Agent-based simulation to evaluate and categorize industrial symbiosis indicators

Mantese, Gabriel Couto; Amaral, Daniel Capaldo

doi:10.1016/j.jclepro.2018.03.142

Cited by 39 publications

(12 citation statements)

References 22 publications

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“…A relevant advantage of ABM is that it can be used to simulate a specific system (e.g., industrial area) under different configurations (e.g., without IS and with IS), with the aim to investigate the marginal impact of each configuration (e.g., the benefits created in a given industrial area if IS is implemented). In fact, such an impact can be easily discovered by comparing the same system performance computed under different system configurationsfor an overview of ISNs performance that can be computed through ABM, readers are referred to, e.g., Mantese and Amaral (2018). This characteristic makes ABM useful to investigate the impact that specific factors play on the emergence of IS.…”

Section: Agent-based Modellingmentioning

confidence: 99%

Decision-Support Tools for Smart Transition to Circular Economy

Yazan¹,

Capelleveen²,

Fraccascia³

2022

Advanced Series in Management

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The sustainable transition towards the circular economy requires the effective use of artificial intelligence (AI) and information technology (IT) techniques. As the sustainability targets for 2030-2050 increasingly become a tougher challenge, society, company managers and policymakers require more support from AI and IT in general. How can the AI-based and IT-based smart decision-support tools help implementation of circular economy principles from micro to macro scales?This chapter provides a conceptual framework about the current status and future development of smart decision-support tools for facilitating the circular transition of smart industry, focussing on the implementation of the industrial symbiosis (IS) practice. IS, which is aimed at replacing production inputs of one company with wastes generated by a different company, is considered as a promising strategy towards closing the material, energy and waste loops. Based on the principles of a circular economy, the utility of such practices to close resource loops is analyzed from a functional and operational perspective. For each life cycle phase of IS businessese.g., opportunity identification for symbiotic business, assessment of the symbiotic business and sustainable operations of the businessthe role played by decision-support tools is described and embedding smartness in these tools is discussed.Based on the review of available tools and theoretical contributions in the field of IS, the characteristics, functionalities and utilities of smart decision-support tools are discussed within a circular economy transition framework. Tools based on recommender algorithms, machine learning techniques, multi-agent systems and life cycle analysis are critically assessed. Potential improvements are suggested for the resilience and sustainability of a smart circular transition.

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Section: Agent-based Modellingmentioning

confidence: 99%

Decision-Support Tools for Smart Transition to Circular Economy

Yazan¹,

Capelleveen²,

Fraccascia³

2022

Advanced Series in Management

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“…In this research, three indicators are adopted to evaluate the IS level of the EIP, namely eco-connectance (Dai 2010), eco-efficiency (Park and Behera 2014), and industrial symbiosis indicator (Felicio et al 2016). The combination of these indicators has been verified effective through simulating industrial symbiosis in distinct scenarios (Mantese and Amaral 2018).…”

Section: Industrial Symbiosis Assessmentmentioning

confidence: 99%

Agent-based model for simulation of the sustainability revolution in eco-industrial parks

Han

Sun

Jia

et al. 2021

Environ Sci Pollut Res

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Eco-industrial parks (EIPs) are of increasing importance for implementing industrial ecology strategies and are facing increasing challenges in terms of environmental pollution and resource scarcity. As a complex adaptive system, an EIP involves multiple sectors and faces various disturbances that influence its evolutionary trajectories. This study adopts an agent-based model to simulate the material flows and industrial symbiosis process in the EIP, considering the initiative of each company and the ever-changing environment. The proposed EIP model emphasises the heterogeneity of companies and attempts to reflect multiple and dynamic factors that have received less attention in previous studies. This model contains two types of agents, companies and the external environment. A company agent makes decisions and interacts with other agents following its own behaviour rules, while the external environment agent functions to coordinate the material flows and exert influence on the companies. The model has been verified and validated by simulating a 20-year-period development of an empirical EIP in China. The simulation results are assessed by three indicators: eco-connectance, eco-efficiency, and industrial symbiosis indicator. Results showed that during the growing phase, the eco-connectance increased from 0.02 to 0.1 for the non-disturbance situation. The eco-efficiency and industrial symbiosis indicator also realised 78.5% and 74.8% of their total increments. The outcome of this research provides insights for the design of the strategies to improve the industrial symbiosis performance and is of high potential to facilitate EIPs in promoting eco-transformation and sustainable development.

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“…[27]. The application of industrial symbiosis indicators to monitor evolution could further contribute to the system understanding [29]. In this sense, another opportunity identified is the lack of indicators which can predict the most critical characteristics for the system evolution.…”

Section: Systemic Analysismentioning

confidence: 99%

An Evaluation of the Industrial Symbiosis Systems Modeling

Guedes

Souza

Borsato

2019

Advances in Transdisciplinary Engineering

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Industrial symbiosis, a concept derived from industrial ecology, emphasizes the collaborative and synergic production among industries. The particular focus is on cyclical flows of resources (material, energy, water, and/or by-products), in order to minimize impacts on the environment. In this way, an industry could reuse the discarded resources of another industry as an input to production. Essentially, the characteristics of the interaction between components of the system define industrial symbiosis as complex and dynamic. Uncertainty, unpredictability, emergency, and adaptability are determining features of this interaction. The development of such an innovative system requires great effort. An important step is to create a representative model of this new reality to support system change. Hence, the present article develops an evaluation of the industrial symbiosis systems modeling. For this purpose, the research adopted a bibliometric and systemic analysis. The results presented in this paper are: (i) an analysis of scientific knowledge about the theme, (ii) the main points discussed and opportunities extracted in the literature, and (iii) the paradigms of industrial symbiosis modeling and simulating. In addition, this work will cooperate as a research base for the development of a new model, which intends to support decision-making processes, during the creation of symbiosis links.

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Agent-based simulation to evaluate and categorize industrial symbiosis indicators

Cited by 39 publications

References 22 publications

Decision-Support Tools for Smart Transition to Circular Economy

Decision-Support Tools for Smart Transition to Circular Economy

Agent-based model for simulation of the sustainability revolution in eco-industrial parks

An Evaluation of the Industrial Symbiosis Systems Modeling

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