Dynamic model of distribution and organization of activities in multi-agent systems

Abstract

Currently, the allocation of tasks is a problem in many different areas such as e-Goverment. Traditionally, the assignment is done manually; therefore it is necessary to anticipate workloads and employee characteristics. This article describes a system based on virtual organizations of agents that allows recommendations about planning of tasks to minimize the resources necessary for their accomplishment and to obtain the maximum profit. For this purpose, a hybrid artificial intelligence system with genetic algorithm, queuing theory and case-based reasoning is used to obtain an efficient distribution. The final part of the article is focused on validating the plan developed inside a case of study centered in the e-Government in order to obtain empirical results.