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Policy-Combination Oriented Optimization for Supply Chain Simulation

Supply chain simulation is able to capture the dynamics and uncertainties in all kinds of supply chains and provide quantitative performance evaluations. In order to address the time consuming evaluation and large search space issues in supply chain simulation, this paper proposes a policy-combination oriented optimization approach to conduct decision makings. The approach begins with reducing the search space by relaxing the goal of optimization, and then refers to meta-heuristic searching methods to solve the main bi-level optimization problem. Lastly the key parameters are fine-tuned with what-if analysis. A case study demonstrates the effectiveness and efficiency of the proposed approach, and compares it with other alternative approaches available in practice.