Workflows in Constructions Modelled with Stochastic Artificial Social Systems

Abstract

This paper focuses on evaluation of the performance characteristics of workflows in constructions modeled with stochastic Petri nets (SPN). This goal is achieved by focusing on a new model for Artificial Social Systems (ASS) behaviors. ASS exists in practically every multi-agent system, and play a major role in the performance and effectiveness of the agents. This is the reason why we introduce a more suggestive model for ASS. To model these systems, a class of Petri nets is adopted, and briefly introduced in the paper. This class allows representing the flow of physical resources and control information data of the ASS's components. In the analysis of SPN we use simulations in respect to timing parameters in a generalized semi-Markov process (GSMP). By using existing results on perturbation (e.g., delays in supply with raw materials, derangements of equipments, etc.) analysis and by extending them to new physical interpretations we address unbiased sensitivity estimators correlated with practical solutions in order to attenuate the perturbations. An important advantage of this approach is that one simulation is needed for evaluating the stochastic Petri nets and the perturbation analysis and to take advantage of the state of the art.