A GLOBAL AND LOCAL SEARCH APPROACH TO QUAY CRANE SCHEDULING PROBLEM

The container flow in terminals at a port is often bottlenecked due to the slow operations of the quay cranes in a scarce terminal land space. The quay crane scheduling problem (QCSP) is a major problem because of the assignment of expensive quay cranes to multiple vessel-holds for container discharging and loading operation. This paper presents a hybrid QCSP Solver, which combines genetic algorithms for global search with steepest ascent hill climbing for local search. Numerical experiments are performed with small- and large-sized random QCSP instances. The experimental results revealed that the hybrid QCSP Solver provides a better solution than the stand-alone QCSP Solver. By scheduling the dynamic operation of quay cranes it is expected that the developed decision making tool will provide terminal planners with a guideline to enhancing the assignment of quay cranes to a vessel.