Udemy – Complete guide to Modern Mathematical Optimization in GAMS 2020-10 – Full Version

Description

Complete guide to Modern Mathematical Optimization in GAMS is a course on Mathematical Optimization with Gomez Software (GAMS) published by Udemy Academy. To participate in this training course you do not need any basic knowledge in the field of programming and mathematical optimization, and all people, regardless of their level of knowledge, can participate in this course . In this course, you will not work with specific, specialized problems and will only deal with a set of general problems and challenges. The target audience for this course is not limited to any specific industry or discipline and anyone can benefit from this course in some way but engineers, programmers, applied math students and operations researchers can get the most out of this course.

What you’ll learn in A Complete Guide to Modern Mathematical Optimization in GAMS

  • Initial installation of Gomez (GAMS) on various operating systems
  • Familiarity with the concept and principles of the mathematical theory of optimization
  • Objective function
  • Constraint
  • Meaning and causes of various errors and errors in the optimization process and ways to fix them
  • Read basic information from an Excel file
  • Save final information and data in an Excel file
  • Multi-objective optimization in Gomez software
  • Conditional Programming and Conditional Expressions in Gomez
  • Loops in Gomz
  • Optimization of mathematical models

Course specifications

Editor: Udemy
Instructors: Optimization team
French language
Level: Introductory to Advanced
Number of lessons: 23
Duration: 2 hours and 56 minutes

Course topics

Complete Guide to Modern Mathematical Optimization in GAMS Content

Complete Guide to Modern Mathematical Optimization in GAMS

You can start now without any prior knowledge of GAMS

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Complete Guide to Modern Mathematical Optimization in GAMS

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english subtitle

Quality: 720p

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Download part 2 – 579 MB

File password(s): ngaur.com

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