We describe a novel approach to scheduling resolution by combining
Autonomic Computing (AC), Multi-Agent Systems (MAS) and Nature Inspired
Optimization Techniques (NIT). Autonomic Computing has emerged as paradigm
aiming at embedding applications with a management structure similar to a central
nervous system. A natural Autonomic Computing evolution in relation to Current
Computing is to provide systems with Self-Managing ability with a minimum human
interference. In this paper we envisage the use of Multi-Agent Systems paradigm
for supporting dynamic and distributed scheduling in Manufacturing Systems
with Autonomic properties, in order to reduce the complexity of managing
systems and human interference. Additionally, we consider the resolution of realistic
problems. The scheduling of a Cutting and Treatment Stainless Steel Sheet
Line will be evaluated. Results show that proposed approach has advantages when
compared with other scheduling systems
