LogisticsBrain | Self-learning AI-based transport optimization software as a service for the most complex logis-tics scenarios in real-time enabling double-digit cost-, CO2- and tyre wear savings

Summary
Smartlane’s AI-based dispatch software LogisticsBrain is a self-learning, cloud-based software for automated transport optimization. Smartlane’s core technology – the scenario-based optimization AI algorithms in combination with KPI and process analysis – optimizes costs by 40%, planning time by 90%, resources, CO2 emissions and fine dust by 21%, and service quality. LogisticsBrain is the enabler of full automation for logistic systems and dispatching processes that so far still are based on manual processes. Sensitivity analyses offer global transport optima by computing several hun-dreds of scenarios in parallel. In this project, partial routes are linked to form a network flow by crowdsourcing. This allows for real time optimization of transport simply using one software – instead of more than three individual solutions as today. Transport logistics planning challenges are solved by standard-ized interfaces even for freight forwarders with complex IT environments.
Results, demos, etc. Show all and search (0)
Unfold all
/
Fold all
More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/190195324
Start date: 01-06-2022
End date: 31-05-2024
Total budget - Public funding: 2 425 000,00 Euro - 1 697 500,00 Euro
Cordis data

Original description

Smartlane’s AI-based dispatch software LogisticsBrain is a self-learning, cloud-based software for automated transport optimization. Smartlane’s core technology – the scenario-based optimization AI algorithms in combination with KPI and process analysis – optimizes costs by 40%, planning time by 90%, resources, CO2 emissions and fine dust by 21%, and service quality. LogisticsBrain is the enabler of full automation for logistic systems and dispatching processes that so far still are based on manual processes. Sensitivity analyses offer global transport optima by computing several hun-dreds of scenarios in parallel. In this project, partial routes are linked to form a network flow by crowdsourcing. This allows for real time optimization of transport simply using one software – instead of more than three individual solutions as today. Transport logistics planning challenges are solved by standard-ized interfaces even for freight forwarders with complex IT environments.

Status

SIGNED

Call topic

HORIZON-EIC-2021-ACCELERATORCHALLENGES-01-01

Update Date

09-02-2023
Images
No images available.
Geographical location(s)