Enhancing supply chain management in the physical internet: a hybrid SAGA approach

Abstract

Abstract This paper introduces an advanced inventory replenishment optimization approach tailored for the Physical Internet (PI), addressing the dynamic and complex nature of this environment. We propose a hybrid Simulated Annealing–Genetic Algorithm (SA–GA), engineered to optimize the balance between exploration and exploitation, ensuring adaptability and efficiency in a variety of PI contexts. The study also presents an enriched mathematical model integrating dynamic demand, and multi-objective optimization. The SA–GA algorithm emerges as a novel contribution, characterized by its computational efficiency and adaptability, marking an advancement in PI inventory management. The incorporation of real-time data analytics in our dynamic inventory replenishment strategy enhances adaptability and responsiveness, while the robust mathematical model offers a versatile tool for both theoretical analysis and practical application. Collectively, these innovations help bridge existing gaps in PI inventory management and serve as a reference for other similar studies.