Modeling and optimization with GAMS

Title of the course

Modeling and optimization with GAMS

Teacher

Thomas I. Maindl

Course description

(scope, content)

We present how to use GAMS (General Algebraic Modeling System) for modeling and solving optimization problems. GAMS is a modeling system for mathematical programming and optimization, designed for modeling linear, nonlinear and mixed integer optimization problems. The course comes with its own example model library and includes many hands-on exercises throughout the curriculum.

The topics covered include

• the foundations of mathematical programming, modeling, and optimization algorithms
• working with the GAMS IDE and/or GAMS Studio
• map decision problems in science to the basic objects of optimization models: indices, data, variables, constraints, and objective functions
• how to analyze and understand existing models
• where to look for more information

Learning goals

• Advance analytics skills by building your own models
• Get an overview of mathematical optimization
• Learn how to use GAMS to solve real-world optimization problems
• Build, understand, enhance, and modify GAMS models

Target group

Only WU participants: PhD candidates, Postdocs, researchers who need to build, maintain, and use quantitative optimization models

Prior knowledge required

Some programming in any programming language

Group size

(minimum and maximum)

10 – 15

Duration of the course

4 days (March 24-27, 2020)

Will the course be given again

No

Credit points

1.3

Self-study hours

4

Is (preparing) home work involved

No

Teaching methods that are used during the course (lectures, group work, practical etc)

Lectures, exercises (single persons or group work depending on participants)

Programme

• Introduction to Mathematical Optimization
• Introducing GAMS
  • Structure
  • The GAMS Integrated Development Environment (GAMS IDE)
  • FirstModelingExercise
• GAMS Language 1: Objects in Optimization
  • Data Objects: Sets, Scalars, Parameters, Tables
  • Variables
  • Equations
  • Models and Model Attributes
  • Output Files, Debugging
• GAMS Language 2: Programming Language Features
  •  Conditional Expressions
  • Procedural Language Elements
• GAMS File I/O
  • Text File Input
  • Formatted Text File Output
• GAMS Data Exchange (GDX)
  • GDX Basics
  • MS® Excel Integration with GDXXRW
• Optional Mixed-integer Linear Programming Exercise: “big M” Method
• Closing
  • Comments on Modeling Practice
  • GAMS Resources
  • Final Discussion

Venue

Wageningen UR campus (exact location to be decided)

Fee

Fee WU-PhD with TSP € 400 / Other WU staff € 800