Academic publications

Collaboration methodology in between logistics clusters

This paper develops a framework for the massification concept and identifies the success and failure elements as well as the evaluation criteria for a successful massification concept. Well-established logistics clusters, in search of bundling existing good flows with other flows in the logistics chain, still do not leverage their full potentials in terms of competitiveness and sustainability for the European industry and society. There are several reasons such as a lack of advanced collaboration practices between the local actors (i.e.…

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Container flow forecasting through neural networks based on metaheuristics

This paper emphasizes the importance of container flow forecasting and provide a comprehensive tool for that purpose. This paper proposes a fuzzy neural network prediction approach based on metaheuristics for container flow forecasting. The approach uses fuzzy if–then rules for selection between two different heuristics for developing neural network architecture, simulated annealing and genetic algorithm, respectively. These non-parametric models are compared with traditional parametric ARIMA technique. Time series composed from monthly container traffic observations for Port of Barcelona are used…

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Opportunities of Product-Service System in Physical Internet

This paper discusses the new opportunities and perspectives of Product Service System in Physical Internet that is one of the most recent breakthrough paradigms. We also investigate some recent innovative business models, services and practices relevant to PSS and PI, in order to point out emerging research avenues and opportunities. Product-Service System (PSS) has shown great potential in supply chain and logistics management. The potential is even more evident for the recent paradigms of sustainable logistics, for example, the Physical…

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Clusters 2.0 project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 723265

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