Python for Optimization | Data Structures, Loops & PuLP Modeling (Workforce & Blending Examples) скачать в хорошем качестве

Python for Optimization | Data Structures, Loops & PuLP Modeling (Workforce & Blending Examples)

This lecture provides a complete introduction to Python fundamentals tailored specifically for optimization modeling. Starting with basic syntax—print statements, operators, and numeric/string types—the lesson introduces crucial Python data structures including Lists, Tuples, and Dictionaries. After covering If/Else logic and For/While loops, the tutorial transitions into practical Linear Programming (LP) model building using the PuLP library. Real-world examples such as Multi-Period Workforce Scheduling and the Blending Problem demonstrate how mathematical optimization models are translated into executable Python code. 📌 What You Will Learn ✔ Python basic syntax: printing, operators, Strings, Integers, Floats ✔ Key Python data structures: • Lists (mutable) • Tuples (immutable) • Dictionaries (key-value pairs) ✔ Conditional logic (If/Else) ✔ Loop structures (For Loop, While Loop) ✔ How to install and import PuLP ✔ How to build optimization models in Python ✔ Translating mathematical functions into PuLP syntax ✔ Defining decision variables and constraints ✔ Solving real optimization problems: • Workforce Scheduling Problem • Blending Problem 📌 Key Takeaways Python provides simple and powerful data structures ideal for algorithmic optimization. Lists, Tuples, and Dictionaries each serve different modeling purposes in LP coding. Loops and conditionals enable logical model construction and parameter handling. The PuLP library converts mathematical optimization models into solvable Python code. Workforce scheduling and blending demonstrate practical LP model building in operations research. Python + PuLP is a powerful combination for logistical, supply chain, and industrial engineering problems. Code + Related files used in the playlist of Python PuLP https://github.com/hakeemrehman/Pytho... “How can I learn Python basics for linear programming?” “How do I solve workforce scheduling problems in Python with PuLP?” “Which Python data structures are best for optimization models?” “What is PuLP and how do you use it for linear programming?” Learn Python basics—Lists, Tuples, Dictionaries, loops—and apply them to optimization modeling with PuLP, including workforce scheduling and blending examples. #PythonProgramming #PuLP #OptimizationModeling #DataStructures #LinearProgramming #OperationsResearch Thanks for watching! 🚀 Next topic: Should I cover Multi-Objective Optimization, Transportation Models, or Python Functions & Classes? Tell me in the comments! This tutorial teaches Python fundamentals—including data structures and loops—and shows how to use PuLP to build and solve optimization models such as workforce scheduling and blending problems.