Cutting-edge optimization methods for sustainable and resilient supply chains - Fauziah, Sifa; Colicchia, Cagno Stone; Blackhurst, Alcívar; Sihotang, Jonhariono (Jurnal Matematika Dan Ilmu Pengetahuan Alam LLDikti Wilayah 1 (JUMPA), 2024)
This research develops a comprehensive multi-objective optimization framework for sustainable and resilient supply chains, integrating cost efficiency, sustainability, and resilience into a unified model. The study advances traditional supply chain optimization, which often prioritizes singular objectives, by presenting a robust mathematical formulation that balances production, transportation, sustainability, and resilience investments. A numerical example demonstrates the model's practical application, highlighting key findings such as the ability to achieve cost efficiency while reducing environmental impact and enhancing supply chain robustness through moderate resilience investments. The research makes significant contributions by introducing a holistic approach to supply chain management, offering a practical tool for decision-makers. However, the model's complexity and reliance on accurate data present implementation challenges. Future research opportunities include incorporating non-linear relationships, applying advanced optimization techniques, and customizing the model for specific industries. This study underscores the importance of an integrated approach to supply chain optimization, providing a foundation for developing supply chains that are efficient, sustainable, and resilient in an increasingly dynamic global environment.