CN110980082A - Automatic stereoscopic warehouse position allocation method - Google Patents

Automatic stereoscopic warehouse position allocation method Download PDF

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CN110980082A
CN110980082A CN201911262877.7A CN201911262877A CN110980082A CN 110980082 A CN110980082 A CN 110980082A CN 201911262877 A CN201911262877 A CN 201911262877A CN 110980082 A CN110980082 A CN 110980082A
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goods
warehouse
shelf
characteristic parameters
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张晴
郭旭
朱伟
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Zhejiang University Kunshan Innovation Institute
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G1/00—Storing articles, individually or in orderly arrangement, in warehouses or magazines
    • B65G1/02—Storage devices
    • B65G1/04—Storage devices mechanical
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G1/00—Storing articles, individually or in orderly arrangement, in warehouses or magazines
    • B65G1/02—Storage devices
    • B65G1/04—Storage devices mechanical
    • B65G1/137—Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed
    • B65G1/1373—Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed for fulfilling orders in warehouses

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Abstract

The invention discloses an automatic stereoscopic warehouse location allocation method in the technical field of warehouse location allocation, and aims to solve the technical problems of low warehouse utilization rate and high warehouse entry and exit time cost caused by unreasonable warehouse location allocation of goods in a warehouse in the prior art. Collecting characteristic parameters of the goods and constructing a corresponding optimization model according to the characteristic parameters of the goods; acquiring characteristic parameters of the goods shelf and constructing a corresponding optimization model according to the characteristic parameters of the goods shelf; converting the weighting coefficients of the plurality of optimization models established in the step into a single objective function model; solving a single objective function model by using a genetic algorithm and optimizing; and obtaining the optimal storage position of the goods according to the optimization result. The warehouse location of the automatic stereoscopic warehouse is optimized, and the warehouse location is reasonably arranged for goods, so that the moving distance of entering and exiting the warehouse is shortened, the operation time is shortened, the storage space can be fully utilized, and the warehousing cost is reduced; the goods location optimization is to dynamically distribute the storage locations of the goods in the warehouse so as to ensure that the distribution of the storage locations is better.

Description

Automatic stereoscopic warehouse position allocation method
Technical Field
The invention belongs to the technical field of warehouse location allocation, and particularly relates to an automatic stereoscopic warehouse location allocation method.
Background
The modern logistics industry plays an increasingly important role in economic development, and according to statistical results, the cost paid for storage and transportation accounts for more than 40% of the production cost. In the existing warehousing operation, managers mostly perform warehousing business execution such as warehousing-out operation and warehousing-in operation according to operation experience, and goods warehousing is stored in a random storage mode according to vacant warehouse positions, so that the mode is too strong in subjectivity and lacks of scientific basis, a large amount of time waste and cost waste occur in the warehousing working process, the warehouse utilization rate is low, and a large amount of goods to be picked are retained in a goods picking area. And is not beneficial to updating and inquiring data, and brings great inconvenience to the disk library.
Disclosure of Invention
The invention aims to provide an automatic stereoscopic warehouse location allocation method to solve the technical problems of low warehouse utilization rate and high warehouse entry and exit time cost caused by unreasonable location allocation of goods in a warehouse in the prior art.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows: an automatic stereoscopic warehouse storage position allocation method comprises the following steps:
a. collecting characteristic parameters of the goods and constructing a corresponding optimization model according to the characteristic parameters of the goods;
b. acquiring characteristic parameters of the goods shelf and constructing a corresponding optimization model according to the characteristic parameters of the goods shelf;
c. converting the weighting coefficients of the plurality of optimization models established in the step into a single objective function model;
d. solving a single objective function model by using a genetic algorithm and optimizing;
e. and obtaining the optimal storage position of the goods according to the optimization result.
The characteristic parameters of the goods comprise the turnover rate of the goods and the correlation of the goods.
