CN109784566B - Order sorting optimization method and device - Google Patents
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- CN109784566B CN109784566B CN201910059738.8A CN201910059738A CN109784566B CN 109784566 B CN109784566 B CN 109784566B CN 201910059738 A CN201910059738 A CN 201910059738A CN 109784566 B CN109784566 B CN 109784566B
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Abstract
The disclosure provides an order sorting optimization method and device. The order sorting optimization method comprises the steps of considering order picking time and storage space constraint conditions, and constructing a coupling degree order sorting model by taking the minimum total time required for finishing picking of current batches of orders as an objective function; solving a coupling degree order sequencing model and outputting an order which completes sequencing; the process of solving the coupling degree order sorting model comprises the steps of distributing orders to a sorting table to obtain the order quantity of the sorting table; selecting the order with the highest coupling degree with other orders from the orders of the corresponding sorting table as a seed order; determining a picking order accompanying the order according to the minimum time consumption for entering and exiting the warehouse; wherein the accompanying order is the remaining order except the seed order.
Description
Technical Field
The disclosure belongs to the field of order sorting, and particularly relates to an order sorting optimization method and device.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
As a typical ' goods-To-person ' picking system (Part-To-Picker '), the multilayer shuttle picking system can effectively reduce the walking time of picking personnel between the goods shelves and improve the picking efficiency compared with the traditional ' person-To-goods ' picking system (Picker-To-Part), and is widely applied To the industries of e-commerce, medicine and the like in recent years. The four-way vehicle picking system is a special form of a multi-layer shuttle system and comprises four-way shuttle (simply called four-way vehicle), a goods shelf, a lifter, a roller way and other equipment. In a traditional multilayer shuttle system, a shuttle only runs in fixed roadways and layers, and in a four-way vehicle sorting system, the four-way vehicle can switch running roller ways among a plurality of roadways and layers, so that the four-way vehicle sorting system has the advantages of strong flexibility, low cost and the like, and becomes a hotspot for the development of the sorting system in recent years.
In a "four-way car" picking system, containers are stored in pallets. When receiving a picking command, the picking platform sends out a delivery instruction to the container, and the container is conveyed to the picking platform by a four-way vehicle, a roller way and a lifter and is picked by a picker. After picking a container, the picker determines whether the next order requires the goods in the container. If so, putting the container to an order cache position to wait for the next order to be picked; otherwise, the container is returned to the warehouse by equipment such as a lifter, a roller way, a four-way vehicle and the like. The inventors have found that the orderliness of the orders reduces order picking efficiency due to the limited number of order buffer slots and "four-way cars".
Disclosure of Invention
According to an aspect of one or more embodiments of the present disclosure, an order sorting optimization method is provided, which is suitable for a "four-way vehicle" picking system, and combines features of the "four-way vehicle" picking system to perform sorting optimization on batch order picking with a goal of minimizing order picking time, so as to improve the efficiency of the order picking system.
The order sorting optimization method comprises the following steps:
considering order picking time and storage space constraint conditions, and constructing a coupling degree order sorting model by taking the minimum total time required for finishing order picking of the current batch as an objective function;
solving a coupling degree order sequencing model and outputting an order which completes sequencing;
the process for solving the coupling degree order sequencing model comprises the following steps:
distributing the order to a sorting table to obtain the order quantity of the sorting table;
selecting the order with the highest coupling degree with other orders from the orders of the corresponding sorting table as a seed order;
determining a picking order accompanying the order according to the minimum sum of the conversion time and the time spent in and out of the warehouse; wherein the accompanying order is the remaining order except the seed order.
In one or more embodiments, the precondition for the coupling degree order ranking model is:
(1) each article item is placed in a container, and the position of each container is fixed;
(2) the quantity of the items in each container at least reaches a preset value, and the requirement of one order picking can be met;
(3) the four-way vehicle can carry out roadway crossing and layer changing operation, and can only convey one container each time; the four-way vehicle is parked at a task completion position after completing the task;
(4) the picking platform picks according to the order, and the next order can be picked only when the current order picking is finished;
(5) the order buffer bits are the same for each picking station.
In one or more embodiments, the total time required to complete the picking of the current batch of orders is equal to the sum of the transition time to pick two adjacent orders "four-way cars" for the cross-floor and lane change and the time to "four-way cars" to pick two adjacent orders to and from the stocker and the picking station.
In one or more embodiments, the process of selecting the order with the highest coupling degree with the other orders in the corresponding picking station orders as the seed order includes:
calculating the number of items of the same article between two orders in the corresponding picking platform order, namely the coupling degree, and obtaining an order coupling degree matrix;
and calculating the sum of the coupling degrees of each order and the rest orders, and taking the order with the highest coupling degree with the rest orders from the corresponding picking station orders as a seed order.
