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首页> 外文期刊>Journal of Computers >Task Schedulable Problem and Maximum Scheduling Problem in a Multi-agent System
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Task Schedulable Problem and Maximum Scheduling Problem in a Multi-agent System

机译：多智能体系统中的任务可调度问题和最大调度问题

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Tasks scheduling is a key problem in multi-agent system, traditional tasks scheduling methods can’t be applied to new application areas of the MAS such as emergency system. In order to apply the Agent method to these new areas, a multi-agent system model is built in this paper, and corresponding task schedulable problem and maximum scheduling problem are defined based on this multi-agent system model. Task schedulable problem is modeled using flow network, and it is proved that maximum flow algorithm can be used to solve such problem, which means the problem can be solved in polynomial time. Furthermore, by analyzing the flow network model, a necessary and sufficient condition which can be used to determine whether tasks can be scheduled is gained and proved. Three approximation algorithms have been proposed to solve the maximum scheduling problem. The experiment results show that all above algorithms can get pretty solutions in solving maximum scheduling problem, and the approximation ratio for optimal solution of these approximation algorithms are all larger than or equal to 0.5 even though the resource ratio is very low.
机译：任务调度是多Agent系统中的关键问题，传统的任务调度方法无法应用于MAS的新应用领域，例如应急系统。为了将Agent方法应用于这些新领域，本文建立了一个多Agent系统模型，并在此多Agent系统模型的基础上定义了相应的任务可调度问题和最大调度问题。利用流网络对任务可调度问题进行建模，证明可以使用最大流算法来解决该问题，这意味着该问题可以在多项式时间内得到解决。此外，通过分析流网络模型，获得并证明了可用于确定任务是否可以调度的充要条件。提出了三种近似算法来解决最大调度问题。实验结果表明，上述所有算法都能很好地解决最大调度问题，即使资源比很低，这些近似算法的最优解近似率也都大于或等于0.5。

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