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Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - LOGISTAR (Enhanced data management techniques for real time logistics planning and scheduling)

Teaser

Summary

The main objective of LOGISTAR project is to allow an effective planning and optimization of transport operations in the supply chain by taking advantage of horizontal collaboration and relying on real-time data gathered from an interconnected environment. For this, real-time decision-making support tools and visualization tools of freight transport will be developed. Their purpose is to deliver information and services to the various agents involved in the logistic chain.

The European Union faces the challenge of maintaining and increasing its economic growth and cope with an increasing freight transport demand and limited transport infrastructure in the next years and decades. Considering the crucial importance of freight industry and its influence, there is a need to increase its efficiency.

LOGISTAR will leverage the data available related to logistics and transport, such as data coming from intermodal mobility transport (logistic infrastructures, transport schedules, prices, traffic congestion, accidents and road networks), to process it in real-time and to deliver services-based optimization and planning of resources and routes. In particular, this will be done taking into account concepts such as synchromodality, prediction of disruptions in real-time, and collaboration through negotiation and identification.

The project will be deployed in three Living Labs to test its effectiveness in real operation environments.

LOGISTAR seeks to improve the logistic infrastructure by means of the use of cutting-edge ICT technologies. It aims to reduce the distribution cost in a 5 to 10%, loading factors (up to 10%) and to enhance the synchromodality, as the use of different transport means.

Work performed

LOGISTAR project has been launched in June 2018 and has already been running for 18 months. The first step in achieving the LOGISTAR objectives was to identify the end user needs and system requirements so that LOGISTAR solution could solved the weaknesses in the current systems. For this, 21 interviews with companies from a range of industry sectors in five different countries were conducted and a coherent list of user needs and system requirements was produced.

Afterwards, the main research technologies of the project started to be developed:

- Data sources concerning the Living Labs have been identified and specified and a LOGISTAR data model is under definition. Also, the data
acquisition pipelines, metadata, data enrichment and the semantic layer have been specified and are already implemented.
- A state-of-the-art analysis on artificial intelligence and optimization techniques applied to logistics has been performed.
- Algorithms for predicting timings and events for a logistics plan, and for learning and inference of stakeholder preferences for optimisation have
been developed and partially implemented.
- The global optimization routing engine, which includes the mathematical analysis of the model, as well as the design and implementation of the
engine has been developed.
- An analysis of the negotiation strategies used by companies to promote co-loading and back-hauling has been performed, as well as a first
implementation using electronic agents. These analysis and automatic negotiation includes routing re-optimization.
- The technical basis server infrastructure has been already designed and implemented.
- The Living labs for testing LOGISTAR solution have been outlined. The location, the resources involved, and the test plan have been defined
including the technical specifications for the system deployment.

Next steps include the deployment and the first testing activities in the Living Labs of the different subsystems being this: module for prediction of timings in the logistic network and events, global optimization module for the planning of resources and the automated negotiation and re-optimisation module basing on the real time events and incidents.

The LOGISTAR consortium has been actively participating in external events and promoting the results already achieved in LOGISTAR to the external world. LOGISTAR has been presented in several conferences and the first Usersâ€™ Board workshop held at the IPIC conference in London (July 2019).

Final results

Here are the main advances beyond the state of the art:

Artificial intelligence focused on prediction
Predictive models will be developed which can predict arrival times for different legs in logistics transportation, between specific locations, for specific vehicle types, at different hours of the day, days or the week, or times of the year. These will be augmented with predictions of turnaround times at the destinations, which will again be location, time and season specific. Finally, models for acquiring the preferences of specific companies and logistics staff in those companies for balancing the trade-offs between important objectives such as time, distance, cost and reliability of logistics components will be developed.

Global optimisation planning
Research on mathematical models and optimization meta-heuristics focused on the reduction of logistic costs in different real scenarios will be done. Up to now, an optimization model for the collaborative optimization of more than one logistic company is under production, dealing with constraints in order to make the solution feasible for all the parts.

Automated negotiation and planning re-optimisation
Research on models of automated negotiation agents that propose the exchange of tasks. Every agent has a set of tasks (deliveries to be done) but can propose to other agents to perform part of these tasks on the basis of a pre-fixed compensation (according to the distance of the delivery). The agents can automatically suggest exchanges for those tasks that are expensive for them, detecting other agents for which they are cheaper, and who could accept them. This implies that every agent knows their own set of tasks, can optimize them, but also knows (part) of the task of other agents.

LOGISTAR will deliver two services based on the advanced processing techniques:
â€¢ A control and decision-making tool for logistics operations capable of monitoring of goods through the whole logistics chain, allowing an
integrated planning of resources and providing dynamic routing relying on synchromodality and horizontal collaboration among agents.
â€¢ Real time information of freight transport will be delivered by means of a website, where the position of the goods in real time in the
various means of transport will be shown.

The project results will contribute to enhance different aspects related to logistics and freight transportation. LOGISTAR will improve the logistic infrastructure by means of the use of cutting-edge ICT technologies. Reducing the distribution costs in a 5 to 10%, increasing loading factors by 10% derived from the optimization techniques applied to freight deliveries planning and shortening the delivery routes by 10% thanks to applying planning of optimal routes relying on synchromodality, being continuously updated in case of disruption.