A dynamic simulation framework based on hybrid modeling paradigm for parallel scheduling systems in warehouses

Abstract

Efficient warehouse management is of crucial significance for the smooth operation of a company's supply chain. With the challenging nature of warehouse environment changes, research on warehouse operational issues is increasingly important. Moreover, system simulation has emerged as a prevalent means of investigating warehouse operational management. However, prior research on warehouse simulation either utilized singular paradigms or lacked a generalized modeling framework. This remains a challenge for modelers exploring diverse domains of warehouse-related issues using simulation techniques. In this context, this study presents an integrated control methodology(ICM) based on the state changes of dispatchers and logistics equipments, the discrimination of task scenarios, and the behaviors of dispatchers. This methodology is incorporated into the warehouse workflow model. The workflow model serves as a conceptual abstraction of a warehouse's parallel scheduling system, while the integrated control methodology (ICM) simulates the entire decision-making process of dispatchers to resolve potential deadlock issues during task execution. Subsequently, we utilize a steel slab warehouse in a case study, employing a dynamic simulation using a hybrid paradigm based on Discrete Event Simulation (DES) and Agent-Based Simulation (ABS) to replicate the historical scheduling process within the warehouse. This demonstration confirms the feasibility of the proposed framework. Finally, we devise multiple dimensions of validation metrics to confirm the model's effectiveness.