Large costs arise at a seaport container terminal from the duration of the unloading of vessels and from the time a vessel is waiting to be unloaded. The optimal allocation of vessels to berth space (Berth Allocation Problem) becomes more and more important as its solution is also input to further terminal decision problems. We compare solutions for a realistic data Berth Allocation Problem found by a Composite Heuristic combining a tree search procedure and a pair-wise exchange heuristic with two metaheuristics. We apply Genetic Algorithms as it is widely used and flexible in adaption with promising results in logistics applications and propose a modified Particle Swarm Optimization for combinatorial optimiza- tion.
['Ole Björn Brodersen', 'Leif Meier', 'Matthias Schumann']
Optimizing the Berth Allocation Problem using a Genetic Algorithm and Particle Swarm Optimization