Matching Algorithm Software Increasingly Benefiting Logistics Industry: Augusto Beato

Augusto Beato, CEO of Ice Break Shipping, forecasts that the logistics industry will be relying more heavily on matching algorithm software for process efficiency. He noted that good examples are the software used by Auptix Pooling to implement a hubless LTL pooling strategy and by Schneider in its bulk tanker logistics.

The hubless pooling method is being implemented by Auptix Pooling to combine LTL shipments that are shipping along the same lane to a specific geographic area. These shipments are loaded in real-time onto a full truckload, bypassing hubs and terminals.

The method primarily benefits smaller shippers save on their LTL transportation. "Small and medium-sized businesses that ship any combination of LTL, partial, and full truckload shipments are the primary beneficiaries of this hubless method," said Beato, who is also the CEO of Portland SEO. "They may simply lack enough stores in a geographic region to generate enough product to fill a truck bound for a particular region. Nor do they have the infrastructure, systems, and technology to coordinate such an effort."

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Because the shipments never have to reach a warehouse and are never unloaded until they reach the final destination, freight can move faster and cheaper. There is also a much lower risk of damage and loss.

Auptix Pooling does away with the hub-and-spoke method, where the distribution centers receive products from many different origins, consolidate the products, and send them directly to destinations. This hub-and-spoke method takes longer because trucks have to navigate through hubs en route to the final destination and there's a higher chance of damage and loss.

Similar technology was used by Schneider in its bulk tanker logistics, which addressed the complexity of offering a comprehensive bulk chemical transportation service.

The service involves coordinating thousands of tractors and tankers, product-sequencing constraints, tanker wash and preparation processes, and driver work-rule restrictions. Schneider’s team designed and implemented a multi-phase, multi-dimensional matching algorithm and then teamed up with IBM to create a software system.

“In many cases, you can find the best solution mathematically: It’s the one that maximizes certain factors, such as the use of trucks, trailers, and drivers, while minimizing others, such as the number of empty miles driven, the amount of fuel used and the total delivery time,” said Shaleen Devgun, executive vice president and chief information officer at Schneider.