In one or more embodiments, the process of determining a picking order for a companion order based on a minimum sum of conversion time and in-out time includes:
calculating a time length matrix consumed by the four-way vehicle to move between the article storage position contained in one order and the article storage position contained in the other order;
calculating the total conversion time and order picking sequence of the four-way vehicle from the storage position of the item in one order to the storage position of the item in another order by an on-table operation method;
and selecting the order corresponding to the minimum sum of the time consumed for picking the order from the four-way vehicle to the warehouse and the total conversion time from the storage position of the item in one order to the storage position of the item in the other order as the next picking order until all the order picking sequences are determined.
The calculation process of the total conversion time and the order picking sequence of the four-way vehicle from the storage position of the item in one order to the storage position of the item in the other order through the on-table operation method is specifically as follows:
finding a table TijThe minimum element in the order, i, matches the current two items in the order, j, e.g
Matching the alpha th SKU in the order i with the beta th item in the order j as two items successively picked by the orders i and j;
deleting the determined matching relation in the orders i and j, namely determining the article items in the continuous picking sequence;
thirdly, continue to look for the table TijMatching two item items corresponding to the next group of orders i and j as the next group of continuously picked item items in the orders i and j;
fourthly, repeating the steps until the sorting sequence of the items in the two orders is completely determined;
obtaining the matching relation of the items of the two orders and the sorting sequence of the items;
sixthly, obtaining the conversion time between the item storage positions when the order i and the order j are picked by the four-way vehicle.
According to another aspect of one or more embodiments of the present disclosure, an order sorting optimization apparatus is provided, which is suitable for a "four-way vehicle" picking system, and combines features of the "four-way vehicle" picking system to optimize sorting of batch orders with a goal of minimizing order picking time, so as to improve efficiency of the order picking system.
The order sequencing optimization device comprises a memory and an order sequencing optimization processor; the order ranking optimization processor is configured to perform the following steps:
considering order picking time and storage space constraint conditions, and constructing a coupling degree order sorting model by taking the minimum total time required for finishing order picking of the current batch as an objective function;
solving a coupling degree order sequencing model and outputting an order which completes sequencing;
the process for solving the coupling degree order sequencing model comprises the following steps:
distributing the order to a sorting table to obtain the order quantity of the sorting table;
selecting the order with the highest coupling degree with other orders from the orders of the corresponding sorting table as a seed order;
determining a picking order accompanying the order according to the minimum sum of the conversion time and the time spent in and out of the warehouse; wherein the accompanying order is the remaining order except the seed order.
In one or more embodiments, in the order ranking optimization processor, the precondition of the coupling degree order ranking model is:
(1) each article item is placed in a container, and the position of each container is fixed;
(2) the quantity of the items in each container at least reaches a preset value, and the requirement of one order picking can be met;
(3) the four-way vehicle can carry out roadway crossing and layer changing operation, and can only convey one container each time; the four-way vehicle is parked at a task completion position after completing the task;
(4) the picking platform picks according to the order, and the next order can be picked only when the current order picking is finished;
(5) the order buffer bits are the same for each picking station.
In one or more embodiments, in the order ordering optimization processor, the total time required to complete the picking of the current batch of orders is equal to the sum of the transition time to pick two adjacent orders "four-way cars" across floors and lanes and the time to pick two adjacent orders "four-way cars" to and from the stocker and picking station.
In one or more embodiments, the step of selecting, in the order sorting optimization processor, the order with the highest coupling degree with the other orders in the corresponding picking station orders as the seed order includes:
calculating the number of items of the same article between two orders in the corresponding picking platform order, namely the coupling degree, and obtaining an order coupling degree matrix;
and calculating the sum of the coupling degrees of each order and the rest orders, and taking the order with the highest coupling degree with the rest orders from the corresponding picking station orders as a seed order.
In one or more embodiments, the process of determining, in the order ranking optimization processor, a picking order for accompanying orders based on a minimum sum of conversion time and in-out time taken to enter or exit the warehouse includes:
calculating a time length matrix consumed by the four-way vehicle to move between the article storage position contained in one order and the article storage position contained in the other order;
calculating the total conversion time and order picking sequence of the four-way vehicle from the storage position of the item in one order to the storage position of the item in another order by an on-table operation method;
and selecting the order corresponding to the minimum sum of the time consumed for picking the order from the four-way vehicle to the warehouse and the total conversion time from the storage position of the item in one order to the storage position of the item in the other order as the next picking order until all the order picking sequences are determined.
