Workload Control in High-Mix-Low-Volume Factories Through the Use of a Multi-Agent System.

Order release in High-Mix-Low-Volume machine environments is often difficult to control due to the high variety of these shops. This paper, therefore, proposes an extension to a Multi-Agent System to control order release. Intelligence is introduced to the agent that is responsible for order release to autonomously learn which jobs to release into the shop through the use of sequencing rules, depending on the current environment. The objective is to minimize the mean weighted tardiness of all jobs. Computational results show that the proposed sequencing rules outperform other more common dispatching rules in terms of mean weighted tardiness. Further analysis of the results also reveals that a more accurate prediction of the lead time of jobs can be made, which is one of the main interests of practitioners in High-Mix-Low-Volume environments.