FISOF: A formal industrial symbiosis opportunity filtering method

Yazdanpanah, Vahid, Yazan, Devrim Murat and Zijm, W. Henk M. (2019) FISOF: A formal industrial symbiosis opportunity filtering method. Engineering Applications of Artificial Intelligence, 81, 247-259. (doi:10.1016/j.engappai.2019.01.005).

Abstract

Industrial Symbiotic Relations (ISRs), as bilaterally cooperative industrial practices, are emerging relations for exchanging reusable resources among production processes of originally distinct firms. In ISRs, firms can enjoy mutual environmental, social, and economic benefits. Due to similarities in aim and functionality of ISRs and the concept of Circular Economy (CE), it is expected that ISRs play a major role in implementing CE in the context of industrial production. However, industrial firms generally lack analytical tools tailored to support their decisions whether – and based on what priority – to negotiate a particular ISR opportunity, selected from a set of potential alternatives. This question is the main focus of the decision support method developed in this paper, that we call the “industrial symbiosis opportunity filtering” problem. The key economic factor that influences the decision of firms to reject or negotiate an ISR in real-life scenarios, is the total cost-reduction/benefit that they may enjoy in case the ISR would be implemented. In case they evaluate that a sufficient benefit is obtainable, they see the opportunity as a promising one and pursue to contract negotiations. Following this observation, we take an operations-oriented stance and provide a Formal Industrial Symbiosis Opportunity Filtering method (FISOFin short) that: (1) takes into account the key operational aspects of ISRs, (2) formalizes ISRs as industrial institutions using semantic structures adopted from multi-agent systems literature, and (3) enables evaluating ISR opportunities using implementable decision support algorithms. In practice, the FISOFmethod and its algorithms can be integrated into industrial symbiosis frameworks to support firms in the process of ISR evaluation. We also illustrate how information sharing enables the use of collective strategies to overcome epistemic limitations and provide a decision support algorithm that is able to capture all the mutually promising ISR implementations.

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Contributors

Author: Vahid Yazdanpanah

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