Modeling and performance evaluation of an agent-based warehouse dynamic resource allocation using Colored Petri Nets

High accuracy modeling plays an important role for the optimization of planning and control in the supply chain members. Agent-based planning and control systems are efficient in representing intelligent manufacturing systems to achieve decision robustness. The purpose of this paper is to combine Colored Petri Nets (CPNs) with an agent-based warehouse control system in order to model the system, evaluate petri net related system properties, and evaluate system performance. A dynamic resource allocation of an order-picking process is presented as a case study to illustrate the applicability of the method. A hierarchical timed CPN (CTPN) model has been implemented. Simulation and state space results are used to identify system properties and evaluate performance.