Overview
Complete Pyomo Bootcamp Python is an Udemy Tutorial. Guide for building optimization probelm (operation research) in Pyomo Jupyter and solve it using CPLEX, Gurobi and IPOPT.
What you'll learn
- Write simple and complex pyomo models.
- How to mathematically formulate your optimization problems in Python?
- How to find the duality coefficients of the constraints ?
- Build a complete understanding of Pyomo models from the ground up!
- Is it suitable for Mechanical engineering ? Yes, for example : design problems.
- Is it suitable for Electrical engineering ? Yes, for example : optimal operation and planning of power plants, optimal power flow and etc.
- LP, MIP, MINLP, NLP ,QCP, MIQCP.
- Practice Exercises to Confirm the Learnings.
- Build the skills you need to get your first Operation research / Optimization job /OR Scientist position.
- How to start coding your optimization problem in Python (pyomo)?
- Linear programming, Mixed Integer programming, Quadratic programming, Non-linear Programming.
- Is it suitable for Chemical engineering ? Yes, for example : optimal design of chemical systems, optimal operation of chemical units, pooling-blending, optimal control of a process and etc.
- Is it suitable for Civil engineering ? Yes for example in traffic management, bridge design , reinforcement planning and etc.
Course Content
- Intro.
- Python and Pyomo Installation.
- Visualization in Python.
- MatPlotLib package.
- Pyomo Elements.
- Create a Dat file for AbstractModel.
- How to call a .dat file for initializing the instance in Abstract Models.
- Analysing the output.
- How to use the examples in this course?
- Biggest rectangle inside a circle.
- Biggest cylinder inside a Sphere.
- Fastest route.
- Heron problem.
- Steiner problem.
- System of linear equations.
- Hostile brothers in a rectangle.
- N-Queens.
- Circle placement in a rectangle.
- Biggest equal sized circles inside a unity circle.
- Clash of clans.
- Biggest circle on a surface with obstacles.
- Center of mass.
- Min Queens to cover the chess board.
- Connected tree.
- Spanning tree with degree constraints.
- Connected tour.
- Conference allocation.
- Max flow.
- Graph Node Coloring.
- Graph Edge Coloring.
- Facility allocation.
- Curve fitting.
- Paper company.
- Transportation.
- Hostile brothers in a triangle.
- Circle placement in a circle.
- Circle placement in a half-circle.
- Circle placement in a triangle.
- Center of mass (negative mass).
- Pareto optimal front.
- Dynamic Transportation Problem.
