Artificial Fish School Algorithm Applied in a Combinatorial Optimization Problem

Автор: Yun Cai

Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa

Статья в выпуске: 1 vol.2, 2010 года.

Бесплатный доступ

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).

Еще

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

Короткий адрес: https://sciup.org/15010138

IDR: 15010138

Список литературы Artificial Fish School Algorithm Applied in a Combinatorial Optimization Problem

  • P. Surekha, P.R.A. Mohana Raajan, and S.Sumathi, “Genetic Algorithm and Particle Swarm Optimization approaches to solve combinatorial job shop scheduling problems,”2010 IEEE International Conference on Computational Intelligence and Computing Research, Coimbatore, India, pp, 202-206,December, 2010.
  • D.Teodorovic, and M. Dell'Orco, Bee colony optimization –A cooperative learning approach to complex transportation problems, In Advanced OR and AI Methods in Transportation, pp.51-60,2005.
  • C Tong, H Lau, A Lim, “Ant colony optimization for the ship berthing problem,” in Advances in Computing Science - ASIAN'99, P.S. Thiagarajan and R. Yap, Eds. Thailand: LNCS1742,1999, pp. 359-370.
  • X. L. Li, Z. J. Shao, and J. X. Qian, “An optimizing method based on autonomous animats: Fish-swarm Algorithm,” System Engineering Theory and Practice, vol. 22, pp.32-38, November 2003.
  • Y. Q. Zhou, Z. C. Xie, “Improved artificial fish-school swarm algorithm for solving TSP,” Systems Engineering and Electronics, vol. 31, pp. 1458-1461, June 2009.
  • X. J. Shan, M. Y. Jiang, “The routing optimization based on improved artificial fish swarm algorithm,” Proc. of IEEE the 6th World Congress on Intelligent Control and Automation, Dalian China, pp.3658-3662, October 2006.
  • P. Li, Modelling and Optimization of Berth Allocation and Quay Scheduling System. Dissertation, Tianjin, China: Tianjin university, 2007.
  • C. Bierwirth,and F. Meisel, “A survey of berth allocation and quay crane scheduling problems in container terminals,” European Journal of Operational Research,vol. 202, pp. 615-627, May 2010.
  • K. H. Kim, K. C. Moon, “Berth scheduling by simulated annealing,” Transportation Research Part B, vol. 37, pp.541-560, July 2003.
  • E. Nishimura, A. Imai, and S. Papadimitriou, “Berth allocation planning in the public berth system by genetic algorithms,” European Journal of Operational Research, vol. 131, pp. 282-292, June 2001.
  • L. P. Ouyang, X. H. Wang and J. M. Xiao, “ Berth scheduling problem based on ant colony algorithm,”Control Engineering of China, vol. 16, S1, pp106-109, July 2009
Еще
Статья научная