As ‘on-demand’ expectations increase within supply chains, the freight industry is under continuing pressure to deploy flexible and responsive transport networks that can react to rapid demand changes. In this article Dr Phillip Welch, Managing Director of Open Door Logistics, explains what real-time route optimisation is and how it can benefit freight networks.
What is real-time route optimisation?
If you have a fleet which needs to make a set of collections and deliveries on a day, a route optimisation system can generate an efficient set of planned routes. In real-life, a single set of planned routes often proves unworkable though if a new collection is added at the last minute or a vehicle is delayed. You have to replan your routes as circumstances change and instead of having a single plan, you need to modify your planned routes many times during a single day.
Traditional route optimisation systems only generate a single set of planned routes, which they assume will be followed rigidly. In contrast, a real-time route optimiser is built to robustly handle change. It runs continually, constantly refining its planned routes based on a real-time data feed, to give you the best possible performance.
How does real-time routing benefit freight networks?
As an example, we consider freight networks transporting palletised goods. In the UK, the big players are Pall-Ex, Palletforce, Palletline and Palletways. Pallet networks work on a hub and spoke system. Individual depots are the spokes, they collect pallets from their local customers which they send up to the hub on trunk routes and they receive pallets back from other depots, via the hub, to deliver in their area. Real-time route optimisation brings many benefits to pallet networks:
1) Automated same day collection optimisation. Pallet networks make same day collections – where a truck already on the road making collections and deliveries will be re-routed to make new collections at short notice. A real-time route optimiser can handle same day collections automatically and efficiently. If a new collection is added to the optimiser, it will replan the remaining stops on the active trucks, potentially shifting multiple pending collections between vehicles to make room for the new collection.
2) Reoptimising around loaded pallets. The deliveries for a day are loaded onto trailers at the depot in the early hours of the morning. Tight time restrictions mean that loading starts before a depot’s transport planner even knows about all the pallets coming down from the hub. This means there’s no ‘magic period’ when routes can be planned, knowing all the delivery locations, before loading has started. Once a pallet is loaded onto a trailer, even though the trailer is still sitting in the depot, it’s time-consuming and undesirable to unload it and place it on another trailer. Instead routes have to be replanned on-the-fly as new delivery pallets arrive at the depot from the hub, based around which pallets are already loaded onto trailers. A real-time route optimiser does this automatically – once a pallet is registered as loaded it is ‘locked down’ and reoptimisation, when new jobs come along, will plan efficiently around this.
3) Offering the best collection time-slots to customers. Some real-time optimisers support ‘planning queries’, for time-slot generation. If a customer rings in wanting a same-day collection at a pre-defined time, the system can tell you the best time windows for the collection (e.g. 2pm-3pm), based around your planned routes.
4) Reordering on-board deliveries. Once a pallet is on-board a truck, and the truck has left the depot, obviously it cannot be moved to a different delivery truck. However when circumstances change it can still be beneficial to re-order the deliveries on-board a truck, for example changing the second delivery to be the fourth. This could happen if a new collection comes in, or if the truck is delayed and another delivery with a tight time window needs to brought forward, to avoid a late delivery.
Author Bio: Dr Philip Welch
Dr Philip Welch specialises in the application of modern artificial intelligence techniques to transport logistics problems, with particular focus on computational intelligence. As a Postdoctoral Research Fellow at Aston University, he worked within the FP7-funded EU ADVANCE project, which aimed to create greater efficiency in freight logistics networks using state-of-the-art data mining, machine learning and optimisation techniques. Philip is now Managing Director of Open Door Logistics, a company which has developed ODL Live, a real-time route optimisation system with support for advanced features such as planning queries. ODL Live can be deployed for a host of on-demand services from freight delivery and collection through to mobile workforce management.
