Agent-Based Model and Simulations of the Management of Ports: The Import Processes at the Port of Genoa

Ports have an integral role of our economy, they are strategic places of exchange, and especially over the last few decades and with the phenomenon of globalization, the ports are a reality in continuous movement and growth. Therefore, they are operating places of extreme complexity, especially in their logistics functions of transport management. The paper deals with the modelling and implementation of the import process of goods in a port in order to make more organized, fast and efficient complex logistics network, through ad-hoc development policies. To this purpose, we develop an agent-based model (ABM) of a port, populated by the real main actors (stakeholders) involved in the port activities. The model simulates the actual port processes, i.e., the sending of goods, the acceptation or not of imported goods, the planning of transports etc. With this framework, the business process is implemented for developing a computer supported management tool to handle the port activities flow. The tool is designed for the integration in a virtual infrastructure that allows an advanced operational management of port traffics. By modelling the time documentation according to the specification of the Genoa case, the business case of the port of Genoa is tested. Results show that the mechanism implemented simulates the actual process. Moreover some bottleneck are discovered, such as delays to the handling of the containers and queues formation due to missing documentation or documentation with errors or not ready.

[1]  Filippo Ricca,et al.  Modeling Business within a UML-Based Rigorous Software Development Approach , 2008, Concurrency, Graphs and Models.

[2]  Thomas H. Davenport,et al.  Process Innovation: Reengineering Work Through Information Technology , 1992 .

[3]  MengChu Zhou,et al.  Modular Design of Urban Traffic-Light Control Systems Based on Synchronized Timed Petri Nets , 2014, IEEE Transactions on Intelligent Transportation Systems.

[4]  Wil M. P. van der Aalst,et al.  On the Suitability of BPMN for Business Process Modelling , 2006, Business Process Management.

[5]  Ramtin Khosravi,et al.  Modeling Variability in Business Process Models Using UML , 2008, Fifth International Conference on Information Technology: New Generations (itng 2008).

[6]  R. Palmer,et al.  Asset Pricing Under Endogenous Expectations in an Artificial Stock Market , 1996 .

[7]  Linda Ponta,et al.  Traders' Networks of Interactions and Structural Properties of Financial Markets: An Agent-Based Approach , 2018, Complex..

[8]  Silvano Cincotti,et al.  Information-based multi-assets artificial stock market with heterogeneous agents , 2011 .

[9]  Maristela Holanda,et al.  Business process modelling: A study case within the Brazilian Ministry of Planning, Budgeting and Management , 2014, 2014 9th Iberian Conference on Information Systems and Technologies (CISTI).

[10]  Mauro Gallegati,et al.  Validating and Calibrating Agent-Based Models: A Case Study , 2007 .

[11]  H. J. Harrington,et al.  Total improvement management : the next generation in performance improvement , 1995 .

[12]  Benjamin Pfaff Process Management A Guide For The Design Of Business Processes , 2016 .

[13]  Kagan Tumer,et al.  Improving Air Traffic Management with a Learning Multiagent System , 2009, IEEE Intelligent Systems.

[14]  Jan Mendling,et al.  A Framework for Assessing BPM Success , 2014, ECIS.

[15]  Giorgio Fagiolo,et al.  Validation of Agent-Based Models in Economics and Finance , 2019, Simulation Foundations, Methods and Applications.

[16]  Peter Stone,et al.  A Multiagent Approach to Autonomous Intersection Management , 2008, J. Artif. Intell. Res..

[17]  Marco Raberto,et al.  A multi-assets artificial stock market with zero-intelligence traders , 2011 .

[18]  A. Simons,et al.  A Survey of Service Oriented Development Methodologies , 2007 .

[19]  Claudia Pahl-Wostl,et al.  Understanding Climate Policy Using Participatory Agent-Based Social Simulation , 2000, MABS.

[20]  Mario Piattini,et al.  MINERVA: Model drIveN and sErvice oRiented Framework for the Continuous Business Process improVement and relAted Tools , 2009, ICSOC/ServiceWave Workshops.

[21]  Silvano Cincotti,et al.  Static and dynamic factors in an information-based multi-asset artificial stock market , 2018 .

[22]  Marco Raberto,et al.  An agent-based stock-flow consistent model of the sustainable transition in the energy sector , 2018 .

[23]  William J. Kettinger,et al.  Business Process Change: A Study of Methodologies, Techniques, and Tools , 1997, MIS Q..

[24]  A. Carbone,et al.  Resistive transition in disordered superconductors with varying intergrain coupling , 2010, 1011.5607.