In this work we present a genetic algorithm (GA), to address the imprecision occurring in the berth allocation problem (BAP) and the quay crane assignment problem (QCAP). The BAP + QCAP is an NP-hard problem of combinatorial optimization. The arrival imprecision in the vessels are represented by fuzzy triangular numbers. The fuzzy model and the GA obtain robust berthing plans, which assign quay cranes to each incoming vessel. Also, the plans support early and late arrivals of vessels. To compare the efficiency of the fuzzy model and GA, instances of 5 to 50 vessels were used. The fuzzy model implemented in CPLEX, obtained optimal and non-optimal solutions for small and medium instances, respectively whereas for large instances, solutions were not found in the defined runtime period. In contrast, the GA implemented in C++ obtained a good solution for all the instances in less time.