Develop Optimization models using Python, GAMS and Mosel
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1. Use this code at checkout (remove spaces) for the best Deal: 11CB773060 F45E51214F
2. Course Overview:
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Master the art of modelling and solving real-world optimization problems using three of the most widely used optimization and modelling languages: GAMS, Pyomo, and Mosel. These tools are essential in fields such as economics, finance, logistics, energy, and transport, enabling professionals to make data-driven decisions and optimize complex systems efficiently.
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Gain hands-on experience with Pyomo, GAMS, and Mosel—each highly regarded in academia, industry, and research. Pyomo integrates seamlessly with Python, making it an accessible choice for those familiar with the language, while GAMS and Mosel offer powerful capabilities for large-scale optimization problems.
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Strengthen your expertise through practical examples, real-world case studies, and industry-relevant projects. Develop the confidence to apply these tools effectively in professional and academic settings, solving complex optimization challenges with ease. By the end of this course, you’ll have a strong foundation to tackle real optimization problems and enhance decision-making in various industries.
3. Connect with me!
I hold a PhD in Energy from Imperial College London. Throughout my career, I have extensively applied Data Science to energy. My LinkedIn and personal website are available on my Udemy profile. I invite you to connect with me there. You can also find me inside the course, where you can send a private message or simply write in the Forum. I try to reply within 24 hours.
4. Find hundreds of Specialized Online Courses!
I invite you to connect with me on my personal website. There, you can find all the online courses that I have created at very low prices and under my personal supervision. Here is the link: www [dot] energydatascience [dot] com.
5. Read about Real-World Applications of Energy Data Science:
I invite you to follow my blog, where I share how I applied Data Science to real-world energy projects. It is very enlightening. The link is www [dot] energydatascience [dot] substack [dot] com.
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IntroductionIntroduction : what is optimization. Download the attached material below.
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A complete tutorial (PDF) for download
Download an introductory tutorial on Optimization to get a taste of what it is.
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Download a complete tutorial on GAMS
A complete tutorial on GAMS. Available for download.
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Overview
Overview of this chapter.
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Initial implementation of an optimization model
Initial implementation steps. Download the attached material below.
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Implement and output
Implementation and output generation. Download the attached material below.
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Grouping decision variables and parameters
How variables are grouped, as well as parameters. Download the attached material below.
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Modelling the summation of decision variables
How to model the summation of variables. Download the attached material below.
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Repetitive application of constraints
How to model the repetitive application of constraints. Download the attached material below.
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Multiple statements on a single line
How to model multiple statements on a line. Download the attached material below.
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Creating comment sections
How to create comment sections. Download the attached material below.
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Applying code conditionally
How to apply code conditionally. Download the attached material below.
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Implicit and explicit variable declarations
How to model implicit and explicit variable declarations. Download the attached material below.
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MILP models
Mixed Integer Linear Programs. Download the attached material below.
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Writing output data
How to write output data. Download the attached material below.
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Input initializations from excel
How to conduct input initialization from Excel. Download the attached material below.
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Procedural coding
How to implement procedural coding. Download the attached material below.
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Functional coding
How to implement functional coding. Download the attached material below.
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Insights into the structure of a problem
How to gain insights into the structure of a problem. Download the attached material below.
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Multidimensional variables
How to implement multi-dimensional variables. Download the attached material below.
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Real World example: Power Substation
A real world consultancy case. The code is downloadable below. Also, below is an academic paper with optimization, so you see just for demonstration of the academic use of optimization.
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Solve in Pyomo
Modelling and solving in Python using Pyomo. The code is downloadable below. Also, below is an academic paper with optimization, so you see just for demonstration of the academic use of optimization.
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Solve in GAMS
Modelling and solving in GAMS. The code is downloadable below.
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Solve in Mosel
Modelling and solving in Mosel. The code is downloadable below.
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Overview of this chapter
Description of this chapter
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Resources
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Optimality Infeasibility Unboundedness
In optimization, unboundedness occurs when the objective function can grow indefinitely without violating any constraints, while infeasibility arises when no solution satisfies all the given constraints simultaneously. Optimality is when the optimal solution is found.
The code is downloadable below. Also, a paper is available below for demonstration.
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Activity, duality, slackness
In optimization models, activity refers to whether a variable is actively contributing to the solution, duality involves the relationship between the primal and dual problems capturing shadow prices, and slackness measures the gap between resource usage and constraints, governed by the complementary slackness condition.
Belo you can download the code.
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Activity, Duality, Slackness - part 2
Second part , with more details.
