A two-level stochastic model to estimate vessel throughput time

Abstract

A good estimate of the vessel sojourn time is essential for better planning and scheduling Of container terminal resources,such as berth scheduling,quay crane(qc)assignment And scheduling,and fleet size planning. However,estimating the expected vessel so journ Time is a complex exercise because the time is dependent on several terminal operating Parameters such as the size of the vessel,the number of containers to be loaded and Unloaded,and the through put of the qcs. The through put of the qcs in turn depends On the type and number of transport vehicles,number of stack blocks,the topology of The vehicle travel path,the layout of the terminal,and several event uncertainties. To Address the modelling complexity, we propose a two-level stochastic model to estimate The expected vessel so journ time. The higher level model consists of a continuous-time Markovchain(ctmc)that captures the effect of qc assignment and scheduling on vessel Sojourn time. The lower level model is a multi class closed queuing network(cqn)that Models the dynamic interactions among the terminal resources and provides an estimate Of the transition rate input parameters to the higher level ctmc model. We estimate the Expected vessel sojourn times for several container load and unload profiles and discuss The effect of terminal layout parameters on vessel so journ times.