A Framework for Industrial Symbiosis Systems for Agent-Based Simulation

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The industrial symbiosis (IS) practice refers to replacing production inputs with wastes generated by other production processes, thus helping to close the loop of manufacturing processes. Companies adopting IS can reduce the amounts of wastes disposed of in landfills and primary inputs used in production processes, enhancing their production efficiency and reducing their production cost. The Agent-based modeling (ABM) approach has been recently adopted to advance the knowledge in the IS field, in particular to explore the extent to which the establishment of IS relationships can be affected by policy measures, benefit-sharing contracts, information-sharing tools, or social factors. However, the agentbased models proposed in the literature are highly different in terms of agents considered, their attributes, possible actions, and decisional rules. In particular, these models might result far from the real world, in terms of how the agents are modeled, as well as on the actions that they can undertake. The aim of this paper is to provide a general framework on how to model IS systems with ABM in a comprehensive way. The paper provides a literature review on IS aimed at identifying the potential agents in IS, their attributes, and their potential actions, shaped by technical, economic, and regulatory issues affecting the behavior of agents in terms of strategic management. Based on the results of the literature review, a general framework is proposed and discussed. This paper is expected to advance the knowledge on ABM for IS by providing useful suggestions to modelers and academicians.
Original languageEnglish
Title of host publicationProceedings - 21st IEEE Conference on Business Informatics, CBI 2019
EditorsJorg Becker, Dmitriy Novikov
Place of PublicationPiscataway, NJ
Number of pages10
ISBN (Electronic)978-1-7281-0650-2
ISBN (Print)978-1-7281-0651-9
Publication statusPublished - 22 Aug 2019
Event21st IEEE Conference on Business Informatics, CBI 2019 - National Research University, Moscow, Russian Federation
Duration: 15 Jul 201917 Jul 2019
Conference number: 21

Publication series

NameProceedings IEEE Conference on Business Informatics (CBI)
ISSN (Print)2378-1963
ISSN (Electronic)2378-1971


Conference21st IEEE Conference on Business Informatics, CBI 2019
Abbreviated titleCBI 2019
Country/TerritoryRussian Federation
Internet address


  • Agent-based Modelling
  • Circular economy
  • Decision support
  • Industrial symbiosis
  • Multi agent technology
  • 2023 OA procedure


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