In 1959, American mathematicians George Dantzig and John Ramser proposed a question: “What is the optimal set of routes for a fleet of vehicles to traverse in order to deliver to a given set of customers?”
We’ve come a long way in the past 60 years in solving this problem. While other mathematical questions remain unsolved, Dantzig & Ramser’s Vehicle Routing Problem lies in the core of the modern route optimization algorithms. Moreover, these changes are not just theoretical – companies with more optimal route times could cut overhead, idle time, delivery costs, and save on fuel, all while reducing delivery times across sectors.
Route optimization’s major benefits depend, at the highest level, on whether you’re refining last-mile or line hauling operations. Let’s look at how this works in each of these two sectors that reveal the power of optimization – but first, a primer on the terminology.
Last-mile operations refer to deliveries made from a transportation hub to its final destination, often in urban or suburban areas. The emphasis is on making the delivery as quickly as possible without raising costs, often requiring drivers to make hundreds of deliveries a day – and creating a complex challenge for route planners. Line hauling, in contrast, refers to the shipping of freight via land, sea, or air to reach a transport hub, where the products are sorted out for further transportation. Line hauling operations eventually reach last-mile delivery hubs; however, the logistics of line hauling cover more distance.
At the same time, customers in both B2B and B2C industries expect their goods to arrive faster than ever to their residences or places of business.
Amazon may have popularized the 2-day, 1-day, and even 2-hour delivery window; however, the price remains a crucial component of the e-commerce landscape, particularly as annual online spending is expected to reach $2.7 trillion. When one survey asked whether customers prefer faster shipping speed or lower shipping costs, the respondents answered with an even split. They want both better delivery times and cheaper costs – then again, so do companies planning their own logistics operations.
There are several recent tech innovations that can help improve shipping times, including drones and autonomous vehicles. However, companies don’t need to overhaul their delivery vehicles entirely to see results. Route Optimization involves delivering more in less time with the vehicles and staff available today. It brings in a number of valuable benefits to companies handling shipping operations while increasing the capacity utilization in both last mile and line haul operations.
Last Mile Route Optimization
Both logistics service providers and private fleet operators can increasingly benefit from route optimization software. These tools utilize batch-planning algorithms to create a number of possible and alternative routes on a given day. Rather than manually planning routes themselves, dispatchers can gain a broader look at all the possibilities to decide which routes are most efficient given the delivery conditions.
The dispatcher-centric approach gives companies a stronger degree of control over route planning. However, delivery drivers consistently note that improvements can be made, given the traffic and road conditions which occur after a route is set. Modern route optimization technologies take these real-time changes into consideration, allowing for ‘on-the-fly’ route tracking that provides a cost vs. time tradeoff.
This kind of real-time reporting also helps with one of the key struggles in logistics management: customer satisfaction. The ability to provide up-to-the-minute updates to customers expecting a shipment – even for bulk orders or in remote delivery locations – is a key asset in improving customer satisfaction. The estimated time of arrival (ETA) is automatically adjusted, and some tools even provide automatic updates for the customer based on changes.
For instance, OptimoRoute offers intelligent route planning which can address many use cases beyond e-commerce, logistics, and food delivery. Another great example is Routific, a route planning application improving delivery times for B2B and B2C companies. Users upload each stop and then adjust routes for full customization, which dispatchers communicate to their drivers’ smartphones via the Routific app. Live tracking keeps dispatchers and customers up-to-date on ETAs, providing rapid updates on any changes. Finally, data analysis is provided through analytics available at the end of each day, allowing businesses an opportunity to improve their strategy iteratively. Companies have achieved 28% reductions in delivery costs and 37% savings on fuel by implementing this technology into their logistics planning.
These sorts of changes, adopted through consumer-grade technology, are possible for companies operating fleets in urban delivery environments. When it comes to moving freight between cities and hubs, however, the nature of logistics works quite a bit differently.
Line Haul Route Optimization
Line haul refers to the movement of freight goods between distant cities, utilizing railines, roads, waterways, and air. In contrast to last-mile, linehaul logistics involve distances of hundreds of kilometers or more, and include a wider array of depots, vehicles, and workers to manage shipping.
Data analytics is a top priority when it comes to line haul optimization. By analyzing the fluctuations in shipping volumes, distances between transport hubs, number of transport hubs, and information on issues disrupting the flow of goods, logistics companies can gain a deeper understanding of how their budgets are being spent. A comprehensive analysis will also include a look at last-mile shipping – specifically, how it affects long-distance transportation of goods and the location of transport hubs.
Line haul optimization is a massive undertaking. Logistics companies operating in the long haul sector often have multiple hubs, hundreds of drivers, and heavy-duty equipment such as trucks to transport goods. The decision to close or open a hub or to expand a fleet cannot be taken lightly and must be informed by solid research data.
Predictive analytics is key to tackling issues within line haul optimization. Routing and capacity restrictions, along with shipment deadlines are the main forces behind optimization. Historical forecasts serve as a basis for the optimization by calculating the most cost-effective way of transporting the predicted volumes. This information shows which trips are safe to cancel without impacting delivery performance and customer service levels. In other words, logistics planners and dispatchers can decide how to plan the route of their trucks – straight to the destination hub or stopping by another hub along the way, making the trip a bit longer, but utilizing much more line haul capacity.
By using Artificial Intelligence and complex proprietary forecasting and optimization algorithms, Transmetrics predictive network planning software helped to significantly improve the capacity utilization of Speedy (part of DPDgroup) and optimize their line haul operations, while canceling unnecessary line hauls. With predictive tools, Speedy has reduced its hub-to-hub costs by 25%, with a 14% increase in fleet utilization. With a total cost reduction of 7-9%, the company is now speedier than ever.
A few months ago, Transmetrics has been awarded a €1.67 million grant from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 945610. This funding will accelerate the research and development activities of Transmetrics, and it will help to increase the offerings and customer value creation.
Since the beginning of March 2020, Transmetrics has been developing a commercially viable tactical optimization solution for the mid-sized logistics market and we are actively looking for beta users to test the solution. It will include what-if functionality that allows planners to make informed sourcing and repositioning decisions based on Transmetrics’ next-generation optimization AI tools.
The Route to Optimization
Whether it’s last-mile or line haul, an emphasis on reducing both delivery times and operating costs is essential for success in the 2020s. Customer demands are higher than ever while the nature of regional, national, and global shipping has changed dramatically.
This heightened demand comes as labor shortages are predicted throughout the shipping industry. Route optimization provides one of the best avenues for handling these shortages, allowing logistics firms to do more with the employees they have.
Logistics firms need deeper insights than ever before to meet these challenges. Data Analytics and Predictive Optimization tools can illuminate better routes while reducing the cost of vehicles and hubs that are not performing as needed. If applied properly, these insights can improve the bottom line while optimized routes and planning can enhance the service levels – a dual win for companies needing that extra edge in an increasingly competitive shipping environment.