Route Optimization Flexible API Tutorials

In this example we will play around with basic constraints offered in NextBillion.ai’s Route Optimization Flexible API. The constraints covered here are time windows of jobs, vehicle shift timings, skills needed to complete the tasks and capacities involved to carry out pickup/delivery type tasks. We specifically demonstrate how the time windows are used to determine the job sequence & assignment and if the time windows are such that they could not be honored then the task would be left unassigned. We will also see how the starting and ending stops for the vehicle are configured when they are assigned to depots versus when they are not assigned to depots.

In this example, we learn about the hard constraint of maximum waiting time. NextBillion.ai’s Route Optimization Flexible API provides options to control how long the driver must wait after arriving at the task's location. It is worth noting that this is a hard constraint and applies to all the tasks given in the problem. This feature is helpful when users want to manage the wait times of their drivers or when achieving the lowest wait times is a crucial business goal (for example, consumer-facing services). Let's look at how to incorporate this functionality into an optimization request.

In this example, we cover an interesting feature of assigning user-defined travel costs of traveling from one point to another. NextBillion.ai’s Route Optimization Flexible API would then use these custom costs to arrange the job fulfillment in a way such that the overall costs are minimum.

Custom Objective is a valuable feature that empowers users to pursue unique objectives which are significantly different from the typical approach of minimizing travel costs. This feature allows users to tune the optimization algorithm to achieve following objectives:

NextBillion.ai’s Route Optimization Flexible API offers a powerful re-optimization feature which allows the users to re-optimize a set of existing or new tasks by readjusting some variables, if needed.

NextBillion.ai’s Route Optimization Flexible API offers a powerful re-optimization feature which allows the users to fulfill previously unassigned tasks by readjusting some variables. These variables can be the number of vehicles included in the optimization request, modifying the shift timings or capacities of the vehicles involved or changing the task time windows or any other strategy that would increase the chances of higher task assignments.

Relations are used to specify the association between different tasks that should be performed in a certain order. NextBillion.ai’s Route Optimization Flexible API offers three types of relations that the users can enforce:

In this example, we learn about the vehicle cost attributes. NextBillion.ai’s Route Optimization Flexible API currently provides two types of vehicle costs - fixed and per_hour costs. Fixed costs are the cost of using the vehicle irrespective of how long the vehicle remains in use. Driver fee, license fee, taxes etc can be thought of as fixed costs. If only the fixed cost of the vehicle is provided then it will be added to the travel_cost of the route.

The Soft Constraints feature enables users to complete more tasks by treating specific time-related limitations as flexible. NextBillion.ai’s Route Optimization Flexible API currently allows vehicle shift timings and task time windows to be made flexible up to a configurable degree. This functionality is useful in commercial scenarios where job completion ratio is the most crucial measure and time constraints are not strict. Let’s build an example to understand how these constraints work.

In this example we will learn about some useful vehicle constraints. NextBillion.ai’s Route Optimization Flexible API provides options to control the maximum number of tasks that a vehicle can serve and also the maximum travel cost that it can incur. These parameters can be used to limit the usage of vehicles and prevent them against unexpected high costs, potential breakdowns or just control the fuel consumptions.

NextBillion.ai’s Route Optimization Flexible API offers a simple but useful feature, called order grouping, that enhances the driver experience by conveniently planning a common stop for multiple tasks located closeby.

Depots are an important piece of any logistic operations and serve as a center for fulfilling customer orders.

Zone based allocations refers to the ability of NextBillion.ai’s Route Optimization service to allow or prohibit certain vehicles from operating in a certain zone. The zones can be configured on the fly while building the input optimization request or can refer to geofence IDs created using Geofence API.

Route Grouping is a powerful feature which deals with how a route plan is actually executed and helps users in achieving highly efficient routes. When used, route grouping attributes tune the algorithm to avoid, as much as possible, overlapping of different routes as well as any back and forth movement of vehicles on a road segment.

Users can leverage the modular nature of NextBillion.ai’s Route Optimization by configuring custom distance values when a vehicle goes from one location to another

An important business criteria for logistics providers is handling the cargo safely which can sometimes entail not mixing cargo of certain types when transporting them. Order Incompatibility feature of NextBillion.ai’s Route Optimization is designed to efficiently solve such cases involving multiple types of loads.

In certain industries like car-pooling and emergency services, reducing the amount of time spent in vehicles is a critical factor in assessing the competitive advantage of a business. Optimizing pickups and drop-offs such that the total time in the vehicle for the passengers or field service agents does not exceed a given threshold can be quite complex for traditional softwares.

Businesses in industries like e-commerce, retail deliveries, and logistics providers deal with a variety of goods & items.

The total distance that a vehicle can drive or the total travel time that a vehicle can operate for, is an important business constraint for many logistics providers as well as fleet owners

Depots or fulfillment centers are a key component in industries like e-commerce, retail deliveries. They are critical for order processing, and storage of goods while helping businesses manage the inventory efficiently and ensure quick and accurate delivery to customers

The ultimate goal of any route optimization exercise is to improve the profitability of the business. One of the ways to do so is to choose the routes which lead to the highest revenue earned.

Managing a fleet with a variety of vehicle types—such as cars, trucks, and minivans—often requires separate route planning requests for each vehicle type, leading to unnecessary complexity and inefficiency.