Manufacturing companies typically use sophisticated production planning
systems optimizing production steps, often delivering near-optimal solutions.
As a downside for delivering a near-optimal schedule, planning systems have
high computational demands resulting in hours of computation. Under normal
circumstances this is not issue if there is enough buffer time before
implementation of the schedule (e.g. at night for the next day). However, in
case of unexpected disruptions such as delayed part deliveries or defectively
manufactured goods, the planned schedule may become invalid and swift
replanning becomes necessary. Such immediate replanning is unsuited for
existing optimal planners due to the computational requirements. This paper
proposes a novel solution that can effectively and efficiently perform
replanning in case of different types of disruptions using an existing plan.
The approach is based on the idea to adhere to the existing schedule as much as
possible, adapting it based on limited local changes. For that purpose an
agent-based scheduling mechanism has been devised, in which agents represent
materials and production sites and use local optimization techniques and
negotiations to generate an adapted (sufficient, but non-optimal) schedule. The
approach has been evaluated using real production data from Huawei, showing
that efficient schedules are produced in short time. The system has been
implemented as proof of concept and is currently reimplemented and transferred
to a production system based on the Jadex agent platform.