Abstract: The effective management of end-of-life products, whether through recycling or incineration for electricity generation, holds pivotal significance amidst escalating concerns over economic, environmental, and social ramifications. While the economic and environmental dimensions often receive primary focus, the social aspect remains comparatively neglected within sustainability discourse. This paper undertakes a comprehensive exploration of the positive social impacts engendered by medical waste recycling, with a specific focus on job creation and economic value enhancement. The principal aim of this research is to highlight the social benefits derived from medical waste recycling, elucidating its role in fostering employment opportunities, and augmenting economic prosperity. By employing a Genetic Artificial Bee Colony algorithm, this study addresses two mathematical problems pertinent to optimizing recycling processes, thereby contributing to the advancement of sustainable waste management practices. Additionally, the proposed algorithm exhibits superior performance, highlighting its potential in addressing sustainability challenges. Ultimately, integrating the social dimension into end-of-life product management discussions can lead to a more comprehensive approach to sustainability, balancing environmental preservation with socio-economic progress.

El Liazidi Sara and Dkhissi Btissam, “A Genetic Artificial Bee Colony Algorithm for Investigating Job Creation and Economic Enhancement in Medical Waste Recycling” International Journal of Advanced Computer Science and Applications(IJACSA), 15(4), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0150439

@article{Sara2024,
title = {A Genetic Artificial Bee Colony Algorithm for Investigating Job Creation and Economic Enhancement in Medical Waste Recycling},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150439},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150439},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {4},
author = {El Liazidi Sara and Dkhissi Btissam}
}