Optimization with GAMS: Operations Research Bootcamp A-Z

About Optimization with GAMS: Operations Research Bootcamp A-Z

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:

Define Sets, Parameters, Scalars, Objective Function & Constraints

Import and read data from an external source (Excel file)

Solve the optimization problem using various solvers such as CPLEX, IPOPT, COUENNE, BONMIN, ...

Create a report from your result in GAMS results

Export your results into an external source (Excel file)

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.