Dynamic vehicle routing and task allocation
Route2 is an innovative engine based on artificial intelligence dedicated to creating delivery schedules and planning routes for vehicles based on orders. Route2 provides dynamic optimization of transport routes, capable of solving complex vehicle routing problems in minutes. Optimal routes determined by the Route2 module are, above all, minimized total transport costs while maintaining a certain level of efficiency, but also saving time needed for planning and ensuring on-time delivery.

Route2 provides measurable benefits
Automate and accelerate the route planning process in your company. Minimize total transportation costs while maintaining delivery timeliness.

Up to 23%
savings in operating costs (OpEx)

Up to 20%
reduction in mileage and service time without delivery delays

Up to 25%
increase in vehicle space utilization

Up to 10%
reduction in the required fleet size

Up to 100%
automation of route planning and fleet management processes

Up to 30%
optimization of capital expenditures (CapEx), including effective fleet electrification, ESG standards, and new operational strategies
Route2 Functionalities
Route2 is the future of dynamic vehicle routing. Leveraging advanced AI, Route2 transforms fleet efficiency with real-time adaptability, consistently delivering optimal routing solutions to mitigate delays and maximize fleet potential. It dynamically manages transport systems, adjusting routes based on parameters like new and canceled orders or changing traffic conditions. Key functionalities of the Route2 module include:
Dynamic route planning considering unpredictability in transportation
Static assignment: Orders are allocated once for a set time period (e.g., 15 minutes, one hour, one day), without updates. This limits fleet efficiency as it doesn’t adapt to new orders or cancellations. Static assignments are ideal for fleet operators who receive transportation orders with a time lag (e.g., once a day) with the need for delivery in the next time interval (the next day). Dynamic assignment: Routes and assignments can be re-optimized based on new orders and road conditions. This solution is beneficial for real-time order processing, it can increase fleet efficiency by up to 23% (23% lower operational cost for a given pool of orders).

Optimization for one or many distribution centers and transshipment hubs
A multimodal system enables significant operational savings, especially for companies handling orders over long distances with potential distribution centers along the way (first mile → hub-to-hub travel → last mile). By considering transshipments in a single optimization, we can better adjust vehicle sizes to transportation needs and increase vehicle utilization efficiency. Transshipment points and distribution centers can be defined by the operator using dedicated tools for the Route2 module. By optimizing services in the multimodal system, our solution ensures coordination of transportation tasks, taking into account factors such as time required for transshipment and delays.

Handling Parameters such as Time Windows, Priorities, and Employee Schedules
Time windows refer to a time interval during which a transportation order can be picked up or delivered, beyond which the operator will be penalized or may not have the possibility to fulfill the order. Meanwhile, priorities determine which order brings greater profit or has a higher priority for servicing in a specific time window. Order priorities are combined with time windows to enable management of vehicles and orders that may have conflicting service times or to enforce the algorithm to choose the most cost-effective solution. In the Route2 module, the fleet operator can define necessary vehicle and driver breaks (as well as their locations). Based on the defined break schedules, the Route2 module will plan the order of service for orders to ensure the break schedules are fulfilled.

Predictive routing for fleet rebalancing, including charging
Route2 includes a built-in module for learning transport patterns and their effectiveness. The algorithm’s self-learning capabilities enable the optimization of fleet utilization for better future balancing, such as the algorithm knowing that peak deliveries from point A are expected at 11am, so it positions vehicles at point A before orders appear. Similarly, vehicle loading and servicing are planned outside of peak fleet utilization hours. Battery charging optimization can occur in reactive mode (charging because the battery has low charge) and proactive mode (charging because the vehicle is close to the charging station and doesn’t have priority orders to fulfill in the near future).

Optimization of Multiple Fleet Utilization Parameters
Route2 can consider various parameters such as: Minimization of operating costs while handling all complex orders. Maximization of profit generated with or without the need to handle all orders. Minimization of traveled distance or service time for a declared pool of orders. Combined criteria depending on the provided service, e.g., minimizing operating costs with the need for priority service in a specific area or group of orders and maximizing profit generation without the need to handle all orders for the remaining area. Parameters optimized: service time, traveled distance, fleet utilization (vehicle and driver availability time), number and size of vehicles handling orders, service cost.

Handling Long-Term Reservations and Dynamically Incoming Reservations
This feature allows for planning the utilization of vehicle fleets while considering orders that have been planned in advance, and the ability to change schedules to accommodate new orders while ensuring the fulfillment of orders planned in advance.

Editing automatically assigned routes in a web Browser
The Route2 module interface allows: Defining new transport orders. Viewing current orders, their statuses, and vehicle statuses. Initiating optimization queries and setting up automatic optimization calls (e.g., every 15 minutes, every hour, dynamically with each new order, etc.). Manually overriding routes and drivers assigned to vehicles (e.g., the algorithm automatically assigns orders and routes to a vehicle, but the dispatcher can manually change the assignment).


Do you want to streamline your transportation processes?
At Aleet, we start by understanding the operational model of your transport business to customize our software to meet your company’s needs.