Mathematical Optimization with GAMS and Pyomo (Python)

🚀 Mathematical Optimization with GAMS and Pyomo (Python): Unleash the Power of Algorithms to Solve Real-World Problems! 🧮🌍

Course Title:

Master Business Optimization with GAMS and Pyomo (Python)

Course Headline:

Learn how to mathematically formulate 16 business problems and find their optimal solutions with GAMS and Pyomo (Python)

Embark on a Journey Through the World of Optimization!

This comprehensive introductory course is meticulously designed to guide you through the intricacies of optimization using GAMS and Pyomo, both within the Python ecosystem. With 4 detailed modules, we delve into the core types of optimization that will empower you to tackle real-world business problems with mathematical precision.

Course Modules:

1. 📈 Linear Programming - Master the art of efficiency and resource allocation in linear environments.
2. 📉 Nonlinear Programming - Explore problems where relationships between variables are not necessarily linear.
3. ⚫️ Mixed Integer Linear Programming (MILP) - Dive into problems with both continuous and discrete variables.
4. ⚛️ Mixed-Integer Nonlinear Programming (MINLP) - Tackle complex problems involving both nonlinearity and mixed integers.

In each module, we dissect 3 diverse examples from fields like science, engineering, and management, followed by a challenging assignment. These practical scenarios are crafted to help you understand the real-world application of these optimization techniques.

What You'll Learn:

• Understanding Problem Statements: Translate complex real-world problems into mathematical models.
  • Identify key components: objective function, decision variables, constraints, and parameters.
• Coding in GAMS and Pyomo: Develop your skills in coding optimization models using these powerful tools.
  • In GAMS:
    • Define sets, variables, parameters, scalars, equations.
    • Utilize various solvers available in GAMS, including the NEOS server.
    • Import data from text, gdx, and spreadsheet files.
    • Export results to text, gdx, and spreadsheet files.
    • Set variable ranges and bounds to refine your models.
  • In Pyomo:
    • Define models, sets, variables, parameters, constraints, and objective functions.
    • Employ different solvers in Pyomo for problem-solving.
    • Access the NEOS server for advanced optimization capabilities.
    • Import/Export data between text, gdx, and spreadsheet files.
    • Control variable ranges and bounds to improve model performance.

By the end of this course, you will be equipped with a robust skill set to approach and solve optimization problems using GAMS and Pyomo effectively. Whether you're in business, economics, engineering, or any field where optimization can lead to better decisions and solutions, this course is your stepping stone to mastering mathematical optimization.

🎓 Enroll Now to start your journey towards becoming an expert in mathematical optimization with GAMS and Pyomo! 🌟