[1]王增臣,周良.带二维装载约束的车辆调度问题建模及优化[J].计算机技术与发展,2018,28(10):105-110.[doi:10.3969/ j. issn.1673-629X.2018.10.022]
 WANG Zeng-chen,ZHOU Liang.Modeling and Optimization of Vehicle Scheduling Problem with Two-dimensional Loading Constraints[J].,2018,28(10):105-110.[doi:10.3969/ j. issn.1673-629X.2018.10.022]
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带二维装载约束的车辆调度问题建模及优化()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
28
期数:
2018年10期
页码:
105-110
栏目:
智能、算法、系统工程
出版日期:
2018-10-10

文章信息/Info

Title:
Modeling and Optimization of Vehicle Scheduling Problem with Two-dimensional Loading Constraints
文章编号:
1673-629X(2018)10-0105-06
作者:
王增臣周良
南京航空航天大学 计算机科学与技术学院,江苏 南京 210016
Author(s):
WANG Zeng-chenZHOU Liang
School of Computer Science and Technology,Nanjing University of Aeronautics and Astronautics, Nanjing 210016,China
关键词:
物流配送车辆调度问题Pareto 最优解多目标蚁群优化最低水平线搜索算法
Keywords:
logistics distributionvehicle scheduling problemPareto solutionmulti-objective ant colony optimizationlowest horizontal search algorithm
分类号:
TP183
DOI:
10.3969/ j. issn.1673-629X.2018.10.022
文献标志码:
A
摘要:
带二维装载约束的车辆调度问题大量存在于现代物流活动中,该问题是二维装箱问题与车辆路径问题这两个经典难题融合之后的一个新问题。 针对这一问题,在综合考虑客户需求、时间窗、二维装载约束、载重量以及客户满意度的基础上,建立了带二维装载约束的多目标物流配送中的车辆调度问题模型,同时,提出了一种车辆调度优化算法。 该算法采用多目标蚁群优化得到 Pareto 最优解,在货物装载阶段采用改进的最低水平线搜索算法的二维装载策略,提高车辆装载率;在车辆路径优化阶段采用改进的信息素更新策略和客户转移概率方法,提升蚁群搜索性能。 实例测试及与其他算法比较表明,该算法能有效解决模型问题,在解空间上有更好的探寻性能。
Abstract:
In modern logistics,there is a great amount of transportation problems called vehicle scheduling problem with two-dimensional loading constraints,which is a new problem that combines the two classical problem of vehicle routing and bin pack. To solve the problem,we build a mathematical model of vehicle scheduling problem in multi-objective logistics distribution based on two-dimensional loading constraints,synthesizing customer requirements,time windows,two-dimensional loading constraints,vehicle load and customer satisfaction. Meanwhile,we propose a vehicle scheduling optimization algorithm which adopts multi-objective ant colony optimization to get Pareto solutions. In the cargo loading,the two-dimensional loading strategy based on the modified lowest horizontal search algorithm is adopted to improve vehicle loading rate,and in the vehicle routing optimization,the algorithm uses the modified updating strategy of pheromone and the method of customer transiting probability to improve the searching performance of the ant particles. The test and comparison with other algorithms show that the proposed algorithm can solve the model effectively with better performance in solution space.

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更新日期/Last Update: 2018-10-10