The beneficial effects of this disclosure are:
(1) the order sorting method disclosed by the invention is based on the coupling degree, so that the order sorting time can be better shortened when the order quantity is larger, the number of layer-changing and roadway-crossing operations of a four-way vehicle and a hoist is reduced, and the system efficiency is improved.
(2) For different order structures, the order sorting strategy of the present disclosure can still better shorten the order picking time relative to other picking strategies.
(3) No matter how the number of the four-way vehicles in the system changes, the improved coupling degree strategy can ensure shorter order picking time, meanwhile, the number of the four-way vehicles is not more but better, when the number of the four-way vehicles is just matched with the picking efficiency, the system is fully utilized and tends to be stable
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure and are not to limit the disclosure.
Fig. 1 is a schematic structural diagram of a "four-way vehicle" picking system provided in an embodiment of the present disclosure.
Fig. 2 is an order picking flow chart of a "four-way vehicle" picking system provided by an embodiment of the present disclosure.
Fig. 3 is a flowchart of an order sorting optimization method provided in an embodiment of the present disclosure.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used in the examples of the present disclosure have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
Interpretation of terms:
SKU, Stock Keeping Unit, item.
The four-way vehicle picking system adopts an operation mode of four-way vehicle-hoister-roller way, and is widely applied in recent years. At present, optimizing order picking time becomes a key factor and a difficult problem for improving the efficiency of a four-way vehicle picking system.
The four-way vehicle picking system in the embodiment is an automatic storage and sorting integrated system in which goods are conveyed to a picking platform by automatic equipment such as a four-way vehicle and are picked by a picker in an automatic warehouse. The four-way vehicle picking system comprises: shelves, "four-way cars", lifts, pickers and pickers, etc., as shown in fig. 1. Different from a traditional shuttle picking system, the four-way vehicle in the four-way vehicle picking system can cross a roadway and perform cross-layer operation, so that the flexibility of the system is greatly improved, and meanwhile, the number of the four-way vehicles can be flexibly adjusted according to order picking requirements, so that the system is suitable for a logistics distribution center with a large picking quantity change.
Due to the fact that the number of the order buffer positions and the number of the four-way vehicles are limited, orders are reasonably sorted, the probability that the front orders and the rear orders need the same container is increased, the container can be put in and taken out of a warehouse once to meet the requirement of more orders, the times of putting the container in and out of the warehouse and the operation frequency of the four-way vehicle switching layer and a roadway can be effectively reduced, and the order picking efficiency is further improved. On the other hand, when the current back order needs different containers, the reasonable order sequence can increase the probability that the containers of the front order and the containers of the back order are distributed on the same roadway and the same layer, the frequency of switching layers and the roadway by the four-way vehicle can be reduced, and the picking efficiency is improved. Therefore, order sequencing optimization is extremely important to improve the picking efficiency of the "four-way vehicle" picking system.
The order picking process of the four-way vehicle picking system comprises the following steps: the system distributes orders to each sorting table in batch and evenly; secondly, taking out the container by the four-way vehicle; thirdly, the hoister conveys the four-way vehicle loaded with the cargo box to the first floor; fourthly, the containers are conveyed to a sorting table by the four-way vehicle according to a delivery line, as shown by a dotted line with an arrow on the left side of the figure 1; picking personnel pick the goods; the order picker judges whether the next order needs the current goods, if so, the order buffer position is continuously judged whether to be full, and if not, the container is buffered; if the next order does not need the goods or the order buffer position is full, returning the container to the warehouse according to the reverse path of the original line; seventhly, picking the next goods until the current order is picked; and eighthly, judging whether the batch of orders are sorted or not, if not, returning to the step two, and the process is shown in figure 2.
In the four-way vehicle picking system, the four-way vehicle can carry out cross-roadway operation in the horizontal direction and can also carry out cross-floor operation with a lifting machine in the vertical direction. The general order sorting method such as sequential picking can cause that containers frequently go out of a warehouse and increase equipment loss, and meanwhile, the four-way vehicle can frequently carry out roadway-crossing and layer-crossing operations to increase order picking time and reduce picking efficiency. In order to solve the problem, the embodiment of the disclosure firstly establishes an order sorting model of the coupling degree for a four-way vehicle sorting system, and then designs a coupling degree order sorting algorithm to perform sorting optimization on orders of all sorting tables in the system, thereby avoiding equipment loss and reducing resource idleness, simultaneously shortening order sorting time and improving order sorting efficiency.
All parameters and variables of this example are shown in table 1.
