Orientador(es)
Resumo(s)
Nowadays, systems are becoming increasingly complex, mainly due to an exponential increase in the number of entities and their interconnections. Examples of these complex systems can be found in manufacturing, smart-grids, traffic control, logistics, economics and biology, among others. Due to this complexity, particularly in manufacturing, a lack of responsiveness in coping with demand for higher quality products, the drastic reduction in product lifecycles and the increasing need for product customization are being observed. Traditional solutions, based on central monolithic control structures, are becoming obsolete as they are not suitable for reacting and adapting to these perturbations. The decentralization of the complexity problem through simple, intelligent and autonomous entities, such as those found in multi-agent systems, is seen as a suitable methodology for tackling this challenge in industrial scenarios. Additionally, the use of biologically inspired self-organization concepts has proved to be suitable for being embedded in these approaches enabling better performances to be achieved. According to these principals, several approaches have been proposed but none can be truly embedded and extract all the potential of self-organization mechanisms. This paper proposes an evolution to the ADACOR holonic control architecture inspired by biological and evolutionary theories. In particular, a two-dimension al self-organization mechanism was designed taking the behavioural and structural vectors into consideration, thus allowing truly evolutionary and reconfigurable systems to be achieved that can cope with emergent requirements. The approach proposed is validated with two simulation use cases.
Descrição
Palavras-chave
Evolutionary systems Holonic manufacturing systems Multi-agent systems Self-organization
Contexto Educativo
Citação
Barbosa, José; Leitão, Paulo; Adam, Emmanuel; Trentesaux, Damien (2015). Dynamic self-organization in holonic multi-agent manufacturing systems: The ADACOR evolution. Computers in Industry. ISSN 0166-3615. 66,p. 99-111