CN112132642A - Order combination method and device based on multi-objective optimization - Google Patents
Order combination method and device based on multi-objective optimization Download PDFInfo
- Publication number
- CN112132642A CN112132642A CN201910550365.4A CN201910550365A CN112132642A CN 112132642 A CN112132642 A CN 112132642A CN 201910550365 A CN201910550365 A CN 201910550365A CN 112132642 A CN112132642 A CN 112132642A
- Authority
- CN
- China
- Prior art keywords
- order
- order set
- orders
- preset
- added
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0633—Lists, e.g. purchase orders, compilation or processing
- G06Q30/0635—Processing of requisition or of purchase orders
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
Abstract
The invention discloses an order combination method and device based on multi-objective optimization, and relates to the technical field of computers. One specific embodiment of the method: acquiring orders to generate an order set; allocating one order in an order set to a preset order set so as to determine a logic area of a current order set according to the item type of the order; distributing other unallocated orders in the order set which can be covered by the logic area of the current order set to a preset order set which can be added; and sequencing according to the roadway and the storage position information which can be added into the order set order so as to sequentially distribute the sequenced orders into the collection list until the preset collection list upper limit requirement is met. Therefore, the method and the device can solve the problems of low efficiency of combining orders and poor quality of the obtained aggregate in the prior art.
Description
Technical Field
The invention relates to the technical field of computers, in particular to an order combination method and device based on multi-objective optimization.
Background
At present, in the e-commerce environment, when a large number of orders appear, a warehousing department combines the orders to pick the orders according to the positions of the articles of the orders, and the reasonable collection list can accelerate the picking speed and reduce the labor cost.
In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art:
the general purpose of combining orders is to minimize the overall picking difficulty, and in actual work, the orders are basically combined manually by experienced staff, or some simpler order combination method is adopted, which considers the single factor and makes it difficult to obtain an efficient collection sheet.
Disclosure of Invention
In view of this, embodiments of the present invention provide an order combination method and apparatus based on multi-objective optimization, which can solve the problems of low order combination efficiency and poor quality of an obtained set in the prior art.
To achieve the above object, according to an aspect of the embodiments of the present invention, there is provided an order combination method based on multi-objective optimization, including obtaining orders to generate an order set; allocating one order in an order set to a preset order set so as to determine a logic area of a current order set according to the item type of the order; distributing other unallocated orders in the order set which can be covered by the logic area of the current order set to a preset order set which can be added; and sequencing according to the roadway and the storage position information which can be added into the order set order so as to sequentially distribute the sequenced orders into the collection list until the preset collection list upper limit requirement is met.
Optionally, if the preset collection sheet upper limit requirement is not met and the addable order set is empty after the sequential allocation, one order is selected from the remaining orders in the order set and allocated to the collection sheet, and the logic area corresponding to the order is added to the logic area set of the collection sheet, so as to allocate other unallocated orders which can be covered by the logic area of the current collection sheet in the order set to the addable order set.
Optionally, acquiring the order to generate the order set includes:
acquiring and classifying orders to generate a single order set and a non-single order set;
the method comprises the following steps of sequencing according to roadway and storage position information which can be added into orders in an order set so as to sequentially distribute the sequenced orders into a collection list until the preset collection list upper limit requirement is met:
for any single order which can be added into the single order set, calculating the picking difficulty after the order is distributed to the single order set, sequencing the single orders from small to large according to the picking difficulty, and distributing the single orders to the single order set in sequence until the preset upper limit requirement of the single order set is met; the picking difficulty is the sum of the product of the optimal path length of the distributed aggregate single roadway and the first difficulty coefficient and the product of the optimal path length of the distributed aggregate single storage position and the second difficulty coefficient;
and calculating the difference between the picking difficulty and the logical area number multiplied by a third coefficient after the non-single order can be added into the non-single order set, sorting the non-single orders from small to large according to the difference, and sequentially allocating the non-single orders to the non-single order set until the preset upper limit requirement of the non-single order set is met.
Optionally, allocating one order in the order set to a preset order set includes:
sorting any non-single order in the non-single order set from large to small according to the comprehensive numerical values of the number of logic areas, the number of lanes and the number of storage digits; wherein, the comprehensive value is the sum of the logical area number multiplied by 100 and the lane number multiplied by 10 and the storage digit number;
and distributing the sorted first non-single order to a preset non-single collection list.
In addition, according to an aspect of the embodiment of the present invention, an order combining apparatus based on multi-objective optimization is provided, which includes an obtaining module, configured to obtain an order to generate an order set; the system comprises a preprocessing module, a data processing module and a data processing module, wherein the preprocessing module is used for distributing an order in an order set to a preset order set so as to determine a logic area of a current order set according to the article type of the order; distributing other unallocated orders in the order set which can be covered by the logic area of the current order set to a preset order set which can be added; and the distribution module is used for sequencing according to the roadway and the storage position information which can be added into the order set order so as to distribute the sequenced orders into the collection list in sequence until the preset collection list upper limit requirement is met.