TABLE 1 variables and assumptions
The present embodiment assumes the following:
(1) each SKU is placed in one container and each container is fixed in position.
(2) The number of SKUs in each bin is sufficient to meet an order picking requirement.
(3) The four-way vehicle can carry out the operation of crossing the roadway and changing the layer, and can only transport one container at a time. The four-way vehicle is parked at the task completion position after completing the task.
(4) The picking platform picks the order, and the next order can be picked only when the current order is picked.
(5) The order buffer bits are the same for each picking station.
As shown in fig. 3, an order ranking optimization method of this embodiment includes:
step 1: considering order picking time and storage space constraint conditions, and constructing a coupling degree order sorting model by taking the minimum total time required for finishing order picking of the current batch as an objective function;
step 2: and solving the coupling degree order sequencing model and outputting the ordered orders.
In a specific implementation, the step of constructing the coupling degree order ranking model includes:
(1) firstly, calculating the time consumption of the four-way vehicle moving between the two storage positions, namely the time consumption t of the four-way vehicle from the storage position k to the storage position sks，tksThe calculation of (c) includes the following three cases:
if xk≠xsThen, then
tks＝(w1+2w2)|xk-xs|/v2+h(yk+ys)/v1+l(zk+zs)/v2 (1)
If xk＝xs,yk≠ysThen, then
tks＝h|yk-ys|/v1+l(zk+zs)/v2 (2)
If xk＝xs,yk＝ysThen, then
tks＝l|zk-zs|/v2 (3)
Wherein (x)k,yk,zk) And the number of the lane, the layer number and the column number of the storage position k are shown. For order i and order j, it takes a long time for the "four-way vehicle" to move between the storage location of the SKU contained in order i and the storage location of the SKU contained in order j as shown in equation (4).
Wherein iα,jβThe storage position of the alpha SKU of the order i and the storage position of the beta SKU of the order j, pi,pjFor the total number of SKUs contained in both orders i and j,
from order i for "four-way vehicleThe length of time it takes for the bin of the SKU to go to the bin of the betath SKU of order j.
(2) The transition time between SKU bins when order i and order j are picked is calculated for "four-way cars".
Suppose orders i and j contain SKU numbers p, respectivelyi,pjThus, the transition time between SKU bins when the "four-way vehicle" picks order i and order j is as shown in equation (5).
In the formula (5)
Is a variable from 0 to 1, and is,
indicating that the alpha th SKU in order i is the same as the beta SKU in order j,
the representation is different. Wherein α ═ 1, 2.. times.pi，β＝1,2,...,pj。
(3) Calculating the time spent in entering and exiting the warehouse when the order i and the order j are selected by the four-way vehicle
Due to the limited order buffer space, the warehouse entry and exit of the order i and the order j picked by the four-way vehicle are divided into the following two cases:
(ii) the same SKU number as order i and order j, i.e. degree of coupling τijGreater than the number m of temporary storage bits1I.e. tauij＞m1At this time, only the front m farther from the sorting table can be cached preferentially1Time for picking order i and order j to enter and exit warehouse by using four-way vehicle
As shown in equation (6).
In the formula (6), DijFor order i and order j contain the top m1A set of one and the same SKU,
it takes time for the "four-way vehicle" to go from the SKU # bin to the picking station for order i, as shown in equation (7).
(ii) the same SKU number as order i and order j, i.e. degree of coupling τijNot exceeding the number m of temporary storage bits1I.e. tauij≤m1In time, all the same SKU containers in order i and order j can be buffered in a temporary storage location to avoid secondary ex-warehouse. At this time, the time taken for the four-way vehicle to enter or exit the warehouse is also shown in the formula (6), but D is shown in the formulaijBecomes the set of all identical SKUs contained in order i and order j.
(4) The total time T taken to pick the batch of orders is calculated.
Suppose that
The order picking sequence of the picking station is
The total time taken to complete the batch of order picks, T, is shown as equation (8).
In the formula (8), the reaction mixture is,
for picking the first order, order V1Warehousing of contained SKUs is time consuming. The total number of times of warehousing can be simultaneously obtained as tauThe difference between the order picking SKU number and the total SKU amount of the two order buffer storages, as shown in equation (9).
In the formula (9), xijIs a variable from 0 to 1, xij1 indicates that order i contains SKUj, xij0 indicates that order i does not contain SKUj.
When the coupling degree of the order i and the order j SKU storage positions is large, the two orders are adjusted to be sequentially and adjacently picked, so that the repeated operation times of a four-way vehicle and a lifter can be reduced, the order picking time is finally shortened, and the operation efficiency of the automatic warehouse can be greatly improved.
