Learning Optimization with Pyomo

Learning Optimization with Pyomo, available at $19.99, has an average rating of 4.25, with 40 lectures, based on 4 reviews, and has 32 subscribers.

You will learn about Students will be able to identify optimization problems, formulate mathematical models, and implement them using Pyomo Students will formulate and solve a wide range of optimization problems, including linear programming, mixed-integer linear programming, quadratic programming Students will analyze and interpret optimization outcomes, make informed decisions, and effectively communicate findings to stakeholders students will have a solid understanding of optimization theory, practical experience in using Pyomo for modeling, and the ability to solve optimization problem This course is ideal for individuals who are This course is designed for learners who have a basic understanding of Python programming and a foundation in mathematical concepts. It is suitable for students, professionals, and enthusiasts seeking to expand their knowledge and practical skills in optimization modeling and problem-solving. Whether you are a data scientist, an operations researcher, a supply chain analyst, or a decision-maker in any field that involves making optimal choices, this course will equip you with the necessary tools to formulate and solve complex optimization problems using Pyomo. By the end of the course, you will have a solid understanding of optimization theory, hands-on experience with Pyomo, and the ability to apply optimization techniques to real-world scenarios. It is particularly useful for This course is designed for learners who have a basic understanding of Python programming and a foundation in mathematical concepts. It is suitable for students, professionals, and enthusiasts seeking to expand their knowledge and practical skills in optimization modeling and problem-solving. Whether you are a data scientist, an operations researcher, a supply chain analyst, or a decision-maker in any field that involves making optimal choices, this course will equip you with the necessary tools to formulate and solve complex optimization problems using Pyomo. By the end of the course, you will have a solid understanding of optimization theory, hands-on experience with Pyomo, and the ability to apply optimization techniques to real-world scenarios.

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Summary

Title: Learning Optimization with Pyomo

Price: $19.99

Average Rating: 4.25

Number of Lectures: 40

Number of Published Lectures: 40

Number of Curriculum Items: 40

Number of Published Curriculum Objects: 40

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Students will be able to identify optimization problems, formulate mathematical models, and implement them using Pyomo
Students will formulate and solve a wide range of optimization problems, including linear programming, mixed-integer linear programming, quadratic programming
Students will analyze and interpret optimization outcomes, make informed decisions, and effectively communicate findings to stakeholders
students will have a solid understanding of optimization theory, practical experience in using Pyomo for modeling, and the ability to solve optimization problem

Who Should Attend

This course is designed for learners who have a basic understanding of Python programming and a foundation in mathematical concepts. It is suitable for students, professionals, and enthusiasts seeking to expand their knowledge and practical skills in optimization modeling and problem-solving. Whether you are a data scientist, an operations researcher, a supply chain analyst, or a decision-maker in any field that involves making optimal choices, this course will equip you with the necessary tools to formulate and solve complex optimization problems using Pyomo. By the end of the course, you will have a solid understanding of optimization theory, hands-on experience with Pyomo, and the ability to apply optimization techniques to real-world scenarios.

Target Audiences

This course is designed for learners who have a basic understanding of Python programming and a foundation in mathematical concepts. It is suitable for students, professionals, and enthusiasts seeking to expand their knowledge and practical skills in optimization modeling and problem-solving. Whether you are a data scientist, an operations researcher, a supply chain analyst, or a decision-maker in any field that involves making optimal choices, this course will equip you with the necessary tools to formulate and solve complex optimization problems using Pyomo. By the end of the course, you will have a solid understanding of optimization theory, hands-on experience with Pyomo, and the ability to apply optimization techniques to real-world scenarios.

This course is designed to provide a comprehensive understanding of mathematical modeling and problem-solving techniques using Pyomo, a powerful optimization modeling language in Python.

In this course, you will embark on a journey to explore the exciting world of optimization, where you will learn how to formulate and solve complex problems to make optimal decisions. Through a combination of theoretical explanations, practical examples, and hands-on exercises, you will gain a solid foundation in optimization principles and the skills needed to apply them in real-world scenarios.

