Mathematical Optimization in Python :Using PuLP, Python-MIP

سرفصل های دوره

A Practical Approach to Solving Optimization Problems: Learn PuLP and Python-MIP Syntax and Features

1. Introduction

1. Introduction

2. What is Mathematical Optimization

3. PuLP and Python-MIP

2. Development Environment Preparation

1. Installing Python

2. Installing Visual Studio Code

3. Installing VScode Extension

4. How to create virtual env

3. PuLP Learning

1. Basic Syntax of PuLP

2. System of Linear Equations

3. Simplifying previous code

4. Production Planning Optimization

5. Production Planning Optimization

6. Production Planning Optimization with Integer Constraints

7. Quick Guide to List Comprehensions Reference

8. Introduction to the Knapsack Problem

9. Knapsack Optimization Using lpSum

10. Knapsack Optimization Using lpDot

11. Quick Guide to Dictionary Reference

12. Knapsack Problem with Larger Datasets

13. Overview of the Traveling Salesman Problem TSP

14. Solving Traveling Salesman Problem

15. Solving Traveling Salesman Problem

16. Solving Traveling Salesman Problem

4. Python-MIP Learning

1. PuLP vs. Python-MIP

2. Syntax Differences Between PuLP and Python-MIP

3. System of Linear Equations

4. Production Planning Optimization

5. Production Planning Optimization

6. Production Planning Optimization with Integer Constraints

7. Knapsack Optimization

8. Knapsack Problem with Larger Datasets

9. Traveling Salesman Problem

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تولید کننده: Udemy