Vehicle route optimization & planning software powered by machine learning

How does a warehouse manager plan the most optimal routes for delivering 5,000 shipments in a day with 500 bike riders to various parts of the city? The task of assigning specific packets and most optimal route suggestions to each rider is a very complex task, especially as the volume of shipments or geographic region expands. Hence surfaced the need to embrace vehicle route planning software.

Imagine the same daily life challenge in the pure mathematical or statistical notations. There will be ‘n’ number of workforce moving through ‘m’ nodal points through ‘x’ routes to meet ‘y’ customers. Feeling lost? Yes, this happens in the logistics industry too. This problem is known as Traveling Salesman Problem (TSP), a nightmare for organizations with a huge workforce. Mathematicians and computer scientists have been working on algorithms to solve the TSP or vehicle routing problem for over half a century now.

FarEye’s team of research analysts and the data scientists have cracked the code and built industry’s most efficient auto-routing product. A mix of Artificial Intelligence and Machine-learning algorithms, FarEye’s vehicle route planner helps in optimizing the routes, at any point of the day - off-peak and peak traffic conditions, keeping anything and everything in consideration.

The moment a shipment at the warehouse is ready for delivery, it needs to be assigned to a rider who covers the specific pin code area. The rider is expected to deliver parcels pertaining to his marked area following an optimum route.

However, with perpetual demand for shorter turnaround time and higher shipment volumes, it is imperative that logistics companies utilize their capacity in a more effective and efficient manner. FarEye’s vehicle routing software can help them achieve this by providing dynamic fleet management.

This means that the information such as vehicle type and capacity utilization, number of shipments that have to be delivered in a specific area, the available number of riders etc. is taken into considerations while planning the optimal route plans, simultaneously. A vehicle route tracker or vehicle route planning software takes into consideration the preferred time-slots and allows personalization of deliveries while routing the rider to the customer location.

The interactive route map embedded in the vehicle routing software enables the manager as well as the customer to track their shipment deliveries on a real-time basis with almost a zero-error estimated time of arrival. In case of any delivery failures, the manager gets SMS and real-time notifications/alerts along with the reason for the failed attempts

By having the right vehicle route optimization software in place, the manager can also create different geofences that act as a guide for auto-routing their fleet. For example, geofencing with regards to vehicle route planning refers to the areas that should not be combined when creating routes. However, these are not static fences. The manager has the right to combine multiple geofences dynamically to optimize volume and load during a particular time period.

AI is one of those key disruptive technologies that's introducing high levels of efficiencies across supply chain and logistics operations. So, why is AI route planning becoming increasingly important in executing deliveries? One of AI's core sub-set is machine learning (ML), and this is what's changing the game for delivery stakeholders. By using ML, an advanced vehicle route planner analyzes enormous volumes of historical data and generates the most efficient route to travel from point A to B to C. It can even warn delivery executives of a route that might be prone to risks like thefts, pilferage, accidents, sudden route closures and more. So, AI route optimization or machine learning based routing empowers delivery stakeholders with critical intelligence that helps them become highly proactive.