Starting with an introduction to optimization fundamentals, you will learn about objective functions, decision variables, and constraints. You will discover linear and nonlinear optimization problem formulations and understand their applications in diverse domains. With Pyomo as your toolkit, you will dive into the syntax, structure, and capabilities of this powerful optimization modeling language.

The course will cover various optimization techniques, including linear programming, mixed-integer linear programming and nonlinear programming. You will explore different solution methods, algorithms, and approaches to handle various optimization challenges. Through practical coding exercises and projects, you will gain hands-on experience in implementing optimization models using Pyomo and solving them with different solvers.

Moreover, the course will delve into result analysis and interpretation, enabling you to evaluate solution quality, perform sensitivity analysis, and make data-driven decisions based on optimization outcomes. You will also learn how to visualize and present optimization results effectively.

By the end of this course, you will have the knowledge and skills to confidently tackle complex optimization problems using Pyomo. Whether you are an aspiring data scientist, an operations researcher, or a decision-maker in any field that requires optimal decision-making, this course will empower you to unlock the potential of optimization and make informed choices that drive efficiency and productivity.

Join me on this optimization journey and take a step towards mastering mathematical modeling and problem-solving for real-world optimization challenges with Pyomo

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: What is Optimization

Lecture 1: Introduction To Optimization

Lecture 2: Basics of Optimization

Chapter 3: Introduction to Programming Concepts of Python

Lecture 1: Basics of Python

Lecture 2: Control Structures in Python

Lecture 3: Lists in Python

Lecture 4: Dictionaries in Python

Lecture 5: Functions In Python

Chapter 4: Installation

Lecture 1: Installation of Python and Frameworks

Lecture 2: Installing Solvers

Chapter 5: Learning Programming in Pyomo

Lecture 1: What is Pyomo

Lecture 2: Introduction to Programming in Pyomo

Lecture 3: Frameworks in Pyomo and Linear Programming

Lecture 4: Mixed Integer Linear Programming

Lecture 5: Non Linear Programming

Lecture 6: Concrete Vs Abstract Modelling in Pyomo

Lecture 7: Knapsack Theory Example

Lecture 8: Knapsack Concrete example

Lecture 9: Knapsack Abstract Example

Lecture 10: Example: Warehouse Location Problem – Theory and Concrete Formulation

Lecture 11: Example: Warehouse Location Problem – Abstract

Chapter 6: Example Problems in Solving Business problems in different domains

Lecture 1: Airline Hub Location : Theory

Lecture 2: Airline Hub Location : Pyomo Implementation

Lecture 3: Animal Food Production : Theory

Lecture 4: Animal Food Production : Pyomo Implementation

Lecture 5: Assembly Line Balancing : Theory

Lecture 6: Assembly Line Balancing : Pyomo Implementation

Lecture 7: Cutting Sheet Metal : Theory

Lecture 8: Cutting Sheet Metal : Pyomo Implementation

Lecture 9: Planning an early retirement scheme : Theory

Lecture 10: Planning an early retirement scheme : Pyomo Implementation

Lecture 11: Gritting of Roads : Theory

Lecture 12: Gritting Roads : Pyomo Implementation

Lecture 13: Job Shop Scheduling : Theory

Lecture 14: Job Shop Scheduling : Pyomo Implementation

Lecture 15: Water Supply Management : Theory

Lecture 16: Water Supply Management : Pyomo Implementation

Lecture 17: Assignment of Batches to Machines : Theory

Lecture 18: Assignment of Batches to Machines : Pyomo Implementation

Chapter 7: Conclusion and Next Steps

Lecture 1: Conclusion and Next Steps

Instructors

Ayanangshu Das
Course Instructor

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3 stars: 1 votes
4 stars: 2 votes
5 stars: 1 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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