Optimizing Berth Allocation by an Artificial Fish Swarm Algorithm

Abstract

In order to improve operation efficiency and customer satisfaction and to minimize the turnaround time of vessels at container terminals, a berth allocation problem (BAP) was formulated. An adaptive artificial fish swarm algorithm (AFSA) was proposed to solve it. Firstly, the basic principle and the algorithm design of the AFSA were introduced. Then, for a test case, computational experiments explored the effect of algorithm parameters on the convergence of the algorithm. Experimental results show that the algorithm has better convergence performance than genetic algorithm (GA) and ant colony optimization (ACO). The improved algorithm with rational parameters can effectively solve the BAP.