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Review of methods for circular supply chain analysis: the application for optimisation studies

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Date
2019
Author
Burinskienė, Aurelija
Metadata
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Abstract
The changing economic environment (the program of European Commission "Creating a Circular Economy - a Europe without Waste"), orientation in modernizing, reorganizing traditional supply chains, switching from "linear" to "circular" supply chain, optimizing material and energy consumption and reducing waste, are being studied more extensively by researchers since 2014. The circular supply chain is different from linear in that it links traditional linear processes with reverse logistics processes that include product recovery, product recycling, disassembly, and recycled product reuse. The emergence of the circular supply chain is a natural process in the evolution of the supply chain, but new challenges are now emerging, such as the seamless (non-fragmented) deployment and timing of the relevant functional logistics activities, since the circular supply chain covers more processes and requires optimization. A systematic analysis of scientific literature will be carried out, which will seek to identify scientific works related to the interpretation of the concept of circular supply chain. To gather knowledge about optimization studies, a review of recent publications literature is delivered by identifying scientific methods and quantitative methods used for circular supply chain analysis. Later, methods used for circular supply chain modelling are figured: mathematical programming methods, simulation methods, heuristic methods, hybrid models, and analytical models. After the descriptive analysis of scientific methods and quantitative models is performed, author proposes a set of meta-heuristic methods for optimizing the circular supply chain processes. Finally, conclusions and directions for further research are presented.
Issue date (year)
2019
URI
https://etalpykla.vilniustech.lt/handle/123456789/148581
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  • Konferencijų pranešimų santraukos / Conference and Meeting Abstracts [3431]

 

 

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