Flexible Symbiosis for Simulation Optimization in Production Scheduling: A Design Strategy for Adaptive Decision Support in Industry 5.0

In the rapidly evolving landscape of Industry 4.0 and the transition towards Industry 5.0, manufacturing systems face the challenge of adapting to dynamic, hyper-customized demands. Current Simulation Optimization (SO) systems struggle with the flexibility needed for quick reconfiguration, often requiring time-consuming, resource-intensive efforts to develop custom models. To address this limitation, this study introduces an innovative SO design strategy that integrates three flexible simulation modeling techniques—template-based, structural modeling, and parameterization. The goal of this integrated design strategy is to enable the rapid adaptation of SO systems to diverse production environments without extensive re-engineering. The proposed SO versatility is validated across three manufacturing scenarios (flow shop, job shop, and open shop scheduling) using modified benchmark instances from Taillard’s dataset. The results demonstrate notable effectiveness in optimizing production schedules across these diverse scenarios, enhancing decision-making processes, and reducing SO development efforts. Unlike conventional SO system design, the proposed design framework ensures real-time adaptability, making it highly relevant to the dynamic requirements of Industry 5.0. This strategic integration of flexible modeling techniques supports efficient decision support, minimizes SO development time, and reinforces manufacturing resilience, therefore sustaining competitiveness in modern industrial ecosystems.