Dynamic Assignation of Roles and Tasks in Virtual Organizations of Agents

Abstract

Nowadays, a common problem that affects the workflow and the results of an entity is the planning and distribution of tasks. Doing this manually implies anticipate workloads and employee characteristics, which is inefficient and almost uncalculated in high dynamic environments. In this paper, a model that generates a planning of tasks, minimizing the resources necessary for its accomplishment and obtains the maximum benefits is presented. Within this proposal, genetic algorithms, queuing theory, and CBR are used in different stages to obtain an efficient distribution. To test the system, the chosen case study that fits the scenario, is the e-Government where an elevated number of tasks must be solved in a precise term using the minimal resources.