Storefront by Fleetbase is an open source hyperlocal shopping or services app. Enables users to quickly launch their own shop or service booking app or setup a multi-vendor marketplace.
AWS Last Mile Route Sequence Optimization
AWS Last Mile Delivery Hyperlocal
Optimize E-Commerce Last-Mile Delivery with Python
Optimal routing and delivery solutions using Google Maps and Python.
Geometric Deep Learning Models for Vehicle Routing Problem
VRP-Models-and-Algorithms Models and algorithms for solving Vehicle Routing Problems using optimization and heuristics.
lmr-analyzer: A powerful toolkit to analyze the interaction between last mile operations and the street network design.
Last-Mile Delivery Made Practical: An Efficient Route Planning Framework with Theoretical Guarantees
Sử dụng Giải thuật Di truyền cho vấn đề Tối ưu hành trình vận chuyển đơn hàng
Optimize specified transports (pickups and deliveries) and displays the optimal routes for each of your vehicles.
End-to-end analytics suite for Blinkit, Swiggy, and JioMart — 100k+ orders analyzed to forecast demand, optimize SLAs, and reduce churn (+37% growth impact)
Parcel Delivery Optimization using Google OR-Tools to generate efficient, real-world delivery routes that account for time slots given by the customer. Includes admin dashboard, driver app, and live tracking.
Amazon HackOn submission for team CodingAlphas.
Network Observer and Explorer (NOX) a multi purpose python city simulation software built to simulate last-mile delivery models with different vehicles (Truck, human couriers, autonomus delivery vehicles, drones, ...etc.)
Display a map, click on a location anywhere on the map and caluclate areas around this location that are reachable in a specific distance or time.
A routing script to obtain optimal routes by considering both load on the truck and distance between places
Bibliometric network analysis and topic modeling
Leveraged historical geospatial data to forecast weather patterns, optimize delivery times and methods to improve efficiency and reduce costs.
An application of causal inference methods to optimizing the location of delivery drivers.
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