We consider a multi-stage inventory control problem with nonstationary customer demand under a customer service-level constraint. We propose a multi-agent based model for distributed inventory control systems. In this model, the agent at the first stage is called a retail agent and those at the remaining stages are called supply agents. The retail agent makes an effort to satisfy a target customer service level by adjusting its order release time according to the changes of customer demand trends. On the other hand, each supply agent tries to control its order release time so that product supply from its upstream agent is synchronized with the order request from its downstream agent. A cooperative demand estimation protocol and a distributed action-reward learning technique are developed to satisfy the target customer service level under nonstationary situations. A simulation based experiment was performed to evaluate the performance of the proposed multi-agent model.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Artificial Intelligence