Tareq Hamadneh1, Khalid Kaabneh2, Omar Alssayed3, Gulnara Bektemyssova4,*, Galymzhan Shaikemelev4, Dauren Umutkulov4, Zoubida Benmamoun5, Zeinab Monrazeri6, Mohammad Dehghani6,*
CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2005-2030, 2024, DOI:10.32604/cmc.2024.052401
Abstract The efficiency of businesses is often hindered by the challenges encountered in traditional Supply Chain Management (SCM), which is characterized by elevated risks due to inadequate accountability and transparency. To address these challenges and improve operations in green manufacturing, optimization algorithms play a crucial role in supporting decision-making processes. In this study, we propose a solution to the green lot size optimization issue by leveraging bio-inspired algorithms, notably the Stork Optimization Algorithm (SOA). The SOA draws inspiration from the hunting and winter migration strategies employed by storks in nature. The theoretical framework of SOA is… More >
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