In decentralized manufacturing environment with multiple factories that are
scattered geographically, the complexity of production systems increases, and
capacity planning and allocation of resources have become a significant concern
that affects system performances. This study focuses on the development of an
integrated framework to allocate limited budget in a multiple-factory
environment. We develop a negotiation framework with learning mechanism to
allocate autonomously finite budget provided by a headquarter and to facilitate the
use of limited manufacturing resources that are scattered over individual factories.
The outcome of the experiments shows good prediction of the opponent offers
during negotiation, so it enables the reduction of negotiation time
