Coalitions in coordinated multi-agent production scheduling: A computational study

Abstract

This paper studies distributed production scheduling where agents control dispersed information and decentralized decision authority. Using the classical job shop scheduling model, the effects of coalition formation and local communication in an iterative auction are studied. The case is investigated where job agents are allowed to form coalitions, where coalition members share private information and resolve resource conflicts among themselves, while intercoalition communication is limited to bidding. The computational study shows that when the size, type, and timing of the coalitions are properly determined, it is possible to produce a high-quality schedule with a reasonable number of iterations. The results show further improvement in convergence and in solution quality when coalition size and update frequency increase. However, these improvements show diminishing return; thus, it is concluded that a high-quality schedule can be achieved with manageable coalition sizes and a moderate level of information sharing.