Modern Mathematical Optimization in GAMS
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3,028 students enrolled

# Modern Mathematical Optimization in GAMS

From Zero to Hero
4.1 (10 ratings)
3,028 students enrolled
Last updated 1/2019
English
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This course includes
• 3 hours on-demand video
• Access on mobile and TV
• Certificate of Completion
Training 5 or more people?

What you'll learn
• GAMS installation

• ### Multi-Objective Optimization

• Conditional statements
• Loop statements
Requirements
• You can start now without any prior knowledge in GAMS
Description

The developed course is suitable for you even if you have no background in programming. The course is devoted to general optimisation problems in GAMS.

In this course you will learn how to use GAMS for solving optimisation problems.

• First of all you will learn how to install GAMS on your machine.

• What is optimisation ? 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 optimisation in GAMS

• How to code conditional statements in GAMS

• How to code Loop statements in GAMS

Who this course is for:
• Engineering
• Applied maths
• Operation research
Course content
Expand all 21 lectures 02:48:10
+ Introduction
12 lectures 01:48:11

Preview 06:15

This gives you a big picture of what you can do with GAMS and how GAMS does the optimisation

Preview 04:56
Sets in GAMS
04:55
• What is Table?

• How to deal with Tables in GAMS ?

• Syntax ?

Parameters in GAMS
02:41
• What is Scalar?

• How to deal with Scalars in GAMS ?

• Syntax ?

Scalars in GAMS
01:50
• What is Table?

• How to deal with Tables in GAMS ?

• Syntax ?

Table in GAMS
01:26

How to define equations in GAMS?

What is the syntax ?

Equations in GAMS
04:36
• What kind of optimisation models can be solved in GAMS ?

• What is my model type ?

Model definition in GAMS
14:32

How to select the appropriate GAMS solver for my model ?

Preview 03:10

The conditional statement is explained in this lecture

Conditional statements in GAMS
32:52

The loop statement is explained in this lecture

LOOP in GAMS
16:20

Multi-objective optimisation is explained and coded in GAMS

Multiobjective Optimisation in GAMS
14:38
+ Solved Problems in GAMS
9 lectures 59:59

Linear programming is explained and some examples are solved

Linear Programming
09:30

Mixed Integer Programming is explained and coded in this lecture

Mixed Integer Linear Programming
07:51

In a given circle find a rectangle of maximal area.

In a given circle find a rectangle of maximal area
02:49

In a given sphere find a cylinder of maximal volume

Cylinder in a Sphere
02:40

“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?“

Min Travel time
03:36

(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.

Preview 03:15

A and B are two given points on the same side of a line ℓ. Find a point D on ℓ such that the sum of the distances form A to D and from D to B is a minimum.

Herons Problem
03:02

In this lecture you will learn how to code in GAMS for finding the shortest paths between nodes in a graph, which may represent, for example, road networks.

Shortest path via LP in GAMS
19:21

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

Traveling Sales Person (TSP)
07:55