In my GitHub repository titled "Optimization-programming," I delve into the intricate world of constrained optimization problems. This project encompasses a broad range of optimization techniques, including linear, network, dynamic, integer, and nonlinear programming. Beyond these, it also features decision trees, queueing theory, and Markov decision processes.
This repository serves as a testament to my ability to handle complex optimization challenges. It showcases my proficiency in employing various algorithms and strategies to find efficient solutions to real-world problems. One of the notable aspects of this project is the use of Markov Chain algorithms for lifecycle scoring and attribution, a technique I applied in a project for Zillow. Additionally, I developed an inventory forecasting algorithm for PACCAR's sales team, optimizing their stock management process.
Furthermore, the project highlights my skills in architecting Data Warehouses for querying MongoDB and SQL server using AWS, demonstrating my ability to integrate multiple technologies for efficient data management and analysis. Another significant achievement is the programming of Airport and Airline Choice Models using advanced algorithms like Random Forest, Nested Logit, and Decision Tree, providing actionable insights for South Korean officials.
This collection of work not only represents my technical capabilities in optimization programming but also reflects my dedication to applying these skills in practical and impactful ways. Whether it's enhancing business strategies, streamlining operations, or contributing to large-scale projects, this repository is a window into the breadth and depth of my expertise in the field of data analytics and optimization.