CU1: Optimization Methods and Operations Research
Course Summary
This course unit offers an extensive overview of optimization methods and operations research, providing students with a solid understanding of fundamental concepts in mathematical modeling and optimization. Students will gain practical skills in implementing optimization algorithms using Python and will explore diverse applications in areas such as health, logistics, and sustainable energy. The curriculum emphasizes the combination of theoretical insights with hands-on experience through case studies, laboratory sessions, and integrated applied projects.Course Highlights
- Introduction to Optimization and Mathematical Modeling
- Linear and Mixed-Integer Linear Programming (MILP)
- Non-linear and Mixed-Integer Non-linear Programming (MINLP)
- Global Optimization Techniques
- Heuristics, Metaheuristics, and Multi-objective Optimization
- Optimization in Networks and Graphs
- Multi-Criteria Decision Making (MCDM)
- Integrated Applied Project