成组集中策略下滚装汽车堆场车位分配优化

陈晓静; 胡志华; 李功君; 滕炜超

doi:10.3969/j.issn.1000-5641.2017.01.002

成组集中策略下滚装汽车堆场车位分配优化

doi: 10.3969/j.issn.1000-5641.2017.01.002

1.
上海海事大学物流研究中心, 上海 201306
2.
上海海通国际汽车码头有限公司, 上海 200137

基金项目:

国家自然科学基金 71471109, 71101088

详细信息

作者简介:
陈晓静, 女, 硕士研究生,研究方向为港口物流运作优化. E-mail: 990598065@qq.com

通讯作者:
胡志华, 男, 教授, 研究生导师,研究方向为物流与供应链管理.E-mail:zhhu@shmtu.edu.cn

中图分类号: O224; U651
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- 被引次数: 0
出版历程
- 收稿日期: 2016-01-06
- 刊出日期: 2017-01-25

Optimization for parking space distribution in storage yard of automotive ro-ro wharf based on the strategy of gathered groups

1.
Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China
2.
Shanghai Haitong International Automotive Terminal Co.,Ltd., Shanghai 200137, China

摘要

摘要: 滚装汽车堆场车位分配的合理性直接影响到滚装运输过程中汽车装卸滚装船舶的周转率.为提升装卸作业效率, 研究了堆场车位最优分配问题;按照成组集中分配原则, 以提高堆场内成组汽车停放集中度为目标,建立了衡量成组汽车停放集中度的混合整数规划模型;进而设计了基于网格随机搜索的启发式算法对模型进行求解.通过数值实验与分支定界法作比,验证了模型的合理性及网格随机搜索算法的有效性,拓展了汽车滚装码头堆场车位分配管理的理论研究.
- 滚装堆场 /
- 成组汽车 /
- 车位分配 /
- 集中度 /
- 网格随机搜索
Abstract: The rationality of parking space distribution of the ro-ro storage yard effects the loading and unloading of turnover rate in the process of ro-ro transportation. In order to improve the working efficiency, the article researched the problem of parking space optimal distribution. According to the principle of gathered groups distribution, focusing on improving concentration degree of batch automobiles, a mixed-integer programming model was proposed to measure concentration degree of batch automobiles. Then a heuristic algorithm of grids random search was designed to solve the model. Compared with branch and bound method through numerical experiments, the results proved that the proposed model and algorithm are reasonable and valid, generalizing the theory research for parking space distribution and managment of ro-ro wharf.
- ro-ro storage yard /
- batch automobiles /
- parking space distribution /
- concentration degree /
- grids random search

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图 1 上海海通汽车滚装码头外四堆场部分车位布局图

Fig. 1 Layout of partial parking space in the outer four storage yard of Shanghai Haitong automotive ro-ro wharf

下载: 全尺寸图片幻灯片

图 2 变量间逻辑关系

Fig. 2 Logical relationship among the variables

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图 3 基于网格随机搜索的汽车车位交换示例

Fig. 3 A demonstration of vehicles swap based on the grids random searching

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图 4 分支定界------场景一算例1堆场车位分配方案

Fig. 4 Branch and bound---distribution scheme of parking space in the first example of first scene

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图 5 网格随机搜索------场景一算例 1 堆场车位分配方案

Fig. 5 Grids random search---distribution scheme of parking space in the first example of first scene

下载: 全尺寸图片幻灯片

表 1 数值实验设计

Tab. 1 Numerical experiments design

实验待		作业汽车属性		初始堆场属性
场景	序号	汽车组数	每组汽车数目	布局 (行,列)	已占车位率	已占车位坐标
一	1	3	2/2/3	(4,5)	0.25	(2,2)(2,5)(3,1)(3,3)(3,5)
	2	3	4/2/3	(4,5)	0.25	(2,2)(2,5)(3,1)(3,3)(3,5)
	3	3	4/3/4	(4,5)	0.25	(2,2)(2,5)(3,1)(3,3)(3,5)
二	1	4	3/2/4/3	(4,5)	0.25	(2,2)(2,5)(3,1)(3,3)(3,5)
	2	5	2/4/1/3/2	(4,5)	0.25	(2,2)(2,5)(3,1)(3,3)(3,5)
	3	6	1/2/3/2/1/3	(4,5)	0.25	(2,2)(2,5)(3,1)(3,3)(3,5)
三	1	3	4/3/5	(4,5)	0.25	(2,2)(2,5)(3,1)(3,3)(3,5)
	2	3	4/3/5	(4,7)	0.25	(2,2)(2,4)(2,6)(2,7)(3,1)(3,3)(3,6)
	3	3	4/3/5	(4,9)	0.25	(2,2)(2,4)(2,6)(3,3)(3,5)(3,7)(4,2)(4,4)(4,6)
四	1	3	4/3/5	(4,5)	0.30	(2,1)(2,3)(2,4)(3,2)(3,3)(3,5)
	2	3	4/3/5	(4,5)	0.20	(2,1)(2,4)(3,3)(3,5)
	3	3	4/3/5	(4,5)	0.10	(2,1)(3,5)

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表 2 分支定界法与网格随机搜算法实验结果对比

Tab. 2 Results comparison between branch and bound method and grids random searchalgorithm

实验		分支定界法		基于网格随机搜索的启发式算法
场景	序号	目标值f	CPU Time/s	目标值f	CPU Time/s	误差/偏差^*
一	1	3.0	46	3.0	17	0.00
	2	3.0	458	3.3	10	0.10
	3	3.3	1439	3.5	11	0.06
二	1	4.0	11931	4.7	8	0.18
	2	5.0	32808	5.5	13	0.10
	3	6.0	21214	6.3	7	0.05
三	1	3.2	2261	3.3	20	0.03
	2	3.0	126076	3.7	26	0.23
	3	3.2^*	259200	3.0	19	1.00^*
四	1	3.0	638	4.1	13	0.17
	2	3.0	2303	3.5	20	0.20
	3	3.5	11976	3.2	20	0.07
注: ① 分支定界法对应的f中上标^值为上界值,其下界值为 0,gap=1; 其余f均为最优解,gap=0. ② 误差计算公式: (b-a*)/a,其中 a 为分支定界法对应的f值,b为网格随机搜索算法对应的f值. ③ 偏差计算公式: (b-a)/b,其中 a为分支定界法对应的下界值,b为网格随机搜索算法对应的 f值.

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