Analysis
Optimizing Last-Mile Delivery for a San Francisco Grocery Startup
Overview
What this challenge is about.
Your task is to formulate a minimum-cost flow problem for daily delivery routes. Use the provided order data (locations, time windows, volumes) and vehicle specs (capacity, speed). Solve using a network flow algorithm (e.g., successive shortest path) and implement in Python or Excel. Success means reducing total distance by at least 15% compared to the current manual routes, with all deliveries within their time windows.
The Brief
What you'll do, and what you'll demonstrate.
Minimize total travel distance for a fleet of delivery vehicles subject to time windows and capacity constraints.
Earning criteria — what you'll demonstrate
- Formulate a real-world logistics problem as a network flow model
- Apply the successive shortest path algorithm to find optimal flows
- Interpret dual variables (shadow prices) for capacity constraints
- Validate model outputs against operational constraints
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
Careers
Roles this prepares you for.
Real titles. Real skill bridges. Pick the one closest to your trajectory.
Career mappings coming soon.