Abstract
<p class="Resumo">A realização das atividades de transporte comumente envolve diferentes atores e veículos dispersos numa rede, de forma que responder aos eventos dinâmicos presentes nas operações é uma tarefa complexa. Neste contexto, o uso de sistemas baseados em agentes (MAS) na tomada de decisões autônoma tem se mostrado potencialmente interessante e sido discutido na literatura recente. Neste artigo, é apresentado um sistema baseado em agentes para lidar com o problema de roteirização dinâmica de veículos, mais precisamente em um problema de coleta de peças e componentes, onde parte das tarefas previamente alocadas ao veículo pode ser eventualmente transferida para outros veículos, sempre que o MAS constatar que o tempo de ciclo pode exceder o limite diário da jornada de trabalho. A transferência das tarefas entre agentes é realizada através do método de negociação de Vickrey. O sistema proposto permite tomada de decisão de forma colaborativa entre os agentes envolvidos, permitindo a realização de ajustes durante a realização da rota inicial.</p>
Highlights
The proper planning and operation of logistics processes is a complex task, which becomes harder when dynamic aspects of logistics operations are taken into account
The use of autonomous agents is suitable for collaborative decision making in many situations, especially when integrated production and transportation activity management is necessary
Planning and performing pick-up activities of parts and components from different suppliers to an Original Equipment Manufacturer (OEM) has an effect on inbound logistics performance, and on production activities
Summary
The proper planning and operation of logistics processes is a complex task, which becomes harder when dynamic aspects of logistics operations are taken into account. Davidsson et al (2005) in their bibliographic review identified that agent technology has been applied to many different problem areas within transport logistics Often these agent approaches are distributed and very complex in nature, including planning and scheduling, fleet management, transport scheduling, traffic management, and traffic control. With regard to the integrated industrial programming of production, component, and manufactured product transportation, existing models are deterministic and static in nature (Chen, 2010), i.e. all relevant parameters are known a priori Such systems usually operate in dynamic environments, where events are often unpredictable and end up causing emergency changes to previously optimized plans
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