# Optimization with GAMS: Operations Research Bootcamp A-Z

Learn Mathematical Optimization and Operation Research, Linear & Non-Linear Programming, Multi Objective Optimization…

The art of decision making and finding the optimal solution to a problem is getting more and more attention in recent years. In this course, you will learn how to deal with various types of mathematical optimization problems as below:

What you’ll learn

• Basic Concepts and Terms Related to Optimization.
• How to Formulate a Mathematical Problem.
• Linear Programming and Coding LP Problems in GAMS.
• Mixed Integer Linear Programming (MILP) and Coding MILP Problems in GAMS.
• Non-Linear Programming (NLP) and Coding NLP Problems in GAMS.
• Mixed Integer Non-Linear Programming (MINLP) and Coding MINLP Problems in GAMS.
• Multi Objective Optimization.
• Sequential Goal Programming and How to Code a SGP Problem in GAMS.

Course Content

• Introduction –> 2 lectures • 6min.
• Introduction to Mathematical Optimization –> 1 lecture • 14min.
• GAMS Installation and Environment –> 3 lectures • 18min.
• Linear Programming (LP) –> 7 lectures • 1hr 48min.
• Mixed-Integer Linear Programming (MILP) –> 7 lectures • 1hr 47min.
• Non-Linear Programming (NLP) –> 7 lectures • 1hr 10min.
• Mixed-Integer Nonlinear Programming (MINLP) –> 7 lectures • 2hr 33min.
• Multi Objective Optimization –> 2 lectures • 36min.
• Flow Control Features –> 1 lecture • 10min.
• Conclusion –> 1 lecture • 3min. Requirements

• There is no prerequisites since this course is designed for complete beginners to mathematical optimization and I start from downloading and installing GAMS and prepare students for the course..

The art of decision making and finding the optimal solution to a problem is getting more and more attention in recent years. 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
• Multi-Objective Optimization

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 model that you formulated in the GAMS environment. Using GAMS, you will learn how to:

1. Define Sets, Parameters, Scalars, Objective Function & Constraints
2. Import and read data from an external source (Excel file)
3. Solve the optimization problem using various solvers such as CPLEX, IPOPT, COUENNE, BONMIN, …
4. Create a report from your result in GAMS results
5. Export your results into an external source (Excel file)
6. Deal with multi-objective problems and solve them using GAMS solvers

In this course, we solve simple to complex optimization examples from 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 GAMS. However, even the challenge problem will be explained and solved with details.

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