Pyomo Bootcamp: Python Optimization from Beginner to Advance
Guide for building optimization probelm (operation research) in Pyomo Jupyter and solve it using CPLEX, Gurobi and IPOPTWhat you'll learn
- Write simple and complex pyomo models
- LP, MIP, MINLP, NLP ,QCP, MIQCP
- How to mathematically formulate your optimization problems in Python?
- Practice Exercises to Confirm the Learnings
- How to find the duality coefficients of the constraints ?
- Build the skills you need to get your first Operation research / Optimization job /OR Scientist position
- Build a complete understanding of Pyomo models from the ground up!
- How to start coding your optimization problem in Python (pyomo)? Linear programming, Mixed Integer programming, Quadratic programming, Non-linear Programming
- Is it suitable for Mechanical engineering ? Yes, for example : design problems
- Suitable for Chemical engineering ? Yes, Optimal design of chemical systems, optimal operation of chemical units, pooling-blending, optimal control of a process
- Is it suitable for Electrical engineering ? Yes, for example : optimal operation and planning of power plants, optimal power flow and etc.
- Is it suitable for Civil engineering ? Yes for example in traffic management, bridge design , reinforcement planning and etc.
- Google Colab and Neos Server
Pyomo Bootcamp: Python Optimization from Beginner to Advance
Pyomo Bootcamp: Python Optimization from Beginner to Advance
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