The optimization model constructed according to the turnover rate of the goods comprises the minimum delivery distance of the goods, the warehousing time of the goods, the ex-warehousing time of the goods, the operation time of a conveyor belt and a stacker during the ex-warehousing operation of the goods and the minimum total time consumed by a certain amount of goods to be completely ex-warehoused; all goods of the same tenant in an optimization model constructed according to the relevance of the goods are placed in a classified and concentrated mode, and the distance from the goods of different classes to an equivalent center is shortest.
The characteristic parameter of the shelf comprises the stability of the shelf.
The optimization model constructed according to the stability of the shelf comprises the gravity center of the shelf in the vertical direction, the gravity center of the shelf in the horizontal direction and the balance of the same group of shelves.
The genetic algorithm is improved by taking a hill climbing algorithm as an operator.
Compared with the prior art, the invention has the following beneficial effects: the warehouse location of the automatic stereoscopic warehouse is optimized, and the warehouse location is reasonably arranged for goods, so that the moving distance of entering and exiting the warehouse is shortened, the operation time is shortened, the storage space can be fully utilized, and the warehousing cost is reduced; the goods location optimization is to dynamically distribute the storage locations of the goods in the warehouse so as to ensure that the distribution of the storage locations is better.
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Fig. 1 is a perspective view of an automated stereoscopic warehouse to which a method for allocating storage space of the automated stereoscopic warehouse according to an embodiment of the present invention is applied;
fig. 2 is a top view of an automated stereoscopic warehouse to which the method for allocating storage space in the automated stereoscopic warehouse according to the embodiment of the present invention is applied;
fig. 3 is a schematic diagram of a single row shelf of an automated stereoscopic warehouse to which a method for allocating positions of the automated stereoscopic warehouse according to an embodiment of the present invention is applied;
fig. 4 is a schematic diagram of an automated stereoscopic warehouse warehousing process applying the method for allocating the warehouse location of the automated stereoscopic warehouse provided by the embodiment of the invention;
fig. 5 is a schematic diagram of an automated stereoscopic warehouse ex-warehouse process using the method for allocating the positions of the automated stereoscopic warehouse according to the embodiment of the present invention;
fig. 6 is a flow chart of the allocation of the storage space of the automated stereoscopic warehouse to which the method for allocating the storage space of the automated stereoscopic warehouse according to the embodiment of the present invention is applied;
fig. 7 is a route diagram of a location allocation technique of an automated stereoscopic warehouse to which a location allocation method of the automated stereoscopic warehouse according to an embodiment of the present invention is applied;
in the figure: 1. a shelf; 2. a guide rail; 3. a stacker; 4. and (4) a conveyor belt.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
The storehouse position is optimized to carry out reasonable distribution on the storehouse positions in the automatic stereoscopic warehouse, and the storehouse position not only comprises the position for storing the goods formulated according to the characteristics of the goods, such as the stability of goods storage measured by the gravity of the goods, but also comprises the storage area for reasonably arranging different goods according to the external requirements and the conversion of the storage environment. The operation of the storage system is influenced by external factor changes, the frequency of goods entering and exiting is different, and the phenomenon that goods are too concentrated on the local goods of the goods shelf is generated after the warehouse is operated for a long time, so that the stress of the goods shelf is not uniform. Therefore, in order to improve the utilization rate of the storage positions of the automatic stereoscopic warehouse as much as possible and improve the efficiency of goods entering and leaving the warehouse, a multi-objective optimization model is established by taking the goods turnover rate, the shelf stability and the goods correlation of each tenant as objective functions.
