IE 381 - Deterministic Modeling and Optimization

3 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 2314 or MA 231)

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
Graphical solution of linear programming LP problems
Applications of LP
Computer solutions to LP problems
LP sensitivity, duality
Transportations & assignments algorithms
Network analysis algorithms
Inventory control models
Introduction to integer and goal programming
Dynamic programming and meta-heuristic optimization

Coordinator
Dr. Aaron Armstrong

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IE 381 - Deterministic Modeling and Optimization