Optimization with Python: Solve Operations Research Problems

Solve optimization problems with CPLEX, Gurobi, Pyomo... using linear programming, nonlinear, evolutionary algorithms...

4.59 (1747 reviews)

Udemy

platform

English

language

Data Science

What you will learn

Solve optimization problems using linear programming, mixed-integer linear programming, nonlinear programming, mixed-integer nonlinear programming,

LP, MILP, NLP, MINLP, SCOP, NonCovex Problems

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

Course Gallery

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Optimization with Python: Solve Operations Research Problems – Screenshot 4 — Screenshot 4 – Optimization with Python: Solve Operations Research Problems

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Comidoc Review

Our Verdict

Optimization with Python: Solve Operations Research Problems serves as an excellent resource to enhance your optimization skills using popular tools like CPLEX, Gurobi, and Pyomo. The course features a wide range of examples and exercises that cater to both beginners and experienced practitioners. However, brace yourself for challenging content and occasional difficulty understanding the instructor's accent.

What We Liked

In-depth exploration of various optimization techniques, including linear and nonlinear programming, genetic algorithms, particle swarm, and constraint programming
Comprehensive coverage of main solvers and frameworks like CPLEX, Gurobi, and Pyomo
Rich set of examples and exercises that demonstrate problem-solving skills using Python
High-quality theoretical content supplemented with helpful reference materials

Potential Drawbacks

Some users may find the course content overly complex and demanding, requiring a solid background in optimization theory
Instructor's English pronunciation can sometimes be difficult to understand, affecting overall learning experience
Coding examples might benefit from better software engineering practices for improved readability
Exercises could be more interactive, avoiding long timers during problem-solving sessions