And comprehensively considering the order picking time and the storage space constraint conditions, and obtaining an improved coupling degree order sorting model.
Objective function (10) is to minimize the total time required to complete the batch of order picks; the formula (11) represents the conversion time of picking two adjacent orders of 'four-way vehicles' for crossing floors and changing lanes; equation (12) represents the time for the four-way vehicle to pick two adjacent orders to and from the storage location and the picking station; equations (13), (14) represent the picking order relationship for picking SKUs in two adjacent orders,
indicating order ViMedium goods alpha and order Vi+1The beta in the medium is sorted in turn,
indicating that two SKUs are not sorted in sequence.
Considering the order quantity as n, the traversal time complexity of the problem when the order contains SKU as m is O (n)2Xm) for large orders (greater than 50) and large SKU numbers, this method does not allow an optimal solution in a limited time. Therefore, the present embodiment designs an improved coupling order ranking algorithm to solve the problem quickly.
In order to solve and analyze the above model, the following coupling degree order sorting algorithm is designed in the present embodiment. The solving algorithm flow is as follows:
(1) and calculating the order quantity of the sorting table to distribute the orders.
In a "four-way vehicle" picking system, the system assigns Q orders to n in turn2Individual sorting decks, qiRepresenting the number of orders allocated to the ith picking station:
in formula (15), the first n2-1 sorting decks are assigned in turn to
Individual order, remaining orders
All assigned to the n-th2A sorting table.
(2) And calculating the SKU coupling degree of the order to obtain a seed order, namely determining the first order picked by the picking station.
Suppose that
A sorting table is distributed to
Each order is as follows:
the specific method comprises the following steps:
calculating
Obtaining an order coupling degree matrix by using the same SKU number between two orders in each order, namely the coupling degree; obtaining the sum of the coupling degrees of each order and the rest orders; taking the order with the highest coupling degree with other orders as a seed order.
The method can avoid the condition that the coupling degree between two orders in the batch orders is large but the coupling degree with other orders is small, thereby reducing the times of 'four-way vehicle' roadway crossing and layer changing operation.
Sorting table
The ith order of (c) contains a SKU that can be expressed as a vector
Wherein xijIs a variable from 0 to 1, xij1 indicates that order i contains SKUj, xij0 indicates that order i does not contain SKUj. Therefore, all of
Each order contains a SKU represented as matrix X.
The coupling between order i and order j is shown as equation (17).
Therefore, the temperature of the molten metal is controlled,
the matrix of the degree of coupling between two orders in a batch of orders is shown as matrix a.
Based on the above derivation, the coupling degree between each order and the rest of the orders can be obtained as shown in formula (19).
Finally, calculating the coupling degree of the current order and the SKU of the residual orders to obtain the coupling degree taui'Q, the sum of the degrees of coupling with the remaining orders, i.e., τi'The largest order is the first order to pick, i.e., the seed order. Thus, the seed order is determined to be i ═ i, such that
(3) The picking order of the accompanying orders, i.e., the remaining orders except for the seed order, is determined.
The method for determining the accompanying order is as follows:
first, a long matrix T is calculated for the time taken for the four-way vehicle to move between the SKU storage location contained in order i and the SKU storage location contained in order jij。
Second, calculating SKU from order i by on-table operation methodTotal conversion time T 'of bin to SKU in order j'ijAnd order picking order.
In a second step of determining the companion order, the "four-way vehicle" conversion time T'ijThe on-table job calculation flow of (1) is specifically as follows:
finding a table TijThe minimum element in, match the current two SKUs in order i and order j, e.g.
Matching the alpha th SKU in the order i with the beta SKU in the order j as two SKUs successively picked by the orders i and j;
deleting the determined matching relation in the orders i and j, namely determining the SKUs in the continuous picking order;
thirdly, continue to look for the table TijMatching the next smallest element with a set of two corresponding SKUs in the orders i and j to serve as the next set of continuously picked SKUs in the orders i and j;
fourthly, repeating the steps until the SKU picking sequence in the two orders is completely determined;
obtaining the SKU matching relation and the SKU picking sequence of the two orders:
therefore, the transition time between SKU stock locations when "four-way vehicle" pick order i and order j is available is T'ij。
Thirdly, calculating the time consumed for entering and exiting the warehouse when the order i and the order j are selected by the four-way vehicle
And get it
The smallest order is the next pick.