Aiming at the condition that the warehouse-in and warehouse-out tables are arranged on two sides of the goods shelf, the automatic three-dimensional warehouse with n rows of p rows of q layers of goods shelves is selected, the first row of the row position closest to the warehouse-in and warehouse-out is arranged, the row closest to the entrance is arranged as the first row, the bottommost layer of the goods shelf is the first layer, and the coordinates of the warehouse-in and warehouse-out opening are (0,0, 0). The warehouse uses the same tray, the size of the warehouse positions on the goods shelf is a, b and c, the length, the width and the height of any tray can be respectively, any tray can only be stored on any warehouse position of the goods shelf, as shown in figure 1, the warehouse position coordinate in the x-th row, y-column and z-layer is (x, y and z). The automatic stereoscopic warehouse is a unit goods format automatic stereoscopic warehouse, and a common stacker is used for storing and taking goods.
Fig. 6 is a flow chart illustrating the allocation of the storage space of the automated stereoscopic warehouse according to the method for allocating the storage space of the automated stereoscopic warehouse according to the embodiment of the present invention; fig. 7 is a route diagram of the location allocation technique of the automated stereoscopic warehouse, to which the location allocation method of the automated stereoscopic warehouse according to the embodiment of the present invention is applied; an automatic stereoscopic warehouse storage position allocation method comprises the steps of collecting characteristic parameters such as the turnover rate of goods and the correlation of the goods, and constructing a corresponding optimization model according to the characteristic parameters of the goods:
minimizing the delivery distance of the goods according to the turnover rate:
Figure BDA0002312040600000041
S’xyz＝S’level of+S’Is vertical+SIs perpendicular to(2)
Figure BDA0002312040600000042
S’Is vertical＝(p-yi)a (4)
SIs perpendicular to＝(Zi-1)c (5)
Wherein, F1(x, y, z) represents an objective function for minimizing a distribution distance of the goods according to a goods turnover rate, DxyzDenotes turnover number, S'xyzRepresenting the ex-warehouse distance, S 'of the ith tenant cargo'Level ofRepresents the horizontal distance, S ', of the row where the goods are located from the delivery platform'Is verticalIndicating the vertical distance of the row of goods from the delivery opening of each row of shelves, SIs perpendicular toIndicating the distance, x, of the layer on which the goods are located from the groundiRows, L, representing coordinates of the goods0Indicating the spacing between shelves, i.e. width of lanes, yiColumns representing coordinates of the goods, ZiA layer representing coordinates of the cargo.
In view of the time cost, it is possible to,
warehousing time:
Sxyz＝Slevel of+SIs vertical+SIs perpendicular to(6)
Figure BDA0002312040600000051
SIs vertical＝(yi-1)a (8)
SIs perpendicular to＝(Zi-1)c (9)
Wherein S isxyzRepresents the warehousing distance of the ith tenant cargo, SLevel ofHorizontal distance, S, from the storage area to the row of goodsIs verticalThe vertical distance between the row where the goods are placed and the warehousing port of each row of shelves is represented;
calculate the coordinates of the cargo space as (x)i，yi，zi) The time taken for the class i goods to be delivered is roughly expressed by the following formula:
Figure BDA0002312040600000052
wherein, txyzRepresents the time required for the ith tenant to move the goods from the goods position to the warehousing port, vxIndicating the maximum speed of travel, v, of the horizontal conveyoryIndicating the maximum speed (vertical) at which the stacker is travelling in the roadway, vzRepresenting the maximum speed of vertical travel of the stacker;
when all goods on the goods shelf are put into storage and operated, the total operation time of the conveyor belt and the stacker is Txyz
Figure BDA0002312040600000053
Wherein Q isxyzRepresenting the total quantity of goods which are delivered and warehoused in one period;
and (3) ex-warehouse time:
S′xyz＝S′level of+S′Is vertical+SIs perpendicular to(2)
Figure BDA0002312040600000054
S′Is vertical＝(p-yi)a (4)
