Optimization with Julia: Mastering Operations Research

Focused View

Rafael Silva Pinto

5:11:35

177 View

1 - Introduction

1 - What is optimization and why use Julia.mp4

02:35

2 - Objective function variables parameters and constraints.mp4

04:21

3 - How to solve optimization problems.mp4

02:13

4 - Examples of what you are gonna learn.mp4

01:33

2 - Starting with Julia

5 - Installing Julia.mp4

01:42

6 - Installing VSCode.mp4

04:02

7 - Our first code.mp4

04:24

8 - If statement.mp4

02:45

9 - Functions.mp4

06:55

10 - Loops.mp4

06:28

11 - Lists arrays and dicts.mp4

06:18

12 - Packages.mp4

03:13

13 - Reading Excel Files.mp4

08:50

13 - dataNameAges.xlsx

13 - readdata.zip

14 - Learning more about Julia.html

3 - Linear Programming LP

15 - Introduction Linear and Nonlinear problems.mp4

05:20

16 - Modeling a linear problem.mp4

06:26

17 - Solving the first linear problem.mp4

13:40

18 - Using CBC.mp4

05:41

18 - lpfirst-cbc.zip

19 - List of solvers.mp4

04:35

20 - Installing and using Gurobi.mp4

12:24

21 - Installing and using CPLEX.mp4

05:56

22 - Example LP 1 Meal Planning Modeling.mp4

07:50

23 - Example LP 1 Meal Planning Solving.mp4

08:27

23 - lp-example1.zip

24 - Example LP 1 Working with indexes.mp4

13:20

24 - lp-example1-indexes.zip

25 - Example LP 2 Financial Investment Modeling.mp4

05:54

26 - Example LP 2 Financial Investment Solving.mp4

12:44

26 - lp-example2.zip

27 - 0-Mathematical-Programming.pdf

27 - 1-LP-concepts.pdf

27 - 2-Duality-Theory.pdf

27 - LP Concepts.html

4 - MixedInteger Linear Programming MILP

28 - Integer and Binary Variables.mp4

06:26

29 - Defining Integer Variables in Julia.mp4

07:16

30 - MILP Solvers.mp4

04:07

31 - Example MILP JobShop Modeling.mp4

10:43

31 - JobShopSchedulling-Article.pdf

31 - JobShopSchedulling-Book.pdf

32 - Example MILP JobShop Solving.mp4

25:48

32 - milp-example2.zip

33 - MILP Concepts.html

33 - MILP-concepts.pdf

5 - Working with Double Summation and Multiple Constraints

34 - Introduction and formulations.mp4

02:54

35 - Multiple Indexes in Julia.mp4

05:32

36 - Double Summations in Julia.mp4

03:23

37 - Multiple Constraints in Julia.mp4

02:57

38 - Multiple Constraints with Summation.mp4

04:49

38 - double.zip

39 - Naming Constraints.mp4

03:24

6 - Using external inputs to solve a routing problem VRP

40 - Routing Problem Formulation.mp4

10:02

41 - Data Input structure.mp4

01:50

41 - input.xlsx

42 - Reading Excel.mp4

06:37

42 - input.xlsx

43 - Reading other sources.html

44 - Creating sets and filtering DataFrames.mp4

14:08

45 - Solving the routing problem.mp4

19:40

45 - input.xlsx

45 - routing.zip

46 - Exporting the solution.mp4

03:57

46 - input.xlsx

46 - output.csv

46 - routing.zip

7 - Parameters and Progress of the Solver

47 - Progress of the Solver.mp4

06:52

47 - milp-example1-reference.zip

48 - CBC-manual-and-parameters.pdf

48 - Checking the parameters.mp4

04:19

48 - glpk.pdf

49 - Gap Tolerance.mp4

07:00

49 - milp-example1.zip

50 - Time Limit.mp4

02:15

50 - milp-example1.zip

8 - Nonlinear Programming NLP

51 - Release date March 26th 2023.html

9 - MixedInteger Nonlinear Programming MINLP

52 - Release date Abril 2nd 2023.html

10 - Expanding Your Knowledge and Exploring Opportunities

53 - Enhancing Your Knowledge of Mathematical Formulation and Optimization.html

54 - Course recommendation to expand your skills Optimization with Python.html

55 - Congratulations.html

Description

Solve optimization problems with Gurobi, CPLEX, GLPK, IPOPT, JuMP... using linear programming, nonlinear, MILP...

What You'll Learn?

Solve optimization problems using linear programming, mixed-integer linear programming, nonlinear programming, mixed-integer nonlinear programming
Main solvers, including Gurobi, CPLEX, GLPK, CBC, IPOPT, Couenne, SCIP, Bonmin
How to use JuMP to solve optimization problems with Julia
How to solve problems with summations and multiple constraints
How to install and use Julia
How to install and activate each solver

Who is this for?

Undergrad, graduation, master program, and doctorate students

Companies that wish to solve complex problems

People interested in solving complex problems

More details

Description
The increasing complexity of the modern business environment has made operational and long-term planning for companies more challenging than ever. To address this, optimization algorithms are employed to find optimal solutions, and professionals skilled in this field are highly valued in today's market.

As an experienced data science team leader and holder of a PhD degree, I am well-equipped to teach you everything you need to solve optimization problems in both practical and academic settings.

In this course, you will learn how to problems problems using Mathematical Optimization, covering:
Linear Programming (LP)
Mixed-Integer Linear Programming (MILP)
Nonlinear Programming (NLP)
Mixed-Integer Nonlinear Programming (MINLP)
Implementing summations and multiple constraints
Working with solver parameters
The following solvers: CPLEX, Gurobi, GLPK, CBC, IPOPT, Couenne, Bonmin, SCIP

This course is designed to teach you through practical examples, making it easier for you to learn and apply the concepts.
If you are new to Julia or programming in general, don't worry! I will guide you through everything you need to get started with optimization, from installing Julia and learning its basics to tackling complex optimization problems.
By completing this course, you'll not only enhance your skills but also earn a valuable certification from Udemy.

Operations Research | Operational Research | Operation Research | Mathematical Optimization

I look forward to seeing you in the classes and helping you advance your career in operations research!
Who this course is for:
Undergrad, graduation, master program, and doctorate students
Companies that wish to solve complex problems
People interested in solving complex problems

User Reviews

Rating

average 0

Total votes0

Focused display

Programming Fundamentals

Rafael Silva Pinto

Instructor's Courses

Hello! I'm passionate about solving complex problems and have dedicated my career to exploring the realms of optimization models, artificial intelligence, and data analysis. With a background in Electrical Engineering and a PhD in optimization models, I have developed a deep understanding of these fields. Additionally, I have honed my skills in data science and big data, and hold an MBA in Business Management.In my professional journey, I have had the opportunity to serve as a Data Science Manager at a leading Brazilian company, where I successfully tackled a variety of challenging projects. Today, I work as a consultant, providing expert guidance to businesses in addressing a wide range of problems.Through my Udemy courses, I'm excited to share my expertise and help others acquire the skills needed to excel in optimization, artificial intelligence, and data analysis. Join me on this learning journey, and let's unlock your potential together!

Udemy

View courses Udemy

Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.