In the third step of determining the accompanying order, the time spent in and out of the warehouse when the order i and the order j are picked by the four-way vehicle is firstly calculated
Then, calculating the coupling degree of the SKU storage positions of the remaining orders and the current order, namely the sum of the warehouse-in and warehouse-out time and the conversion time
Taking the order with the minimum coupling degree with the current order SKU storage position as the next picking order, namely taking the order j*To make
The final order picking order is obtained as:
finally, the third step is repeated until all order picking orders are determined.
In this embodiment, the picking operation activity in the "four-way vehicle" picking system is considered, and the number of SKUs is 100, the number of lanes, the number of layers, and the number of columns are 5,5, and 4 in sequence. The number of order buffer positions is 2, and the number of shuttle vehicles is 3.
The four-way vehicle and the speed of the hoister are as follows: v. of2＝5m/s,v1The system performance under the following three order ranking strategies was analyzed and compared at 3 m/s:
(1) and S1, sorting in sequence, and directly sorting the original orders without any sorting optimization.
(2) And S2, an SKU coupling degree algorithm, an order sorting strategy based on the two order SKU coupling degrees, and sorting the batch orders according to the size of the two SKU coupling degrees.
(3) S3, the improved coupling degree algorithm is the algorithm provided by the embodiment, and the batch orders are sorted according to the coupling degree of the SKU storage positions.
The order picking times under the three order sorting strategies are respectively calculated by randomly generating orders with the order quantities of 10,20,30,40,50,60,70,80,90 and 100 in sequence. To avoid the chance of single outcome, 10 sets of calculations were repeated and averaged to obtain the results shown in table 2.
TABLE 2 picking times for three sort strategies under different order amounts
The order picking times under the three order sorting strategies increase gradually as the order batch increases, and the S1 strategy, that is, the order picking time for sequential picking, is much higher than the order picking times of S2 and S3. Meanwhile, the number of times of warehouse entry and warehouse exit under the condition of S3 is always greater than that of S2, but the picking time is always less than that of S2. By comparing the order completion time differences under the two strategies, it can be known that, as the order batch size increases, the order completion time difference between the strategy S3 under the strategy S3 and the strategy S2 under the strategy S2 gradually increases, and when the order quantity is 90, the difference between the two strategies is 518.7S, and the shortest order picking time cannot be guaranteed due to the fact that the lowest warehouse entry and exit times are found.
Thus, for picking of large batches of orders, S3 may better shorten order picking times compared to the S2 and S1 strategies. For a large-scale automatic warehouse, when the daily order quantity reaches the tens of millions of levels, the strategy can greatly shorten the order picking time and improve the system picking efficiency. The number of times of warehouse entry and exit in the strategy S3 is kept low, and the strategy S2 is better than the strategy S1.
Sequentially generating orders with SKU numbers of 10,20,30,40,50,60,70,80,90 and 100 by random strategies, and calculating order picking time under the three strategies; the experiment was repeated 10 times, and the results of 10 groups were averaged to obtain the results shown in table 3. The S3 strategy is the shortest to place order picking time, and the S2 strategy is still superior to the S1 strategy. However, as the number of order SKUs increases, the order picking time difference between the S2 strategy and the S1 strategy decreases, and the order picking time difference between the S3 strategy and the S2 strategy tends to stabilize. This is because the number of SKUs not coupled between two orders is gradually increased along with the increase of the number of SKUs in the order, and the number of coupled SKUs is relatively decreased, so that the order picking time cannot be reduced well by simply considering the degree of coupling.
TABLE 3 picking times for three sort strategies under different order structures
Analysis three strategic order picking time changes as the number of "four-way cars" increases from 1 to 11 are shown in table 4. The order picking time for the S3 strategy is the shortest of the three strategies, regardless of the number of "four-way cars" that varies. Also the S2 strategy is consistently superior to the S1 strategy. When the number of the four-way vehicles is increased to 9, the order picking time of the three strategies tends to be stable and does not change any more. This is because the system has reached the limit, and if the number of the four-way vehicles is increased, the increased four-way vehicles are left unused, the picking time cannot be shortened, and the system efficiency cannot be improved. Meanwhile, the number of times of entering and exiting the garage is reduced along with the increase of the number of the four-way vehicles, but the change trend is weak.
TABLE 4 picking times for three sort strategies with different "four-way cars" quantities
In order to shorten the order picking time and improve the efficiency of a four-way vehicle picking system, the optimization goal of the order sorting optimization model provided by the embodiment of the disclosure can be simplified into the reduction of the round trip time of the four-way vehicle between storage positions. When the total order amount is greater than 50, the model may be determined to be an NP-Hard problem. In order to solve the model, the proposed coupling degree order sorting algorithm sorts orders according to the order storage degree coupling degree, determines the order sorting sequence of the SKUs in the orders and minimizes the order sorting time. And the calculation result shows that the order sorting optimization method of the embodiment can effectively shorten the order picking time and improve the picking system efficiency.
