Artificial Fish School Algorithm Applied in a Combinatorial Optimization Problem

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Yun Cai 1,*

1. Wuhan University of Science and Technology/Country College of Machinery and Automation, Wuhan, China

* Corresponding author.


Received: 20 Feb. 2010 / Revised: 23 May 2010 / Accepted: 1 Sep. 2010 / Published: 8 Nov. 2010

Index Terms

Combinatorial optimization, berth allocation, scheduling, artificial fish swarm algorithm


An improved artificial fish swarm algorithm (AFSA) for solving a combinatorial optimization problem—a berth allocation problem (BAP), which was formulated. Its objective is to minimize the turnaround time of vessels at container terminals so as to improve operation efficiency customer satisfaction. An adaptive artificial fish swarm algorithm 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 verified the validity and feasibility of the proposed algorithm with rational parameters, and show that the algorithm has better convergence performance than genetic algorithm (GA) and ant colony optimization (ACO).

Cite This Paper

Yun Cai,"Artificial Fish School Algorithm Applied in a Combinatorial Optimization Problem“, International Journal of Intelligent Systems and Applications(IJISA), vol.2, no.1, pp.37-43, 2010. DOI: 10.5815/ijisa.2010.01.06


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