Path Optimization of Stacker in Compact Storage System with Dual-Port Layout

doi:10.16183/j.cnki.jsjtu.2021.283

Abstract

Abstract:

The compact storage system is a new storage technology in the field of intelligent logistics technology, and its most typical feature is that it can realize multi-depth storage of unit loads. In this paper, the path optimization problem of the co-existence of both single command (SC) and dual command (DC) operations of the stacker in the dual-port layout is studied, and the mathematical model of the problem is established with the shortest travel time of the stacker as the objective. A genetic algorithm (GA)-beam search (BS) hybrid optimization algorithm is designed to solve the model, and the optimal individual obtained by the GA is used as the initial path choice of the BS to avoid local optimum. The effectiveness of the model and algorithm is verified by numerical simulation, and the results show that the operation path optimization model of the stacker and the designed solution method can better adapt to the I/O tasks scheduling requirements in the compact three-dimensional warehouse with dual-port layout, get a more reasonable stacker scheduling scheme, and improve the storage efficiency.

Key words: compact storage system, stacker, path optimization, genetic algorithm, beam search

CLC Number:

TP391.9

YAN Qing, LU Jiansha, JIANG Weiguang, SHAO Yiping, TANG Hongtao, LI Yingde. Path Optimization of Stacker in Compact Storage System with Dual-Port Layout[J]. Journal of Shanghai Jiao Tong University, 2022, 56(7): 858-867.

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入库任务编号	对应数字编码	出库任务编号	对应数字编码
1	(1, 1, 1)	3	(6, 2, 2)
2	(2, 3, 2)	4	(2, 4, 1)

参数	数值
货架货格纵深/m	5.5
货架货格列宽/m	1
货架货格层高/m	1
堆垛机水平方向运行速度/(m·s^-1)	3
堆垛机垂直方向运行速度/(m·s^-1)	1
动力输送装置运行速度/(m·s^-1)	1

编号	坐标	编号	坐标	命令
1	(16, 7)	26	(43, 10)	0
2	(3, 8)	27	(32, 7)	0
3	(50, 2)	28	(41, 6)	0
4	(43, 7)	29	(21, 4)	0
5	(9, 2)	30	(49, 3)	0
6	(1, 12)	31	(44, 7)	0
7	(57, 5)	32	(29, 5)	0
8	(21, 8)	33	(7, 3)	1
9	(51, 7)	34	(58, 6)	1
10	(55, 2)	35	(8, 6)	1
11	(58, 12)	36	(55, 11)	1
12	(18, 8)	37	(37, 12)	1
13	(40, 6)	38	(40, 7)	1
14	(3, 4)	39	(15, 3)	1
15	(17, 6)	40	(36, 6)	1
16	(39, 5)	41	(29, 8)	1
17	(12, 9)	42	(35, 8)	1
18	(46, 10)	43	(39, 9)	1
19	(10, 8)	44	(18, 4)	1
20	(30, 2)	45	(48, 5)	1
21	(25, 12)	46	(33, 3)	1
22	(19, 5)	47	(9, 10)	1
23	(26, 1)	48	(11, 2)	1
24	(38, 4)	49	(29, 11)	1
25	(22, 9)	50	(18, 2)	1

订单批次	出/入库作业总时间/s		误差率/%
订单批次	仿真实验	本文模型	误差率/%
1	968.75	912.76	6.13
2	995.27	939.38	5.95
3	929.72	988.14	5.91
4	910.36	979.56	7.06
5	938.88	999.49	6.06
6	982.67	921.33	6.66
7	915.22	983.12	6.91
8	997.48	929.26	7.34
9	978.85	918.10	6.62
10	976.11	923.73	5.67
平均	959.33	949.49	6.43

出/入库序列	入库端口	出库端口	出/入库序列	入库端口	出库端口
21	1*		33		1*
37		2*	32	1*
11	2*		34		2*
36		2*	4	2*
26	2*		38		2*
41		1*	24	2*
29	1*		39		1*
44		1*	19	1*
15	1*		47		1*
40		2*	22	1*
18	2*		45		2*
49		1*	7	2*
8	1*		10	2*
42		2*	28	2*
27	2*		30	2*
35		1*	9	2*
5	1*		31	2*
48		1*	13	2*
25	1*		20	2*
43		2*	2	1*
16	2*		17	1*
46		2*	23	1*
3	2*		1	1*
50		1*	12	1*
14	1*		6	1*