Modeling and Analysis for Uncertainty in Logistic Chains Based on Logical Time Petri Nets

Abstract

A present logistic chain is a cooperative system with multiple partners. Batch processing function and passing value uncertainty are two important properties, and time-related schedulability analysis is key for improving efficiency of business operations in a cooperative logistic chain system. A logical time Petri net is proposed in order to model and analyze time-related property, batch processing function and passing value uncertainty in logistic chains. The analysis methods are presented for calculating time-related property for different types of transitions such as logical input transitions, logical output transitions and traditional transitions. An example of a logistic chain is given to illustrate the use of the proposed methods.