  This paper addresses the optimization of container unloading and loading
operations at ports, integrating quay-crane dual-cycling with dockyard rehandle
minimization. We present a unified model encompassing both operations: ship
container unloading and loading by quay crane, and the other is reducing
dockyard rehandles while loading the ship. We recognize that optimizing one
aspect in isolation can lead to suboptimal outcomes due to interdependencies.
Specifically, optimizing unloading sequences for minimal operation time may
inadvertently increase dockyard rehandles during loading and vice versa. To
address this NP-hard problem, we propose a hybrid genetic algorithm (GA)
QCDC-DR-GA comprising one-dimensional and two-dimensional GA components. Our
model, QCDC-DR-GA, consistently outperforms four state-of-the-art methods in
maximizing dual cycles and minimizing dockyard rehandles. Compared to those
methods, it reduced 15-20% of total operation time for large vessels.
Statistical validation through a two-tailed paired t-test confirms the
superiority of QCDC-DR-GA at a 5% significance level. The approach effectively
combines QCDC optimization with dockyard rehandle minimization, optimizing the
total unloading-loading time. Results underscore the inefficiency of separately
optimizing QCDC and dockyard rehandles. Fragmented approaches, such as QCDC
Scheduling Optimized by bi-level GA and GA-ILSRS (Scenario 2), show limited
improvement compared to QCDC-DR-GA. As in GA-ILSRS (Scenario 1), neglecting
dual-cycle optimization leads to inferior performance than QCDC-DR-GA. This
emphasizes the necessity of simultaneously considering both aspects for optimal
resource utilization and overall operational efficiency.
