The punctuality of containerships has become the prevalent issue in container liner shipping operations, as the on-time arrival of a containership at the next port of call is paramount. When a delay occurs at the previous port of call, it may also cause a delay at the next port of call. This paper proposes a departure punctuality model of analysis. This model employs a Fuzzy Rule-Based Bayesian Belief Network (FRBBN) for predicting the departure punctuality of a containership. To ensure the reliability of the model, two containerships were tested. The results show that the prediction values from the model are between 95.6% and 99% accurate provided that no tactical strategy is implemented during the voyage. In addition, the most significant factors that determine the punctuality of departure were found to be punctuality of arrival at the same (base) port prior to departure, dangerous events and other unexpected delays during the port stay. It is expected that this model is capable of helping researchers and practitioners to understand the influence of the dynamic environment and to make predictions on the departure punctuality of containerships.

Abstract
1. Introduction
2. Literature Review
    2.1. Fuzzy Rule-Based Bayesian Belief Network (FRBBN)
3. Methodology
4. Test Case
    4.1. Identifying the Critical Influential Factors
    4.2. Defining the States of the Nodes
    4.3. Developing a Model for Departure Punctuality
    4.4. Determining the Conditional Probabilities
    4.5. Determining the Unconditional Probabilities
    4.6. Validating the Model and Results (Step 6)
5. Result and Discussions
6. Conclusions
Reference

• N. H. MOHD SALLEH(School of Maritime Business and Management, Universiti Malaysia Terengganu)
• A. H. SAHARUDDIN(School of Maritime Business and Management, Universiti Malaysia Terengganu) Corresponding Author