Container Terminal Berth-Quay Crane Capacity Planning Based on Markov Chain

Abstract

This paper constructs a berth-quay crane capacity planning model with the lowest average daily cost in the container terminal, and analyzes the influence of the number of berths and quay cranes on the terminal operation. The object of berth-quay crane capacity planning is to optimize the number of berths and quay cranes to maximize the benefits of the container terminal. A steady state probability transfer model based on Markov chain for container terminal is constructed by the historical time series of the queuing process. The current minimum time operation principle (MTOP) strategy is proposed to correct the state transition probability of the Markov chain due to the characteristics of the quay crane movement to change the service capacity of a single berth. The solution error is reduced from 7.03% to 0.65% compared to the queuing theory without considering the quay crane movement, which provides a basis for the accurate solution of the berth-quay crane capacity planning model. The proposed berth-quay crane capacity planning model is validated by two container terminal examples, and the results show that the model can greatly guide the container terminal berth-quay crane planning.

HUs Fleet Management in an Automated Container Port: Assessment by a Simulation Approach

“…The strategic level includes all the decisions usually adopted in the initial design phase of a new structure, or an extension of an existing port or conversion [45][46][47][48][49][50]. These kinds of problems involve high investments; therefore, the choices made are not changed over short time horizons.…”