SIoT for cognitive logistics: Leveraging the social graph of digital twins for effective operations on real-time events

Abstract

Over the years, with the migration of organizations towards the concepts of logistics 4.0, a paradigm shift was necessary to guarantee logistics efficiency. The challenge is to dynamically cope in real time with vast number of shipments and destinations, which need to be realigned both with a determined lead time and with a finite of available resources. Although a number of standards have already been adopted for the management of transport and logistics operations, taking advantage, for instance, of Decision Support Systems and Geographic Information Systems, new models are required for achieving effective handling of the dynamic logistics environment that is shaped today. In this paper, an integrated logistics framework addressing the previous challenges is presented, for the first time, as a result of the activities of the H2020 COG-LO project. This novel approach exploits Social Internet of Things (SIoT) and the digital twins technique to realize the concept of the Cognitive Logistics Object (CLO). A CLO is defined as an entity that is augmented with cognitive capabilities, it is autonomous, and bears social-like capabilities, which enable the formulation of ad hoc communities for negotiating optimal solutions in logistics operations.

Data-Driven Supply Chain Operations—The Pilot Case of Postal Logistics and the Cross-Border Optimization Potential

“…Though the VRP optimization is an NP-hard problem, using Tabu search heuristics with a combination of ML techniques enabled the requests to be processed in real time, even for an extremely large and dense logistics network (such as the size of European Union region, or large urban areas). A detailed presentation of the algorithmic method can be seen in previous work [ 22 , 23 ].…”