Holonic and Multi-Agent Systems for Manufacturing. Proceedings of the 4th Int. Conf. on Industrial Applications of Holonic and Multi-Agent Systems, HoloMAS 2009, Linz, Austria, August 31-September 2, 2009. Marìk, V., Strasser, T. and Zoitl, A., Eds., LNCS, 2009
In this paper, the static layout of a traditional multi-machine factory producing a set of distin... more In this paper, the static layout of a traditional multi-machine factory producing a set of distinct goods is integrated with a set of mobile production units - robots. The robots dynamically change their work position to increment the product rate of the different typologies of products in respect to the fluctuations of the demands and production costs during a given time horizon. Assuming that the planning time horizon is subdivided into a finite number of time periods, this particularly flexible layout requires the definition and the solution of a complex scheduling problem, involving for each period of the planning time horizon, the determination of the position of the robots, i.e., the assignment to the respective tasks in order to minimize production costs given the product demand rates during the planning time horizon.
We propose a decentralized multi-agent system (MAS) scheduling model with as many agents as there are the tasks in the system, plus a resource (robot) owner which assigns the robots to the tasks in each time period on the basis of the requests coming from the competing task agents. The MAS model is coupled with an iterative auction based negotiation protocol to coordinate the agents’ decisions. The resource prices are updated using a strategy inspired by the subgradient technique used in the Lagrangian relaxation approach. To measure the effectiveness of the results, the same are evaluated in respect to that of the benchmark centralized model.
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Papers by Marin Lujak
and formal approaches for defining agent organisations in an explicit way. Since artificial institutions can be seen as a regulative layer for agent organisations, a review of recent approaches of this issue will be also included. Moreover, there have been some recent approaches for making agents that might be capable of understanding the organisation structure and functionality and then being able for deciding whether participate inside or even to decide new structures for the organisation. A review of this kind of agents, known as organisation-aware agents, will be provided. Finally, an important question in open systems is how to endow an organisation with autonomic capabilities to yield a dynamical answer to changing circumstances. Thus, a review of methods for designing and/or implementing adaptive agent organisations will be given.
We propose a decentralized multi-agent system (MAS) scheduling model with as many agents as there are the tasks in the system, plus a resource (robot) owner which assigns the robots to the tasks in each time period on the basis of the requests coming from the competing task agents. The MAS model is coupled with an iterative auction based negotiation protocol to coordinate the agents’ decisions. The resource prices are updated using a strategy inspired by the subgradient technique used in the Lagrangian relaxation approach. To measure the effectiveness of the results, the same are evaluated in respect to that of the benchmark centralized model.
and formal approaches for defining agent organisations in an explicit way. Since artificial institutions can be seen as a regulative layer for agent organisations, a review of recent approaches of this issue will be also included. Moreover, there have been some recent approaches for making agents that might be capable of understanding the organisation structure and functionality and then being able for deciding whether participate inside or even to decide new structures for the organisation. A review of this kind of agents, known as organisation-aware agents, will be provided. Finally, an important question in open systems is how to endow an organisation with autonomic capabilities to yield a dynamical answer to changing circumstances. Thus, a review of methods for designing and/or implementing adaptive agent organisations will be given.
We propose a decentralized multi-agent system (MAS) scheduling model with as many agents as there are the tasks in the system, plus a resource (robot) owner which assigns the robots to the tasks in each time period on the basis of the requests coming from the competing task agents. The MAS model is coupled with an iterative auction based negotiation protocol to coordinate the agents’ decisions. The resource prices are updated using a strategy inspired by the subgradient technique used in the Lagrangian relaxation approach. To measure the effectiveness of the results, the same are evaluated in respect to that of the benchmark centralized model.