A Study of Archipelago Berth Allocation Based on Hybrid Particle

 Swarm Optimization Algorithm

Abstract

Abstract: Berth allocation is the key to improving the efficiency of port operation. Aiming at the archipelago berth allocation, a model is established with minimum waiting time of ships as objective, and a hybrid particle swarm optimization (HPSO) algorithm proposed. In HPSO, simulated annealing (GA) and artificial immunity (AI) are applied to update the state of particles, thus improving the global optimization of HPSO. Numerical experiment results show that, the HPSO is an effective and feasible algorithm for solving the archipelago berth allocation problem.

Key words: archipelago berth allocation, hybrid particle swarm optimization(HPSO), artificial immunity(AI)

Peng Jian-liang， Li Ren-jian， Li Xiu-lin， Ju Chun-hua. A Study of Archipelago Berth Allocation Based on Hybrid Particle Swarm Optimization Algorithm[J]. Industrial Engineering Journal , 2014, 17(5): 17-22.

References

［1］Steenken D, Voβ S, Stahlbock R. Container terminal operation and operations researcha classification and literature review ［J］. OR Spectrum, 2004, 26(1): 3-49. ［2］Stahlbock R, Voβ S. Operations research at container terminals: a literature update ［J］. OR Spectrum, 2008, 30(1):1-52. ［3］Imai A, Nagaiwa K, Chan W T. Efficient planning of berth allocation for container terminals in Asia ［J］. Journal of Advanced Transportation, 1997，31(1): 75-94. ［4］Imai A, Nishimura E, Papadimitriou S. The dynamic berth allocation problem for a container port ［J］. Transportation Research Part B, 2001, 35(4): 401-417. ［5］Imai A, Sun X, Nishimura E, et al. Berth allocation in a container port: using a continuous location space approach ［J］. Transportation Research Part B, 2005, 39 (3):199-221. ［6］Imai A, Chen H C, Nishimura E. The simultaneous berth and quay crane allocation problem ［J］. Transportation Research. Part E, 2008, 44(5): 900-920. ［7］Lokuge P, Alahakoon D. Improving the adaptability in automated vessel scheduling in container ports using intelligent software agents ［J］. European Journal of Operational Research, 2007, 177(3):1985-2015 ［8］Wang F, Lim A. A stochastic beam search for the berth allocation problem ［J］. Decision Support Systems, 2007, 42(4):2186-2196. ［9］Seyedalizadeh G S, Babazadeh A, Arabshahi N. Analysis of the continuous berth allocation problem in container ports using a genetic algorithm ［J］. Journal of Marine Science and Technology, 2010, 15(4): 408-416. ［10］Rudinei M O, Geraldo R M, et al. Clustering Search for the Berth Allocation Problem ［J］. Expert Systems with Applications, 2012, 39(5): 5499-5505. ［11］Liang C, Huang Y, Yang Y. A quay crane dynamic scheduling problem by hybrid evolutionary algorithm for berth allocation planning ［J］. Computers and Industrial Engineering, 2009, 56 (3):1021-1028. ［12］Eduardo L, Belen M J. Marcos M. Artificial intelligence hybrid heuristic based on tabu search for the dynamic berth allocation problem ［J］. Engineering Applications of Artificial Intelligence, 2012, 25(6): 1132-1141. ［13］杜玉泉,陈秋双,姬晓涛.面向服务的泊位和岸桥联合调度［J］.计算机集成制造系统, 2011, 17(9):2051-2060. Du Yu-quan, Chen Qui-suang, Ji Xiao-tao. Serviceoriented berth allocation and quay crane assignment ［J］. Computer Integrated Manufacturing Systems, 2011, 17(9):2051-2060 ［14］周鹏飞,康海贵.面向随机环境的集装箱码头泊位岸桥分配方法［J］.系统工程理论与实践.2008(1):161-169. Zhou Pengfei, Kang Haigui. Study on berth and quaycrane allocation under stochastic environments in container terminal ［J］. Systems Engineering Theory and Practice, 2008(1):161-169 ［15］Kennedy J, Eberhart R. Particle swarm optimization ［C］. Proc of IEEE Int Conf on Neural Networks. Piscataway,1995: 1942-1948. ［16］高尚,杨静宇.混沌粒子群优化研究［J］. 模式识别与人工智能,2006,19(2):266-270. Gao Shang, Yang Jingyu. Research on Chaos Particle Swarm Optimization Algorithm ［J］. Pattern Recognition and Artificial Intelligence, 2006, 19(2):266-270 ［17］潘全科,王文宏,朱剑英等.基于粒子群优化和变领域搜索的混合调度算法［J］.计算机集成制造系统,2007,13(2):323-328. Pan Quan-ke, Wang Wen-hong, Zhu Jian-yin. Hybrid heuristics based on particle swarm optimization and variable neighborhood search for Job Shop scheduling ［J］. Computer Integrated Manufacturing Systems, 2007, 13(2):323-328. ［18］叶春明，潘登，潘逢山.基于混沌粒子群算法的关键链项目进度管理研究［J］.计算机应用研究，2011，28（3）：890-894. Ye Chun-ming，Pan Deng，Pan Feng-shan. Critical chain project management based on chaos particle swarm optimization ［J］. Application Research of Computers, 2011，28（3）：890-894.

A Study of Archipelago Berth Allocation Based on Hybrid Particle Swarm Optimization Algorithm

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