A resilient optimization methodology for integrated workforce scheduling and system configuration in manufacturing

Scheduling and configuration problems in manufacturing systems are frequently viewed as separate entities, despite their interconnectedness. This research delves into intricate scheduling management, proposing a model that augments performance through optimization. Effective optimization necessitates evaluating system performance, but intricate scheduling impedes this process. Conventional methods often fail to provide insightful analysis of the system. This study introduces a model capable of generating response curves, thereby unveiling system behaviors influenced by configuration and scheduling. The methodology is validated through the application of a specific scheduler and demonstrated in a footwear case study, highlighting its practical relevance and potential for long-term decision-making.