An order sorting optimization device of the embodiment comprises a memory and an order sorting optimization processor; the order ranking optimization processor is configured to perform the following steps:
considering order picking time and storage space constraint conditions, and constructing a coupling degree order sorting model by taking the minimum total time required for finishing order picking of the current batch as an objective function;
solving a coupling degree order sequencing model and outputting an order which completes sequencing;
the process for solving the coupling degree order sequencing model comprises the following steps:
distributing the order to a sorting table to obtain the order quantity of the sorting table;
selecting the order with the highest coupling degree with other orders from the orders of the corresponding sorting table as a seed order;
determining a picking order accompanying the order according to the minimum sum of the conversion time and the time spent in and out of the warehouse; wherein the accompanying order is the remaining order except the seed order.
In a specific implementation, in the order sorting optimization processor, the precondition of the coupling degree order sorting model is as follows:
(1) each article item is placed in a container, and the position of each container is fixed;
(2) the quantity of the items in each container at least reaches a preset value, and the requirement of one order picking can be met;
(3) the four-way vehicle can carry out roadway crossing and layer changing operation, and can only convey one container each time; the four-way vehicle is parked at a task completion position after completing the task;
(4) the picking platform picks according to the order, and the next order can be picked only when the current order picking is finished;
(5) the order buffer bits are the same for each picking station.
Specifically, in the order sorting optimization processor, the total time required for completing the picking of the current batch of orders is equal to the sum of the switching time for picking two adjacent orders of the four-way vehicle to cross floors and change lanes and the time for picking two adjacent orders of the four-way vehicle to go to and from the storage positions and the picking platform.
Specifically, the process of selecting, in the order sorting optimization processor, an order with the highest degree of coupling with the remaining orders in the corresponding picking station orders as a seed order includes:
calculating the number of items of the same article between two orders in the corresponding picking platform order, namely the coupling degree, and obtaining an order coupling degree matrix;
and calculating the sum of the coupling degrees of each order and the rest orders, and taking the order with the highest coupling degree with the rest orders from the corresponding picking station orders as a seed order.
In one embodiment, the process of determining, in the order sorting optimization processor, a picking order associated with an order based on a minimum sum of a conversion time and an in-out time includes:
calculating a time length matrix consumed by the four-way vehicle to move between the article storage position contained in one order and the article storage position contained in the other order;
calculating the total conversion time and order picking sequence of the four-way vehicle from the storage position of the item in one order to the storage position of the item in another order by an on-table operation method;
and selecting the order corresponding to the minimum sum of the time consumed for picking the order from the four-way vehicle to the warehouse and the total conversion time from the storage position of the item in one order to the storage position of the item in the other order as the next picking order until all the order picking sequences are determined.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
Although the present disclosure has been described with reference to specific embodiments, it should be understood that the scope of the present disclosure is not limited thereto, and those skilled in the art will appreciate that various modifications and changes can be made without departing from the spirit and scope of the present disclosure.
Claims (8)
1. An order ranking optimization method, comprising:
considering order picking time and storage space constraint conditions, and constructing a coupling degree order sorting model by taking the minimum total time required for finishing order picking of the current batch as an objective function;
the step of constructing the coupling degree order ranking model comprises the following steps:
(1) firstly, calculating the time consumed by moving the four-way vehicle between two storage positions;
(2) calculating the transition time between SKU stock locations when the four-way vehicle picks one order and another;
(3) calculating the time consumed for entering and leaving the warehouse when the four-way vehicle selects one order and the other order;
(4) calculating the total time for picking the batch of orders;
solving a coupling degree order sequencing model and outputting an order which completes sequencing;
the process for solving the coupling degree order sequencing model comprises the following steps:
distributing the order to a sorting table to obtain the order quantity of the sorting table;
selecting the order with the highest coupling degree with other orders from the orders of the corresponding sorting table as a seed order;
the process of selecting the order with the highest coupling degree with other orders in the corresponding sorting table orders as the seed order comprises the following steps:
calculating the number of items of the same article between two orders in the corresponding picking platform order, namely the coupling degree, and obtaining an order coupling degree matrix;
calculating the sum of the coupling degrees of each order and the rest orders, and taking the order with the highest coupling degree with the rest orders from the corresponding sorting table orders as a seed order; determining a picking order accompanying the order according to the minimum sum of the conversion time and the time spent in and out of the warehouse; wherein the accompanying order is the remaining order except the seed order.
