A simulation–optimization approach for capacitated lot-sizing in a multi-level pharmaceutical tablets manufacturing process
提出一种迭代仿真优化方法，解决多级药片制造中基于概率需求的产能约束批量问题，并与两阶段随机规划方法对比，给出管理启示。
This paper discusses an iterative simulation–optimization approach to estimate high-quality solutions for the multi-level capacitated lot-sizing problem with linked lot sizes and backorders (MLCLSP-L-B) based on probabilistic demand. It presents the application of the Generalized Uncertainty Framework (GUF) to the MLCLSP-L-B. The research provides an exact mathematical problem formulation and a variable neighborhood search (VNS) algorithm for the GUF. The evaluation procedure uses anonymized real-world data of multi-level pharmaceutical tablets manufacturing processes. It compares the GUF against a two-stage stochastic programming (SP) approach from the literature regarding manufacturing costs and customer service levels. Finally, planning rules and managerial insights are given for the tablets manufacturing processes. • Apply GUF approach and VNS algorithm on MLCLSP-L-B problem instances. • Extension of VNS algorithm by multi-level product interdependencies. • Execute numerical experiments with real-world tablets manufacturing data. • Benchmark the GUF against the two-stage stochastic programming approach SMLCLSP-L-B. • Deviation of managerial insights based on numerical experiments.