Simulation Optimization for Supply Chain Decision Making

Supply chain design and optimization have been a subject of interest for academia and industry alike. We focus on stochastic and hybrid models in this paper since they closely approximate reality. This paper explains the structure of supply chains, decisions required to be taken in a typical supply chain, and models developed for supply chain design and optimization. The paper further explores optimization via simulation to solve stochastic and hybrid models, its applications in the supply chain domain and future research directions arising out of recent emphasis on sustainability, robustness and resilience of supply chains and the opportunities offered by advances in Industry 4.0, Machine Learning and Big Data.