not explicitly considered. A mixed integer programming formulation minimizing the (weighted) sum of departure times of the vessels is presented. Some heuristics for a dynamic variant, in which vessel arrival times are uncertain are also proposed. [@peterkofsky1990branch] develop a branch-and-bound algorithm for the same problem that is able to solve larger problem instances.

[@kim2004crane] studies the scheduling of multiple QCs simultaneously operating on a single vessel taking into account precedence constraints between containers and no-passing constraints between QCs. In their setting, a task refers to a “cluster”, where a cluster represents a collection of adjacent slots in a hold and a set of containers to be loaded into/unloaded from these slots. The objective is to minimize a weighted combination of the load/unload completion time of the vessel and the sum of the completion times of the QCs, with higher weight for the load/unload completion time. The sum of the completion times of the QCs is included in the objective to ensure that QCs will be available to load/unload other vessels as early as possible. The problem is modeled as an parallel machine scheduling problem. A MIP formulation is presented and branch-and-bound algorithm is developed for its solution. A greedy randomized 