Multiagent Industrial Symbiosis Systems

Research output: ThesisPhD Thesis - Research UT, graduation UT

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Multiagent Systems (MAS) research reached a maturity to be confidently applied to real-life complex problems. Successful application of MAS methods for behavior modeling, strategic reasoning, and decentralized governance, encouraged us to focus on applicability of MAS techniques in a class of industrial systems and to develop multiagent models, coordination methods, and decision support tools for this context.

We direct attention towards a form of industrial practices called Industrial Symbiosis Systems (ISS) as a highly dynamic domain of application for MAS techniques. In ISS, firms aim to reduce their material and energy footprint by circulating reusable resources among the participants. To enable systematic reasoning about ISS behavior and support firms' (as well as ISS designers’) decisions, we saw the opportunity for marrying industrial engineering with multiagent systems research. This enabled the introduction of contextualized representation frameworks to reason about the dynamics of ISS, operational semantics to develop computational models for ISS, coordination mechanisms to enforce desirable ISS implementations, and transaction cost allocation methods that ensure fairness and stability properties in ISS.

In practice, the contributions presented in this work are proved to aid firms and policy-makers for evaluating, coordinating, and allocating costs in industrial symbiosis. Our formal frameworks lead to practical tools with commercialization potentials and are validated through various sessions with industrial firms. We argue that this work is the first attempt—and can be a motivation for further approaches—on practical application of MAS technologies in the context of industrial symbiosis as it presents MAS-oriented methodological foundations for ISS development and elaborates on various open problems.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • University of Twente
  • Zijm, Henk, Supervisor
  • van Hillegersberg, Jos, Supervisor
  • Yazan, Devrim Murat, Co-Supervisor
Thesis sponsors
Award date27 Nov 2019
Place of PublicationEnschede
Print ISBNs978-90-365-4887-8
Publication statusPublished - 27 Nov 2019


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