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May 05, 2024
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IE 381 - Deterministic Modeling and Optimization3 lecture hours 0 lab hours 3 credits
Course Description
Modeling requires building a logical or mathematical representation of a system and using the model to assist the decision making process. This course examines modeling techniques for systems in which the variables influencing performance are deterministic (non-random). These techniques include linear programming, transportation and assignment algorithms, inventory models and network analysis. Case studies and computer algorithms are utilized. (prereq: MA 127 , junior standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• understand, develop, and apply deterministic (non-random) mathematical models to engineering and operational problems
• use these models to assist the decision-making process
• develop an understanding of how these methods impact business and industry
• use computer software to solve these engineering problems
• improve problem solving skills
• improve communications skills
Prerequisites by Topic
• College algebra
• Mathematical procedures for solving systems of linear equations
Course Topics
• Introduction to quantitative management (2 classes)
• Graphical solution of linear programming LP problems (4 classes)
• Applications of LP (3 classes)
• Computer solutions to LP problems (2 classes)
• LP sensitivity, duality (3 classes)
• Transportations & assignments algorithms (3 classes)
• Network analysis algorithms (3 classes)
• Inventory control models (4 classes)
• Introduction to integer and goal programming (2 classes)
• Examinations (3 classes)
Laboratory Topics
• No laboratory
Coordinator
Aaron Armstrong
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