Schedule Optimization of Time Petri Nets Based on Ant Colony Systems

Abstract

This paper presents a time Petri net model with the optimizing mechanism based on ant colony systems that addresses the problem of schedule optimization. The choice rules and pheromone update rules of artificial ants are embedded into the evolution rules of a time Petri net, so the modeling and scheduling analysis of real systems can be integrated into the same model. Compared with the approaches based on the heuristic search and genetic algorithms, our method efficiently unifies the modeling and analysis of schedule problems based on a time Petri net.