| Summary: | Based on Logic Time Petri nets (LTPNs) models, this paper focuses on improving the efficiency of Petri Net intelligent search method execution. With an analysis of the E-Commerce Logistics (ECL) system, the method of system scheduling using LTPNs is studied, and the Ant Colony algorithm is proposed based on it. By introducing the concept of pheromones to system transition, using the Ant Colony algorithm (ACA) in the processing of the network, and setting the heuristic factor in combination with the time boundary, the non-deterministic behavior can be automatically analyzed and selected in the LTPNs so that the efficiency of control and scheduling during the system dynamics operation is improved. The result of the analysis of the ECL system serves as evidence of the superiority of ACA.
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