Optimization with Python: Solve Operations Research Problems
Optimization with Python: Solve Operations Research Problems
Solve optimization problems with CPLEX, Gurobi, Pyomo… using linear programming, nonlinear, evolutionary algorithms…
Created by Rafael Silva Pinto | 12.5 hours on-demand video course
Operational planning and long term planning for companies are more complex in recent years. Information change fast, and the decision making is a hard task. Therefore, optimization algorithms are used to find optimal solutions for these problems. Professionals in this field are the most valued ones.
The classes use examples that are created step by step, so we will create the algorithms together. Besides this course is more focused in mathematical approaches, you will also learn how to solve problems using artificial intelligence (AI), genetic algorithm, and particle swarm.
Don’t worry if you do not know Python or how to code, I will teach you everything you need to start with optimization, from the installation of Python and its basics, to complex optimization problems. Also, I have created a nice introduction on mathematical modeling, so you can start solving your problems. I hope this course can help you in your carrier. Yet, you will receive a certification from Udemy.
Operations Research | Operational Research | Mathematical Optimization
What you’ll learn
- Solve optimization problems using linear programming, mixed-integer linear programming, nonlinear programming, mixed-integer nonlinear programming,
- LP, MILP, NLP, MINLP
- Main solvers and frameworks, including CPLEX, Gurobi, and Pyomo
- Genetic algorithm, particle swarm, and constraint programming
- From the basic to advanced tools, learn how to install Python and how to use the main packages (Numpy, Pandas, Matplotlib…)
- How to solve problems with arrays and summations
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