Sudden changes to lockdown restrictions during COVID-19 has made 2020 an extremely challenging year for the local high street including bakers, cafes, restaurants and charities in their fight for survival. With premises unable to open and with an excess supply, businesses have been forced to adapt to new ways of operating through reliance upon offering takeaway services or delivering their products directly to customers. Planning for an efficient delivery supply chain for SMEs in such a short timescale is straightforward when there is one courier delivering goods from the business premises to the customer before returning. It is a lot more challenging to ensure efficiency in situations with multiple couriers using multiple methods of travel delivering to multiple customers concurrently.
City Science were successful in obtaining funding from Innovate UK to develop RUSH as a tool to help SMEs and volunteer groups within the Exeter area plan deliveries during the COVID-19 crisis. RUSH is a free to use online tool that utilises algorithms combined with open-source mapping to derive optimal delivery routing and scheduling plans.
The scope of the tool aimed to:
- Develop a single page online tool allowing users to enter a set of delivery postcodes and schedules and derive an optimal routing plan.
- Generate solutions to incorporate route planning for cargo bikes.
- Incorporate functions accounting for restrictions associated with electric vehicles and cargo bikes.
City Science Response
Our award-winning team of software developers and transport technologists developed RUSH to allow users to input courier data such as their method of travel, goods carrying capacity and shift hours alongside locational data pinpointing the depot hub location and customers' addresses.
Using these inputs, RUSH calculates an optimal schedule and route for each courier that minimises overall travel time and distance.
RUSH is underpinned by City Science's decarbonisation ethos. Although it can account for many modes, a unique feature is its ability to effectively route and account for the needs of cargo bikes, e-bikes and electric vehicles. Under the bonnet, the algorithm devises the most efficient cycling route through the use of Open Street Map’s bicycle preference triangle to balance the factors of speed, topography and cycle infrastructure. The algorithm for e-bikes and electric vehicles accounts for the respective mileage range and charging time.
Our success on developing the preliminary version of RUSH has meant we have have been successful in obtaining further funding from Innovate UK to make additional enhancements to the tool.