Robust mathematical model for supply chain optimization: A comprehensive study - Lise Pujiastuti; Mochamad Wahyudi; Barreto Jose da Conceição; Fristi Riandari (Institute of Computer Science (IOCS), 2023)
This research provides a comprehensive review of existing literature and research on supply chain optimization, aiming to capture the advances made in the field and identify emerging perspectives. Supply chain optimization plays a vital role in improving operational efficiency, reducing costs, and enhancing customer satisfaction. By analyzing a wide range of studies, this review examines various approaches, models, and techniques used in supply chain optimization, including mathematical programming, stochastic programming, simulation, and metaheuristic algorithms. The review also encompasses key aspects such as demand forecasting, inventory management, production planning, transportation, and distribution network design. Furthermore, the study investigates recent trends, such as incorporating sustainability considerations, addressing uncertainties and risks, and utilizing real-time data and decision support systems. By identifying the gaps and limitations in the existing research, this review sets the stage for future investigations and provides valuable insights for researchers and practitioners seeking to advance supply chain optimization efforts. The findings of this review contribute to enhancing the understanding of supply chain optimization and provide a roadmap for future research directions in this dynamic and critical field