2. The order ranking optimization method of claim 1, wherein the preconditions of the coupling degree order ranking model are:
(1) each article item is placed in a container, and the position of each container is fixed;
(2) the quantity of the items in each container at least reaches a preset value, and the requirement of one order picking can be met;
(3) the four-way vehicle can carry out roadway crossing and layer changing operation, and can only convey one container each time; the four-way vehicle is parked at a task completion position after completing the task;
(4) the picking platform picks according to the order, and the next order can be picked only when the current order picking is finished;
(5) the order buffer bits are the same for each picking station.
3. The order ordering optimization method of claim 1, wherein the total time required to complete the picking of the current batch of orders is equal to the sum of the transition time between "four-way vehicle" cross-floor and lane changing for picking two adjacent orders and the time between "four-way vehicle" picking two adjacent orders to and from the stocker and the picking station.
4. The method of order sort optimization of claim 1, wherein the process of determining a picking order for the accompanying order based on the minimum sum of conversion time and in-out time includes:
calculating a time length matrix consumed by the four-way vehicle to move between the article storage position contained in one order and the article storage position contained in the other order;
calculating the total conversion time and order picking sequence of the four-way vehicle from the storage position of the item in one order to the storage position of the item in another order by an on-table operation method;
and selecting the order corresponding to the minimum sum of the time consumed for picking the order from the four-way vehicle to the warehouse and the total conversion time from the storage position of the item in one order to the storage position of the item in the other order as the next picking order until all the order picking sequences are determined.
5. An order sorting optimization device is characterized by comprising a memory and an order sorting optimization processor; the order ranking optimization processor is configured to perform the following steps:
considering order picking time and storage space constraint conditions, and constructing a coupling degree order sorting model by taking the minimum total time required for finishing order picking of the current batch as an objective function;
the step of constructing the coupling degree order ranking model comprises the following steps:
(1) firstly, calculating the time consumed by moving the four-way vehicle between two storage positions;
(2) calculating the transition time between SKU stock locations when the four-way vehicle picks one order and another;
(3) calculating the time consumed for entering and leaving the warehouse when the four-way vehicle selects one order and the other order;
(4) calculating the total time for picking the batch of orders;
solving a coupling degree order sequencing model and outputting an order which completes sequencing;
the process for solving the coupling degree order sequencing model comprises the following steps:
distributing the order to a sorting table to obtain the order quantity of the sorting table;
selecting the order with the highest coupling degree with other orders from the orders of the corresponding sorting table as a seed order;
in the order sorting optimization processor, the process of selecting the order with the highest degree of coupling with the other orders in the corresponding picking station orders as the seed order comprises the following steps:
calculating the number of items of the same article between two orders in the corresponding picking platform order, namely the coupling degree, and obtaining an order coupling degree matrix;
calculating the sum of the coupling degrees of each order and the rest orders, and taking the order with the highest coupling degree with the rest orders from the corresponding sorting table orders as a seed order;
determining a picking order accompanying the order according to the minimum sum of the conversion time and the time spent in and out of the warehouse; wherein the accompanying order is the remaining order except the seed order.
6. The order ranking optimization device according to claim 5, wherein in the order ranking optimization processor, the preconditions of the coupling degree order ranking model are:
(1) each article item is placed in a container, and the position of each container is fixed;
(2) the quantity of the items in each container at least reaches a preset value, and the requirement of one order picking can be met;
(3) the four-way vehicle can carry out roadway crossing and layer changing operation, and can only convey one container each time; the four-way vehicle is parked at a task completion position after completing the task;
(4) the picking platform picks according to the order, and the next order can be picked only when the current order picking is finished;
(5) the order buffer bits are the same for each picking station.
7. The order sorting optimization device of claim 5, wherein in the order sorting optimization processor, the total time required to complete the picking of the current batch of orders is equal to the sum of the transition time to pick two adjacent orders "four-way cars" across floors and lanes and the time to pick two adjacent orders "four-way cars" to and from the stocker and the picking station.
8. The order sort optimization apparatus of claim 5, wherein the process of determining, in the order sort optimization processor, the picking order for accompanying orders based on the minimum sum of the conversion time and the in-out time includes:
calculating a time length matrix consumed by the four-way vehicle to move between the article storage position contained in one order and the article storage position contained in the other order;
calculating the total conversion time and order picking sequence of the four-way vehicle from the storage position of the item in one order to the storage position of the item in another order by an on-table operation method;
and selecting the order corresponding to the minimum sum of the time consumed for picking the order from the four-way vehicle to the warehouse and the total conversion time from the storage position of the item in one order to the storage position of the item in the other order as the next picking order until all the order picking sequences are determined.
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