ANALYZING QUAY CRANES JOB SEQUENCE USING STOCHASTIC PROJECT SCHEDULING TECHNIQUE

Abstract

In this thesis, we studied the vessel transshipment problem in the container terminal with uncertainty. Our objective is to find an effective method to estimate the transshipment time of a vessel, which is defined as the total time for the terminal to load and unload the vessel, considering the uncertainty of the truck™s travel time and the queuing time of trucks at the yard side. We model this problem as the project management problem, and apply the persistency model to address the uncertainty issue. We first consider the uncertainty in the truck™s travel time only, and use the persistency model to compute the criticality of each job. We then solve the crashing problem for a given number of extra trucks. Next, we consider the queuing of trucks at the yard side, and develop a method to measure the queuing delay for each job by analyzing the structure of the entire job sequence. The queuing delay is incorporated into the mean and variance of the service time of the job, which leads to a better estimation of the vessel™s transshipment time. We have tested our models with a small test case as well as a large test case, which is extracted from real past data of a local port. Experimental results show that our model gives a very promising estimation of the transshipment time, which is very close to the actual transshipment time. We also conduct sensitivity analysis for various factors to help the terminal to identify important factors that could potentially lead to significant reduction in the transshipment time.