SIs perpendicular to＝(Zi-1)c (5)
Calculate the coordinates of the cargo space as (x)i，yi，zi) The time taken for the class i goods to be delivered is roughly expressed by the following formula:
Figure BDA0002312040600000055
wherein, t'xyzRepresenting the time required for a certain type of goods to be taken out of the warehouse;
when all goods on the goods shelf are simultaneously taken out of the warehouse, the total time of the operation of the conveyor belt and the stacker is T'xyz
Figure BDA0002312040600000061
Wherein, T'xyzRepresenting the time required for all goods to be delivered out of the warehouse;
the minimum total time consumed by a certain amount of goods to be completely delivered into and delivered out of the warehouse is taken as an optimization objective function,
an objective function:
F2(x，y，z)＝min(Txyz+T’xyz) (14)
wherein, F2(x, y, z) represents an objective function that minimizes cargo access time,
constraint conditions are as follows:
Figure BDA0002312040600000062
consider the relevance of goods: according to the method, goods of the automatic warehouse are stored for multiple tenants, the goods of a single tenant have relevance, and the goods can be taken out of the warehouse at the same time when being extracted according to an order, so that the goods of the same tenant can be put together as much as possible in order to shorten the picking time and the movement path of the stacker. All goods in the warehouse are divided into N types according to different tenants, and N is contained under each type of productjThe coordinates of the goods positions with mutual correlation are (x)ij，yij，zij) From this, the center coordinate O on the shelf of the same large class of products can be calculatedi＝(Oi(x)，Oi(y)，Oi(z))
Figure BDA0002312040600000063
Figure BDA0002312040600000064
Figure BDA0002312040600000065
The goods of the same type or with the internal contact degree are ensured, and when the goods location is distributed, the distance from all the goods to the equivalent center of the product is shortest;
intra-class dispersion:
Figure BDA0002312040600000071
wherein, F6(x, y, z) represents an objective function with minimum dispersion of the same kind of goods,
constraint conditions are as follows:
Figure BDA0002312040600000072
acquiring characteristic parameters of the goods shelf and constructing a corresponding optimization model according to the characteristic parameters of the goods shelf:
considering shelf stability, the center of gravity of a single shelf in the vertical direction,
suppose a cargo space (x)i，yi，zi) Mass of the stored goods is mxyzI.e. the vertical centre of gravity of the entire pallet is Gxyz，
Figure BDA0002312040600000073
An objective function:
F3(x，y，z)＝minGxyz(20)
wherein, F3(x, y, z) represents the objective function of the lowest center of gravity of the overall shelf,
center of gravity in the horizontal direction, the closer the average center of gravity in the horizontal direction is to the middle column or columns, the better, assuming a cargo space (x)i，yi，zi) Mass of the stored goods is mxyzI.e. the vertical centre of gravity G 'of the overall shelf'xyz，
Figure BDA0002312040600000074
An objective function:
Figure BDA0002312040600000081
wherein, F4(x, y, z) represents an objective function of the distance of the horizontal center of gravity of the overall shelf from the middle of the shelf,
the same group of goods shelves ensures that the two goods shelves of the same group of goods shelves bear the weight basically in consideration of the anti-overturning stability of a single goods shelf;
an objective function:
Figure BDA0002312040600000082
wherein, F5(x, y, z) represents an objective function with the smallest difference of the gravity of the goods on the same shelf group, wherein x is 2k and x is 2k +1,
Figure BDA0002312040600000083
2 shelf close to each other are shown, as shown in fig. 3, a stacker is arranged between two rows of shelf, and the difference between the gravity of goods placed on two shelf together is considered to be small, so that overturning is prevented;
constraint conditions are as follows:
the pallet is most stable when it is loaded with goods of a nominal weight and the centre of gravity of the pallet is below the neutral line. Each bin stock is assumed to be of uniform quality and to fill the entire bin space.
