Complete Pyomo Bootcamp. Python Optimization From Beginner to Advance

In this course, you will learn how to deal with various types of mathematical optimization problems as below:

• Linear Programming (LP)

• Mixed Integer Linear Programming (MILP)

• Non-Linear Programming

• Mixed Integer Non-Linear Programming

Since this course is designed for all levels (from beginner to advanced), we start from the beginning that you need to formulate a problem. Therefore, after finishing this course, you will be able to find and formulate decision variables, objective function, constraints and define your parameters. Moreover, you will learn how to develop the formulated model in the Python environment (using the Pyomo package).

Here are some of the important skills that you will learn when using Python in this course:

1. Defining Sets & Parameters of the optimization model

2. Expressing the objective function and constraints as Python function

3. Import and read data from an external source (pdf file)

4. Solve the optimization problem using various solvers such as CPLEX, IPOPT, COUENNE &, etc.

5. 43 Downloadable resources

In this course, we solve simple to complex optimization problems from various disciplines such as engineering, production management, scheduling, transportation, supply chain, and … areas.

This course is structured based on 3 examples for each of the main mathematical programming sections. In the first two examples, you will learn how to deal with that type of specific problem. Then you will be asked to challenge yourself by developing the challenge problem into the Python environment. Nevertheless, even the challenge problem will be explained and solved with details.

Who this course is for:

• Students in all levels (Undergrad, Grad and PhD)
• Companies Who Wants to Use Optimization in Their Businesses
• Professionals in Various disciplines such as Engineering, Management and Operation Research
• Anyone Who is Interested to Learn Optimization and Coding in Python!