Route Optimization API

Route Optimization API for Efficient Routing and Scheduling

Get optimized routes, dynamic schedules and highly accurate ETAs. Swiftly order and reorder complex task sequences.

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Key Features

Incorporate 50+ Hard and
Soft Constraints

Implement over 50 hard and soft constraints for enhanced route and schedule flexibility. Balance time and cost considerations by setting preferences for specific waiting times, task lateness limits and vehicle work hours.

Leverage Custom Objective
Functions

Go beyond travel cost minimization using the custom objectives. Minimize the number of vehicles used or the total time taken to complete tasks. Ensure equal task distribution or keep travel costs within a close range across routes.

Optimize Routes for Various
Vehicle Profiles

A route for a gasoline delivery truck won't work for a waste collection truck — and we get that. With our API, efficiently plan routes for a variety of vehicles, including cars and commercial vehicles.

Design Task Sequences With
Complex Constraints

Arrange task sequences, both direct and indirect, as per your complex business constraints. Define job-shipment connections to ensure sequences follow your preferences and are executed as specified.

Integrate Real-Time and
Historical Traffic

Get routes that adapt to both current road situations and past traffic trends. Give your fleet reliable ETAs tailored to the hour and day of the week.

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By substantially reducing the number of developer hours spent on scheduling, NextBillion.ai’s MVRP and large Distance Matrix API have helped us improve our operational efficiency and increase our cost savings significantly!

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Carson Stevens,
Data Engineer

I admire NextBillion.ai's fast response and friendly manners whenever we need professional support in geospatial data processing. They have delivered a valuable service and support to our company that we appreciate.

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Yantisa Akhadi,
Strategy and Partnership Manager

NextBillion.ai solves the problem of providing a high-performance mapping platform at scale. We generate efficient delivery schedules in real time for hundreds of vehicles, so distance calculations need to be fast and reliable. NextBillion.ai’s Distance Matrix service meets and exceeds this demand.

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James Nebeker,
Machine Learning Engineer

How To Use
Route Optimization API

What Makes Us Unique

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Solve Unique
Use Cases

Utilize over 50 parameters and complementary APIs to fit any workflow, no matter how complex.

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Flexible
Pricing

Choose the option suited for your business needs — whether it's asset-based or usage-based.

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Designed for
Scalability

Manage nationwide logistical operations for thousands of orders and vehicles.

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Exceptional
Support

Receive assistance from our solution engineers throughout your evaluation and integration phase.

Seamless Integrations With
Top Enterprise Clouds, ERPs and CRMs

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FAQ

What is Route Optimization?

Route optimization refers to the process of determining optimized routes for a fleet of vehicles between multiple locations. This process is used in logistics, last-mile delivery, transportation trucking etc., to optimize vehicle routing problem efficiently. Route optimization helps improve efficiency, reduce operational costs and efficient resource utilization.

Route Optimization API helps businesses optimize their delivery routes to maximize efficiency, save time, and reduce costs. It is designed to solve both Single and/or Multi-Vehicle Routing Problem (VRP), which is a classic optimization problem. It involves finding the optimal routes for a fleet of vehicles to visit a set of locations while satisfying various constraints such as time windows, capacity, and vehicle availability.

The Multi-Depot Vehicle Routing Problem (MDVRP) is a route optimization problem that involves determining the most efficient route to deliver goods or services from multiple depots to a group of clients.

The MDVRP aims to reduce overall travel distance while considering vehicle capacity, depot location, and route length constraints. MDVRP has many applications in the logistics and transportation industries, where effective fleet management is critical to the company's success.

Route Optimization API has two main components, i.e., the input data and the optimization engine.

  • Input data: It consists of all the information about the jobs, which are stops/places to visit, vehicles and shipments, which are pickup and delivery tasks.
  • Optimization Engine The optimization engine considers the input data to generate optimized routes for the vehicle fleet. The optimization engine can handle multiple constraints and variables, such as vehicle capacity, time windows and skills, and truck-specific routing parameters.

The POST method submits the input to the Optimization Engine, which returns a unique optimization job id. The GET method retrieves the optimized route result using the unique reference id.