  In this paper, we study a problem that integrates the vessel scheduling
problem with the berth allocation into a collaborative problem denoted as the
multi-port continuous berth allocation problem (MCBAP). This problem optimizes
the berth allocation of a set of ships simultaneously in multiple ports while
also considering the sailing speed of ships between ports. Due to the highly
combinatorial character of the problem, exact methods struggle to scale to
large-size instances, which points to exploring heuristic methods. We present a
mixed-integer problem formulation for the MCBAP and introduce an adaptive large
neighborhood search (ALNS) algorithm enhanced with a local search procedure to
solve it. The computational results highlight the method's suitability for
larger instances by providing high-quality solutions in short computational
times. Practical insights indicate that the carriers' and terminal operators'
operational costs are impacted in different ways by fuel prices, external ships
at port, and the modeling of a continuous quay.
