Enhanced Features Support Fleets as Delivery Demand Surges Amid COVID-19

***Updated July 2022***
The demand for deliveries surged because of the COVID-19 pandemic. People stayed home and got their groceries and other essentials delivered to their doorsteps. With this increase in demand came a greater need for effective multi-stop route planning for delivery drivers. Launched in May 2019, the Bing Maps Multi-Itinerary Optimization (MIO) API automates delivery route planning for multiple agents travelling between multiple locations. Since launch, we have listened to customer feedback and made a series of enhancements to meet the growing need.

We are happy to announce that the MIO API now supports up to 200 agents and 2000 waypoint itinerary locations (versus 10 agents and 100 locations at the initial launch).

On top of the rich features introduced in the previous Bing Blog, we have also added some new features to the MIO API to support more scenarios. The following table summarizes the previously supported features and newly added ones.

We encourage you to try the MIO API demo to see how the API handles optimization for the sample scenarios and selected parameters to offer comprehensive delivery route planning.

In this blog, we will further explain how the new features work using some new sample scenarios below. For simplicity of interpreting the optimization results, we will use single agent examples to demonstrate how the optional parameters capacity, quantity, depot, and dropOffFrom can be used, respectively.

Scenario 1: Food delivery courier picking up food from restaurants and delivering to customers

This scenario will make use of capacity, quantity, and dropOffFrom options to plan and create delivery routes. A food delivery carrier named “Sam” has a thermal bag which can carry up to 12 food containers. He needs to pick up the food orders from some restaurants before delivering the orders to customers. To define this sequence of constraints, we’ll use the dropOffFrom parameter.

Agents

Itinerary Items

Note that quantity is an optional parameter defined by numeric values that represents the load quantity in terms of volume, weight or amount (i.e., pallet, case or passenger counts), etc. that the vehicle delivers to or picks up from each location. In this scenario, it can be used to define the number of food containers the carrier can carry. A negative value of quantity indicates dropping off loads at a location, while a positive value of quantity indicates picking up loads from a location. The table below summarizes the optimized itinerary for Carrier_Sam for the above itinerary items.

Optimized Itinerary

The optimized itinerary deleivery route plan for Carrier_Sam is illustrated in the map below. Location 1 is where the Sam starts his shift and Location 10 is where his shifts ends.

Note that Carrier_Sam first picks up two orders from “Mexican Food” at Location 2 and then makes his first Mexican Food delivery to “Customer 2” at Location 3. After that, he picks up all orders from “Pizza Place” at Location 4 and completes the route with four “Pizza Place” deliveries at different locations as well as another Mexican Food delivery at “Customer 4” at Location 8.

Scenario 2: Home delivery service picking up orders from the warehouse and delivering to customers during different time slots.

This scenario will make use of the capacity, quantity, and depot parameter options. A delivery driver “John” needs to pick up some large objects like home appliances and furniture from a warehouse and have them delivered to customers at different locations on his optimal route plan. Each customer has a specified time window for delivery.

If the delivery quantity is large and exceeds the capacity of the agent’s vehicle, the agent needs to be able to make multiple trips during the day to reload at the “Warehouse” and deliver all goods. In the MIO API request, we can define the “Warehouse” as depot to allow the location to be visited more than once. In this example, quantity can be used to represent the volume in square meters.

Agents

Itinerary Items

The table below summarizes the optimized itinerary for driver_John for the above itinerary items.

Optimized Itinerary

The MIO delivery route plan for driver_John is illustrated in the map below. With a capacity constraint of 16, driver_John needs to return to the “Warehouse” several times to pick up more quantity to fulfil the delivery requests from all the customers with a total quantity of 35.

On the map, Location 1 denotes where the agent starts his shift. Location 2, Location 8 and Location 10 all overlap with Location 1, as the driver needs to load several times from the “Warehouse.” By setting “depot”: true in the JSON request, the API allows the truck to visit an itinerary location more than once.

Learn More

To learn more about using the MIO API to develop a multi-itinerary optimization solution, please refer to the MIO API documentation. This documentation has details including various options, how each scenario works, supported methods, sample Request Body and Response, how a transaction is calculated and more to create comprehensive, robust delivery route plans.

For details about all of the Bing Maps APIs that are part of the Bing Maps Platform and how to get licensed, please visit microsoft.com/maps.

Start Building for Free

As we continue to enhance and expand on our APIs, we encourage you to connect with us on the Bing Maps Forum or Microsoft Q&A to share your thoughts and let us know what features you would like to see us add in the future.

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