Supply chain management using an optimization driven simulation approach

In this work, we propose a hybrid simulation-based optimization framework to solve the supply chain management problem. The hybrid approach combines a mathematical programming model with an agent-based simulation model and uses them in an iterative framework. The optimization model is used to guide the decisions toward an optimal allocation of resources given the realistic supply chain representation given by the simulation. Thus, the proposed approach provides a more realistic solution compared to a stand-alone optimization model, often a simplified representation of the actual system, by making use of the simulation model, which captures the detailed dynamic behavior of the system. A multiobjective problem has been formulated by taking into consideration the environmental impact of supply chain operations. The proposed framework has been applied to small-scale case studies to study the effectiveness of the approach for such problems.