQ Inventory Models
5.
Probabilistic Inventory Models
6. Markov
Chains
7.
Deterministic Dynamic Programming
8.
Probabilistic Dynamic Programming
9. Queuing
Theory
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Professional Component:
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This course introduces stochastic concepts to
senior-level industrial and manufacturing engineering students. The course
is an engineering topics course.
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Relationship
to Program Educational Objectives:
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Students successfully
completing this course will have the ability to:
1. Apply
game theory to operations research problems.
2. Construct
and analyze probabilistic inventory models.
3. Perform
both deterministic and stochastic dynamic programming.
4. Apply
queuing theory.
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Prepared
by:
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Song Foh
Chew, Mathematics & Statistics
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Date:
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January 24, 2007
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Program Educational Objective•Outcome
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General Course
Outcomes
IME 461 Operations Research: Stochastic Processes
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1
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2
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3
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4
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1.1
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1.2
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P
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P
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P
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1.3
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1.4
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2.1
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P
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2.2
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2.3
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2.4
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3.1
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3.2
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P
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P
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P
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P
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3.3
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3.4
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3.5
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4.1
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4.2
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4.3
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4.4
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