Complete guide to Modern Mathematical Optimization in GAMS
- 3 hours on-demand video
- 18 downloadable resources
- Full lifetime access
- Access on mobile and TV
- Certificate of Completion
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- GAMS installation
- Model any kind of optimisation (LP, NLP, MILP, MINLP)
- Multi-Objective Optimization
- Conditional statements
- Loop statements
- You can start now without any prior knowledge in GAMS
The developed course is suitable for you even if you have no background in programming. The course is devoted to general optimization problems in GAMS.
In this course, you will learn how to use GAMS for solving optimization problems.
First of all, you will learn how to install GAMS on your machine.
What is optimization? What is the objective function? What is the constraint?
You understand the meaning of different errors and the way you should debug them
How to read/write from/to an Excel file
Multi-Objective optimization in GAMS
How to code conditional statements in GAMS
How to code Loop statements in GAMS
- Applied maths
- Operation research
Before you start this module please have quick look at this video
In this lecture, you will become familiar with the optimization elements
By this lecture you will learn more about the structure of GAMS
This gives you a big picture of what you can do with GAMS and how GAMS does the optimisation
“A woman at a point A on the shore of a circular lake with radius 2 mi wants to arrive at the point C diametrically opposite A on the other side of the lake in the shortest possible time (see the figure). She can walk at the rate of 4 mi/h and row a boat at 2 mi/h. For what value of the angle θ shown in the figure will she minimize her travel time?“
(Steiner) In the plane of a triangle, find a point such that the sum of its distances to the vertices of the triangle is minimal.
The travelling salesman problem (TSP) asks the following question: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city and returns to the origin city?"
Each city should be met only once
Every city should be visited