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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Optimizing Berth Allocation by an Artificial Fish Swarm Algorithm


    Contributors:
    Yun Cai, (author) / Yongzhong Huo, (author) / Meng Yu, (author)


    Publication date :

    2010-11-01


    Size :

    235283 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Optimizing Multi-Quay Berth Allocation using the Cuckoo Search Algorithm

    Aslam, Sheraz / Michaelides, Michalis P. / Herodotou, Herodotos | TIBKAT | 2022

    Free access


    Simulated Annealing Algorithm for Berth Allocation Problems

    Line, Shih-Wei / Ting, Ching-Jung | Springer Verlag | 2013


    Enhanced Berth Allocation Using the Cuckoo Search Algorithm

    Aslam, Sheraz / Michaelides, Michalis P. / Herodotou, Herodotos | Springer Verlag | 2022