Figure BDA0002312040600000084
Wherein M is the rated bearing capacity of the goods shelf, kg; h-height m of the shelf; c- -each library siteHeight m of (a); m isxyz-the mass kg of the goods in the x, y and z-th tier of the depot,
the goods shelf is provided with q layers of goods,
H＝qc (25)
is provided with
Figure BDA0002312040600000085
Figure BDA0002312040600000086
Is the rated bearing capacity kg of a single storage position,
Figure BDA0002312040600000087
in order to ensure the absolute stability of the shelf, each term of the formula is less than or equal to zero,
Figure BDA0002312040600000088
in summary, the constraint:
Figure BDA0002312040600000091
converting the weighting coefficients of the plurality of optimization models established in the steps into a single objective function model: because the objective functions are restricted with each other, and the problem cannot be solved by independently carrying out optimization research, different weights need to be given to the objective functions through a weight coefficient method of a genetic algorithm, and the objective functions are combined to form a single objective function problem which is favorable for calculation. The magnitude of each weight is set according to the company's own situation,
Figure BDA0002312040600000092
wherein, w1Representing an objective function F1Occupied weight value, w2Representing an objective function F2Occupied weight value, w3Representing an objective function F3Occupied weight value, w4Representing an objective function F4Occupied weight value, w5Representing an objective function F5Occupied weight value, w6Representing an objective function F6The weight value occupied.
And solving the model by using a genetic algorithm after the hill climbing algorithm is used as an operator for improvement, and carrying out storage position distribution on the warehoused goods to find out the optimal storage position for storing the goods.
As shown in fig. 1, 2 and 3, the automatic stereoscopic warehouse is composed of n rows of p rows of q layers of shelves 1, the shelves in the first row and the last row are independently placed, every two shelves in the middle are placed in parallel, a roadway is reserved between the shelves 1, guide rails 2 are laid, and a stacker 3 is used for picking goods between the shelves 1. And the row closest to the warehouse inlet and outlet is the first row, the row closest to the warehouse inlet and outlet is the first column, the bottommost layer of the goods shelf is the first layer, and the coordinates of the warehouse inlet and outlet are (0,0, 0). The goods are conveyed to a conveyor belt 4 through a stacker 3 and then moved to an in-out warehouse table.
The warehouse uses the same tray, the size of the warehouse positions on the goods shelf is a, b and c, the length, the width and the height of any tray can be respectively, any tray can only be stored on any warehouse position of the goods shelf, as shown in figure 1, the warehouse position coordinate in the x-th row, y-column and z-layer is (x, y and z). According to the figure 4, before the goods are put in storage, according to the warehousing list, the warehousing order of the batch of goods is recorded in the system, after the warehousing order is checked to be correct, the warehouse location is automatically distributed according to a warehouse location optimization algorithm, the production instruction is generated in the system, and the stacker carries out warehousing operation according to the operation instruction. When the goods are taken out of the warehouse, according to the figure 5, after the order form is received, the warehouse-out form is generated, after the goods are checked to be correct, the warehouse positions are automatically distributed according to the goods optimization algorithm, and the stacker receives the instruction to carry out warehouse-out operation. According to the invention, the warehouse location of the automatic stereoscopic warehouse is optimized, and the warehouse location is reasonably arranged for goods, so that the aims of shortening the moving distance of entering and exiting the warehouse, shortening the operation time, even fully utilizing the storage space and reducing the warehousing cost and the like are achieved; the goods location optimization is to dynamically allocate the locations of goods in the warehouse so as to ensure that the distribution of the locations is better, and the optimization degree of the location allocation determines the operation effect of the automatic stereoscopic warehouse system.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.

Claims (6)

1. An automatic stereoscopic warehouse storage position allocation method is characterized by comprising the following steps:
a. collecting characteristic parameters of the goods and constructing a corresponding optimization model according to the characteristic parameters of the goods;
b. acquiring characteristic parameters of the goods shelf and constructing a corresponding optimization model according to the characteristic parameters of the goods shelf;
c. converting the weighting coefficients of the plurality of optimization models established in the step into a single objective function model;
d. solving a single objective function model by using a genetic algorithm and optimizing;
e. and obtaining the optimal storage position of the goods according to the optimization result.
