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Sep 25, 2024
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MATH 4630 - Discrete Modeling and Optimization
Modeling and solving real-life problems by discrete optimization techniques. The discrete models include integer programming, dynamic programming, network optimization problems. Applications in large economic systems, scheduling, voting theory, telecom and transportation networks are discussed.
Requisites: MATH 3300
Credit Hours: 3
Repeat/Retake Information: May be retaken two times excluding withdrawals, but only last course taken counts.
Lecture/Lab Hours: 3.0 lecture
Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I
Learning Outcomes: - Students will know how to build optimization models using binary integer variables, dynamic programs, and mathematical networks;
- Analyze the algorithms in terms of their accuracy and efficiency.
- Apply algorithms to solve the optimization problems.
- Understand the theory behind the algorithms.
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