preprints.org > engineering > industrial and manufacturing engineering > doi: 10.20944/preprints202307.1685.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 25 July 2023 / Approved: 25 July 2023 / Online: 26 July 2023 (02:43:27 CEST)

The objective of this study was to apply simulation and computational intelligence techniques using artificial intelligence and genetic algorithm for economic and environmental optimization of the reverse network (manufacturers, waste managers and recyclers in São Paulo, Brazil) of waste electrical and electronic equipment (WEEE) to promote circular economy. For the economic evaluation, the reduction of: fuel, drivers, insurance, depreciation, maintenance and charges was considered and for the environmental evaluation, the environmental impact was measured in the abiotic, biotic, water, land, air and greenhouse gases compartments. It is concluded that the optimized structure of the WEEE reverse chain for São Paulo, Brazil reduced the number of collections, making the most of the cubage. It also generated economic and environmental gains, contributing to the strategic actions of the circular economy. Thus, the proposed simulation allows replication in organizational practice, mainly to meet the 2030 agenda on reducing the carbon footprint generated in transport in large cities. Thus, this study can guide companies on structuring the reverse WEEE chain in São Paulo, Brazil for economic and environmental optimization, a relevant aspect considering the exponential generation of WEEE, requiring the implementation of the national solid waste policy, and subsequently the signature of the electronics sector agreement in São Paulo.

Reverse logistic; Reverse Chain; WEEE; Industry 4.0 Technology; Simulation; Artificial intelligence; Eco-efficiency; Circular Economy

Engineering, Industrial and Manufacturing Engineering

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