This repository is a part of the official submission of IIT Bhubaneswar for the Grow Simplee Problem Statement, which earned them a Silver Medal🥈 among 23 competing IITs.
Given n items to deliver and a fleet of m riders, (n > m), and some k dynamically added pickup points. Optimize for n items and at most m tours,
also considering the cases where k >= 0 and points are added or deleted from the original route.
The Objectives are:
-
A tool that accurately estimates the
length,breadth,heightandvolumetric weightof an item with a small margin of error. The product developed should be easy to use, reproducible and reusable. Bonus points will be awarded, if erroneous objects can be flagged on a conveyor. -
An effective route planning system to cluster items into different tours that maximize the number of items delivered in each route of the tour,
maximizing the on-time delivery percentage and minimizing overall distance travelledon all routes combined with minimum tours/riders involved in fulfilment. While route planning, maximizing the output of riders by smart bag creation/clustering to get the best out of riders and routes. This Route planning system should also have the ability to add pickup points dynamically for multi-pickup cases by selecting the correct rider/tour, reroute their routes to cater pickups along with their ongoing tour and consider the rider bag capacity as well. -
A basic platform (
web/app) to fit all these objectives together where points can be added or removed dynamically. The app is expected to support navigation on a map by prompting the best route between any two points on the tour for riders. The app needs to be integrated with Challenge-1 for the rider-bag problem.
👉 Click here to get the detailed problem statement.
 Order of Deliveries for Rider |
 Route for navigation using Map |
 Rider Simulation (4 hours) For Delivery |