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Leveraging Neutrosophic Uncertainty Theory toward Choosing Biodegradable Dynamic Plastic Product in Various Arenas
Summary
This paper uses a mathematical decision-making framework (neutrosophic uncertainty theory) to help choose among biodegradable plastic alternatives, recognising that replacing conventional plastics is complex and context-dependent. While not a primary microplastics study, it is relevant to efforts to reduce the production of persistent plastics that ultimately break down into microplastic pollution.
Numerous studies in recent years have documented the negative effects of plastic waste on the environment and human wellness. Due to their widespread usage in daily life, particularly in packaging, and their rising direct or indirect discharge into the environment, plastics are recognized as an emerging environmental hazard. Thus, this point is considered the first problem in this study. As a result, efforts to replace traditional plastics with bioplastics have intensified. However, studies regarding the effects of conventional and bioplastics (BioPs) are also important. Hence, biodegradable polymers for industrial and commercial usage are essential in the present day as an alternative to traditional plastic. Another point considered in this study is packaging which entails the quest for new natural materials that may be included in the production of reusable, eco-friendly, and long-lasting flexible polymers. Prior studies demonstrated that starches from both tubers and grains may be processed into malleable biopolymers. Since the quality of the carbs from different vendors varies, choosing which one to work with presents a Multi-Criteria Decision-Making (MCDM) challenge. This paper proposed a neutrosophic MCDM methodology to select the best biodegradable dynamic plastic product (BDPP). The neutrosophic method is used to overcome uncertain data. The neutrosophic is integrated with the Additive Ratio Assessment (ARAS) method. The weights of the criteria are computed then the rank of BDPP is obtained by the neutrosophic ARAS method.
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