A novel object-oriented Petri net framework with logic programming for discrete and continuous event simulations

Abstract

This paper introduces a novel simulation modeling framework that seamlessly integrates Petri nets with logic programming, resulting in intelligent and adaptable simulation models capable of handling both discrete and continuous events. Instead of treating systems as standalone Petri nets, this methodology embeds Petri net semantics within simulation models, creating a hybrid state vector that incorporates attributes from both the Petri net and model-specific states. In addition, the modular design of the model supports high reusability and scalability, making it applicable across various domains, including industrial automation and workflow management. Embedding Petri nets within simulation entities enhances dynamic decision-making and specialized time-management capabilities. This approach reduces errors associated with fixed time-step sizes, thereby improving the accuracy of continuous event simulations. The solution introduces the external transition concept for Petri nets and implements a time-management approach based on qualitative landmarks and mathematically meaningful points, effectively minimizing errors caused by simulation time-step variations. To demonstrate the framework's versatility and effectiveness, six example applications illustrate how combining Petri nets with logic programming enhances the analytical power and flexibility of traditional simulation models. Ultimately, this paper establishes a comprehensive hybrid simulation framework that unifies discrete and continuous analysis, endows simulation entities with reasoning capabilities through logic programming, and provides robust modularity.