delivery-optimization

A dynamic Python-based routing and package management system for optimizing delivery schedules and operations. Designed for WGUPS, it showcases efficient use of algorithms and data structures for real-world logistics solutions.

Gen AI–powered sprint risk analysis prototype for Technical Program Management. Simulates automated detection of delivery blockers and cross-team dependencies, demonstrating potential to reduce manual status review time by ~30–40% and improve early risk visibility in engineering programs

An Operations Research portfolio project solving the Capacitated Vehicle Routing Problem (CVRP) for last-mile logistics using PyVRP and Python.

🚚 A genetic model written in Python for minimizing the delay time of delivery routes（使用Python编写的用于最小化物流配送时间的遗传算法）

Multi-objective Vehicle Routing Problem solver using NSGA-II — 4-objective optimization (distance, lateness, idle time, fairness) with Kathmandu traffic modeling, demand forecasting, and FastAPI REST API

End-to-end delivery analytics: SQL ops analysis, 37-feature ML model (94.77% accuracy), peak-hour insights, weather/traffic impact, production-ready predictions.

AI agent for optimizing last-mile delivery slots to reduce redelivery, built with Agentic Star.

A case study of kernel memory growth associated with Windows Delivery Optimization, with diagnostic evidence, remediation steps, and known limitations.

AI-powered e-commerce delivery intelligence platform that diagnoses delivery delays, predicts SLA breach risks, analyzes warehouse and route performance, and recommends data-driven operational improvements.