scholarly journals On the evolution of maritime ports towards the Physical Internet

Futures ◽  
2021 ◽  
Vol 134 ◽  
pp. 102834
Author(s):  
Patrick B.M. Fahim ◽  
Manuel Martinez de Ubago Alvarez de Sotomayor ◽  
Jafar Rezaei ◽  
Arjan van Binsbergen ◽  
Michiel Nijdam ◽  
...  
Keyword(s):  
Author(s):  
Eric Ballot ◽  
Benoit Montreuil ◽  
Zach G. Zacharia

Author(s):  
Patrick Fahim ◽  
Jafar Rezaei ◽  
Raja Jayaraman ◽  
Marc Poulin ◽  
Benoit Montreuil ◽  
...  
Keyword(s):  

Author(s):  
Safwen Ben Neila ◽  
Abderahman Rejeb ◽  
Péter Németh

In recent years, there is a need for new methods and frameworks for planning transport systems, improving their efficiency, and addressing globalisation and sustainability challenges. In addition, the use of existing capacities and infrastructure has raised significant issues in the transport sector. To achieve an economically, environmentally, and socially sustainable logistics ecosystem, Benoit Montreuil introduces the concept of “Physical Internet” (PI) to increase the efficiency and effectiveness of logistics networks. As a ground-breaking transportation philosophy, the PI aims to revolutionise freight and logistics transport. Moreover, the PI can enhance logistics productivity through the organisation of large-scale pooling. Similar to Digital Internet that conveys data, the PI strives to connect, synchronise, and ship regular modular containers from the point of origin to an exact destination, thereby creating robust and collaborative logistics networks. While the literature on the PI is relatively growing, there is still a lack of reviews that synthesise this knowledge body, identify current trends and gaps, and advance the research more broadly.  Therefore, this study aims to investigate the potentials of the PI for the development of sustainable logistics networks. Overall, 59 studies are selected from leading academic databases and further analysed. The review findings reveal that most scholars focus on the optimisation of transport at the tactical and organisational stage while devoting little attention to the contribution of the PI to the social sustainability of logistics compared to the economic and environmental aspects.


2019 ◽  
Vol 11 (11) ◽  
pp. 3127 ◽  
Author(s):  
Tarik Chargui ◽  
Abdelghani Bekrar ◽  
Mohamed Reghioui ◽  
Damien Trentesaux

In the context of supply chain sustainability, Physical Internet (PI or π ) was presented as an innovative concept to create a global sustainable logistics system. One of the main components of the Physical Internet paradigm consists in encapsulating products in modular and standardized PI-containers able to move via PI-nodes (such as PI-hubs) using collaborative routing protocols. This study focuses on optimizing operations occurring in a Rail–Road PI-Hub cross-docking terminal. The problem consists of scheduling outbound trucks at the docks and the routing of PI-containers in the PI-sorter zone of the Rail–Road PI-Hub cross-docking terminal. The first objective is to minimize the energy consumption of the PI-conveyors used to transfer PI-containers from the train to the outbound trucks. The second objective is to minimize the cost of using outbound trucks for different destinations. The problem is formulated as a Multi-Objective Mixed-Integer Programming model (MO-MIP) and solved with CPLEX solver using Lexicographic Goal Programming. Then, two multi-objective hybrid meta-heuristics are proposed to enhance the computational time as CPLEX was time consuming, especially for large size instances: Multi-Objective Variable Neighborhood Search hybridized with Simulated Annealing (MO-VNSSA) and with a Tabu Search (MO-VNSTS). The two meta-heuristics are tested on 32 instances (27 small instances and 5 large instances). CPLEX found the optimal solutions for only 23 instances. Results show that the proposed MO-VNSSA and MO-VNSTS are able to find optimal and near optimal solutions within a reasonable computational time. The two meta-heuristics found optimal solutions for the first objective in all the instances. For the second objective, MO-VNSSA and MO-VNSTS found optimal solutions for 7 instances. In order to evaluate the results for the second objective, a one way analysis of variance ANOVA was performed.


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