Yu Wang

Data Scientist

Ford Motor Company•  June 2023 - August 2023

Conducted an in-depth study of Ford's single echelon reorder-point inventory policy in Dubai, identifying key challenges in their inventory system. Developed and integrated a simulated annealing algorithm in Python with an existing Monte Carlo Simulator via API calls. Rigorously tested the algorithm on the Traveling Salesman Problem with over ten thousand cities, achieving optimal solutions through parameter tuning for efficiency. Applied the algorithm to optimize safety stock in Dubai's inventory system, resulting in an 11% reduction in budget for 200,000 vehicle parts. Designed unit tests for the simulated annealing functions, contributing to the team's development and enhancing IPST's operational capabilities. Created a FastAPI endpoint to facilitate interaction with the optimization process. Automated the Dubai inventory system optimization using Google Cloud Platform, employing BigQuery for data and plot storage.