2. The method as claimed in claim 1, wherein the characteristic parameters of the goods include a turnover rate of the goods and a correlation of the goods.
3. The automatic stereoscopic warehouse storage space allocation method according to claim 2, wherein the optimization model constructed according to the turnover rate of the goods comprises the minimum delivery distance of the goods, the warehousing time of the goods, the ex-warehouse time of the goods, the operation time of a conveyor belt and a stacker during the ex-warehouse operation of the goods and the minimum total time consumed by the whole ex-warehouse of a certain amount of goods; all goods of the same tenant in an optimization model constructed according to the relevance of the goods are placed in a classified and concentrated mode, and the distance from the goods of different classes to an equivalent center is shortest.
4. The automated stereoscopic warehouse slot allocation method of claim 1, wherein the characteristic parameter of the shelf comprises shelf stability.
5. The method of claim 4, wherein the optimization model constructed based on shelf stability comprises a vertical center of gravity of the shelf, a horizontal center of gravity of the shelf, and a balance of the same group of shelves.
6. The method as claimed in claim 1, wherein the genetic algorithm is a genetic algorithm modified by using a hill-climbing algorithm as an operator.
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CN112884305B (en) * 2021-02-03 2024-04-16 杨耿标 Warehouse logistics distribution method based on big data platform
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CN113255988A (en) * 2021-05-21 2021-08-13 河海大学 Dynamic threshold value cross access method based on precise goods position matching
CN113255988B (en) * 2021-05-21 2022-09-30 河海大学 Dynamic threshold value cross access method based on precise goods position matching
CN113283837A (en) * 2021-05-31 2021-08-20 深圳市库宝软件有限公司 Warehousing control method and device
CN113222293A (en) * 2021-06-03 2021-08-06 江南大学 Intelligent stereoscopic warehouse optimal scheduling method
CN114261668A (en) * 2021-11-29 2022-04-01 广东嘉腾机器人自动化有限公司 Allocation strategy based on dispatching system and multi-storage-position system joint dispatching AGV
CN114356298A (en) * 2021-12-31 2022-04-15 常州飞石机器人系统有限公司 Method for automatically generating appropriate storage position based on storage dynamic position
CN115490016A (en) * 2022-09-30 2022-12-20 山东海运股份有限公司 Distribution method of dynamic container storage positions
CN115578039A (en) * 2022-12-09 2023-01-06 成都运荔枝科技有限公司 Warehouse goods space allocation method, electronic equipment and computer storage medium
CN116050671A (en) * 2023-03-31 2023-05-02 成都思越智能装备股份有限公司 Automatic stereoscopic warehouse shelf information automatic maintenance method
CN116050671B (en) * 2023-03-31 2023-06-02 成都思越智能装备股份有限公司 Automatic stereoscopic warehouse shelf information automatic maintenance method
CN117371621A (en) * 2023-12-06 2024-01-09 湖北浩蓝智造科技有限公司 Library position distribution method, system and medium based on improved drosophila optimization algorithm
CN117371621B (en) * 2023-12-06 2024-02-27 湖北浩蓝智造科技有限公司 Library position distribution method, system and medium based on improved drosophila optimization algorithm
CN117875846A (en) * 2024-03-11 2024-04-12 青岛冠成软件有限公司 Cargo storage method for improving utilization rate of warehouse
CN117875846B (en) * 2024-03-11 2024-05-31 青岛冠成软件有限公司 Cargo storage method for improving utilization rate of warehouse
CN117952522A (en) * 2024-03-26 2024-04-30 瑞熙(苏州)智能科技有限公司 Warehouse entry management method and system based on data processing
CN117952522B (en) * 2024-03-26 2024-06-07 瑞熙(苏州)智能科技有限公司 Warehouse entry management method and system based on data processing

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