A Hybrid Recommender System to Improve Circular Economy in Industrial Symbiotic Networks

Abstract

Recently, the need of improved resource trading has arisen due to resource limitations and energy optimization problems. Various platforms supporting resource exchange and waste reuse in industrial symbiotic networks are being developed. However, the actors participating in these networks still mainly act based on predefined patterns, without taking the possible alternatives into account, usually due to the difficulty of properly evaluating them. Therefore, incorporating intelligence into the platforms that these networks use, supporting the involved actors to automatically find resources able to cover their needs, is still of high importance both for the companies and the whole ecosystem. In this work, we present a hybrid recommender system to support users in properly identifying the symbiotic relationships that might provide them an improved performance. This recommender combines a graph-based model for resource similarities, while it follows the basic case-based reasoning processes to generate resource recommendations. Several criteria, apart from resource similarity, are taken into account to generate, each time, the list of the most suitable solutions. As highlighted through a use case scenario, the proposed system could play a key role in the emerging industrial symbiotic platforms, as the majority of them still do not incorporate automatic decision support mechanisms.

Information and Communication Technology Solutions for the Circular Economy

“…To enhance decision support in CE models, a range of scientific approaches grounded in recommender systems, reasoning techniques or semantic technologies can also be found. Gatzioura et al present a hybrid recommender system, which supports industrial users in identifying possible resources and symbiotic partners, improving overall performance [53]. Case-based reasoning (CBR) has also been utilized for solving problems and supporting decisions in the CE domain.…”

Machine learning‐assisted industrial symbiosis: Testing the ability of word vectors to estimate similarity for material substitutions

“…Regarding the evaluation of such systems, a comparison of the approach to NPMI has been done; however, it would be very interesting to compare and benchmark a broader range of approaches such as the hybrid approach of Gatzioura et al. (2019) and the more traditional approaches listed in Table 1 centering on name or classification matches. Establishing an unbiased method to benchmark approaches with verification enabled through comparison to real‐world cases would improve our understanding of the strengths and drawbacks of various existing and novel approaches in the future.…”

“…One example being the case‐based reasoning approach (proposing solutions based on those that worked for situations with similar aspects) taken by Gatzioura et al. (2019) in their development of the Sharebox platform.…”

“…Furthermore, efforts have been made in developing hybrid approaches to elicit more exchange potential through less explicit information. One example being the case-based reasoning approach (proposing solutions based on those that worked for situations with similar aspects) taken by Gatzioura et al (2019) in their development of the Sharebox platform.…”

European Waste Statistics data for a Circular Economy Monitor: opportunities and limitations from the Amsterdam Metropolitan Region

“…A typical example of secondary resource supply and demand matching are recommender systems for industrial symbiotic networks. They recommend the best suitable alternative destination for industrial waste instead of a conventional waste disposal option based on such information fields as waste codes, user assigned keywords and descriptions, waste/material quantities, generation frequency, and site location (Gatzioura et al, 2019;van Capelleveen, 2020;Yeo et al, 2019;Maqbool et al, 2019).…”