Passenger Liner Dynamic Fleet Planning Mathematical Model and Solving Method

Abstract

Abstract:

Through analyzing the characteristic of regular passenger liner shipping, multi-objective dynamic fleet Mathematical model is set up. This model can comprehensively reflect the ships update, idle and purchase problems under the circumstance of volume increase significantly or increase slowly. The model based on the definition of green technology, economy, environmental protection, the objective function is given. The mathematical model has the characteristics of large, discrete and integral. Computing speed increased as exponential function with the increase of the ships quantity and kinds. And "Dimension disaster" problem is generated. In this paper, the multi-objective discrete particle swarm optimization algorithm is improved by using chaos initialization, dimensional renewal, files to update and gene exchange to make it suitable for large- scale dynamic fleet planning. Finally the feasibility of this method is verified through examples and getting the conclusion of fleet planning.

Key words: waterway transportation, passenger liner, fleet planning, particle swarm optimization algorithm, mathematical model, multi-objective

摘要：

通过对定期客运班轮运输特点分析，构建出能全面反映运量增加显著和运量增加缓慢情况下的运力更新、运力闲置、运力购置的多目标动态船队规划数学模型，模型根据绿色的定义给出了技术、经济、环保性目标函数.其数学模型具有大规模、离散和整数的特点，计算速度随着船舶数量和船型的增加以指数形式递增，造成“维数灾”难题.采用混沌初始化、维更新、非支配档案更新及基因交换对多目标离散粒子群优化算法进行改进使其适用于大规模动态船队规划，最后通过实例验证该方法的可行性并得到了相应的船队规划结论.

关键词: 水路运输, 客运班轮, 船队规划, 粒子群算法, 数学模型, 多目标

CLC Number:

U6-9

QI Jun,WANG Li-zheng, SU Shao-juan. Passenger Liner Dynamic Fleet Planning Mathematical Model and Solving Method[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(4): 195-200.

齐钧，王丽铮，苏绍娟. 客运班轮动态船队规划数学模型及其求解方法研究[J]. 交通运输系统工程与信息, 2017, 17(4): 195-200.

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http://www.tseit.org.cn/EN/Y2017/V17/I4/195

References

[1] 杨秋平. 船队规划数学建模与算法研究[D]. 大连: 大连海事大学, 2010. [YANG Q P. Study on the mathematical modeling and algorithm for fleet planning[D]. Dalian: Dalian Maritime University, 2010.]

[2] 吴凯. 深港澳航线水上高速客运船队规划研究与应用[D]. 武汉: 武汉理工大学, 2010. [WU K. Research and application of high speed passenger fleet planning in Shenzhen, Hongkong and Macao[D]. Wuhan: Wuhan University of Technology, 2010.]

[3] KRISHAN RANA, VICKSON R G. Routing container ships using lagrangean relaxation and decomposition[J]. Transportation Science, 1999, 25 (3): 201-214.

[4] PERAKIS A N, JARAMILLO D I. Fleet deployment optimization for liner shipping[J]. Part 1, Background, Problem Formulation and Solution Approaches, Maritime Policy and Management,1991,18 (3): 183-200.

[5] 苏绍娟. 沿海干散货船运输的不确定性分析方法研究及应用[D]. 武汉: 武汉理工大学, 2007. [SU S J. Uncertain analytical method research and application on coast dry bulk cargo ships transportation[D]. Wuhan: Wuhan University of Technology, 2007.]

[6] 伍思敏. 多目标粒子群优化算法的改进及应用研究[D]. 无锡: 江南大学, 2013. [WU S M. Improved multi- objective swarm optimization algorithm and its application[D]. Wuxi: Jiangnan University, 2013.]

[7] 徐鹤鸣. 多目标粒子群优化算法的研究[D]. 上海: 上海交通大学, 2013. [XU H M. Research on multiobjective particle swarm optimization algorithms[D]. Shanghai: Shanghai Jiaotong University, 2013.]

[8] 陈绍新. 多目标优化的粒子群算法及其应用研究[D]. 大连: 大连理工大学, 2007. [CHEN S X. Research on multi- objective optimization particle swarm algorithm and its application[D]. Dalian: Dalian University of Technology, 2007.]

[9] 左一多. 多目标优化问题的粒子群算法及其性能分析[D]. 北京: 中国地质大学, 2013. [ZUO Y D. Particle swarm optimization algorithm and performance analysis of multi- objective optimization problems[D]. Beijing: China University of Geosciences, 2013.]

[10] 裴胜玉, 周永权. 用于约束多目标优化问题的混合粒子群算法[J]. 计算机工程与应用, 2011, 47(15): 49- 52. [PEI S Y, ZHOU Y Q. Using hybrid particle swarm algorithm for solving constrained multi-objective optimization problem[J]. Computer Engineering and Applications, 2011, 47(15): 49-52.] 200

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