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All businesses are tied together with a couple of common acts that they perform in their strife of standing out. A business has a budget plan, inventory, operations, marketing etc all these once combined and in sync is what makes a business work. Likewise the common thread amongst on-demand delivery based businesses is the need to plan daily routes to deliver. And this exercise might need to be done multiple times during the day depending on the nature and scale of your business.

There are multiple parameters, resource constraints, stakeholders and schedules to take into consideration while chalking out these routes or the delivery plans. The challenge is to find the shortest or the best routes to visit a given number of places, with a certain number of resources available at disposal. This is an industry-specific problem faced by logistics players every day and it is vital to optimize the resource utilization while deciding on routes, as cost incurred to make these deliveries makes a crucial part of business economics. Businesses can benefit tremendously from having easy access to reliable tools to automate and help plan these routes.

  • Stakeholders – Customers, business owners, delivery personnel
  • Resources – Fleet members, time, vehicles, fuel
  • Restrictions – Shift timings of fleet, max number of tasks per person, earliest and latest pick up and drop times for different shipments, carrying capacity of vehicles

Flight map algorithm has been built around the primary requirement to identify most efficient routes to make multiple deliveries, enabling businesses increase their productivity by saving time spent in planning and traveling. Flight Map APIs are currently available for two types of routing problems:

1. Simple Vehicle Routing Problem – Single pick up and multiple drop locations

Most common use case of this problem is generally seen with businesses such as food delivery or courier delivery etc where there is single point of start for each delivery personnel such as a restaurant or a central hub.
Parameters to be defined:

  • Id of each order, coordinates of each order delivery location, time window during which service has to be performed and duration of each service
  • Id of each fleet, coordinates of start and end location of each vehicle, shift times of each vehicle/delivery

There can be other parameters thrown into mix such as restrictions of maximum number of tasks or deliveries per person.

Once you have the orders, businesses need to feed the inputs in the form of above parameters to Flight Map API, that will analyze the possible combinations of routes.

2. Multiple pick up and multiple drop off problem

A common use case for this routing problem is where agents need to pick shipments from different places around the city and deliver them same day within the city. E.g an aggregated grocery delivery platform, where delivery personnel needs to pick up grocery packages from one of many stores on the platform depending on current proximity and deliver to customers across the town.

Parameters to be defined for shipments – Id for each shipment, coordinates for pick up and drop off location for each shipment, time window between which shipment is available for pick up and time window in which shipment can be dropped.

On delivery side – Id of each agent, coordinates of start and end location of each vehicle, shift times of each vehicle/agent need to be defined

To create additional restrictions, certain options parameters can be added such as maximum number of pick ups that can be made by a fleet before delivering a shipment.

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API response in both cases consists of actionable list of solutions i.e. list of agents mapped to the services or order deliveries that they need to perform, number of routes all agents have to take in order to complete all the tasks, along with calculations of total time taken by all the agents to complete all the tasks, the time by which all the tasks will be completed and total distance covered by all the agents. The Flight Map API uses Google Maps to identify the time and distance between different locations.
Effectively, the solution provides the best sequence in which products should be delivered, factoring in aspects like time, maximum carrying capacity of the vehicle and the total cost involved. To find out more, click here.

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