Optionally, the preprocessing module is further configured to:
if the preset collection sheet upper limit requirement is not met and the addable order set is empty after the sequential allocation, one order is selected from the remaining orders in the order set and allocated to the collection sheet, and the logic area corresponding to the order is added to the logic area set of the collection sheet, so that other unassigned orders in the order set which can be covered by the logic area of the current collection sheet are allocated to the addable order set.
Optionally, the obtaining module obtains the order to generate an order set, including:
acquiring and classifying orders to generate a single order set and a non-single order set;
the distribution module sorts according to the roadway and the storage position information which can be added into the order centralized order, so as to distribute the sorted order to the collection list in sequence until the preset collection list upper limit requirement is met, and the method comprises the following steps:
for any single order which can be added into the single order set, calculating the picking difficulty after the order is distributed to the single order set, sequencing the single orders from small to large according to the picking difficulty, and distributing the single orders to the single order set in sequence until the preset upper limit requirement of the single order set is met; the picking difficulty is the sum of the product of the optimal path length of the distributed aggregate single roadway and the first difficulty coefficient and the product of the optimal path length of the distributed aggregate single storage position and the second difficulty coefficient;
and calculating the difference between the picking difficulty and the logical area number multiplied by a third coefficient after the non-single order can be added into the non-single order set, sorting the non-single orders from small to large according to the difference, and sequentially allocating the non-single orders to the non-single order set until the preset upper limit requirement of the non-single order set is met.
Optionally, the allocating, by the preprocessing module, one order in the order set to a preset order set includes:
sorting any non-single order in the non-single order set from large to small according to the comprehensive numerical values of the number of logic areas, the number of lanes and the number of storage digits; wherein, the comprehensive value is the sum of the logical area number multiplied by 100 and the lane number multiplied by 10 and the storage digit number;
and distributing the sorted first non-single order to a preset non-single collection list.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any of the multi-objective optimization-based order combining embodiments described above.
According to another aspect of the embodiments of the present invention, there is also provided a computer readable medium, on which a computer program is stored, which when executed by a processor, implements the method of any of the above embodiments of order combination based on multi-objective optimization.
One embodiment of the above invention has the following advantages or benefits: the invention generates an order set by acquiring orders; allocating one order in an order set to a preset order set so as to determine a logic area of a current order set according to the item type of the order; distributing other unallocated orders in the order set which can be covered by the logic area of the current order set to a preset order set which can be added; and sequencing according to the roadway and the storage position information which can be added into the order set order so as to sequentially distribute the sequenced orders into the collection list until the preset collection list upper limit requirement is met. Therefore, the invention can obtain the collection list with high saturation by considering the three-dimensional positioning information of the order logic area, the roadway and the storage position, and simultaneously greatly improves the efficiency of order combination.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a schematic diagram of a main flow of an order combination method based on multi-objective optimization according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a main flow of an order combination method based on multi-objective optimization according to another embodiment of the present invention;
FIG. 3 is a schematic diagram of a main flow of an order combination method based on multi-objective optimization according to another embodiment of the present invention;
FIG. 4 is a schematic diagram of the major modules of an order combining apparatus based on multiobjective optimization according to an embodiment of the present invention;
FIG. 5 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 6 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
FIG. 1 is a schematic diagram of a main flow of a multi-objective optimization-based order combination method according to a first embodiment of the present invention, which may include:
step S101, obtaining orders to generate an order set.
Preferably, the orders are captured and categorized to generate a single order set and a non-single order set. The non-single order set comprises a multi-non-order set and a multi-order set. The single order is a single order according to the number of the items 1. The multiple non-orders refer to the situation that if one order has multiple articles and is in the same logic area. The multi-order is that one order has a plurality of articles and is not in the same logic area.
Step S102, one order in an order set is distributed to a preset order set so as to determine a logic area of the current order set according to the item type of the order; and distributing other unallocated orders in the order set which can be covered by the logic area of the current order set to a preset addable order set.
Preferably, for the generated single-piece order set, step S102 is to allocate one single-piece order in the single-piece order set to a preset single-piece order set, and allocate other single-piece orders in the single-piece order set that are not allocated and can be covered by the logic area of the single-piece order set to a preset joinable single-piece order set.
In addition, for the generated non-single-piece order set, in step S102, one non-single-piece order in the non-single-piece order set is allocated to a preset non-single-piece order set, and other non-single-piece orders in the non-single-piece order set, which are not allocated and can be covered by the logic area of the non-single-piece order set, are allocated to a preset joinable non-single-piece order set.
Preferably, any non-single order in the non-single order set is sorted from large to small according to the comprehensive numerical values of the number of logic areas, the number of lanes and the number of storage digits, and then the sorted first non-single order is distributed to a preset non-single order set. Wherein, the integrated value is the logical area number multiplied by 100 plus the lane number multiplied by 10 plus the storage bit number.
And S103, sequencing according to the roadway and the storage position information which can be added into the order set order, and sequentially distributing the sequenced orders into the collection list until the preset collection list upper limit requirement is met.
Preferably, for any single order in the addable single order set, the picking difficulty after the order is distributed to the single order set is calculated, the single orders are sorted from small to large according to the picking difficulty and are distributed to the single order set in sequence until the preset upper limit requirement of the single order set is met. And the picking difficulty is the sum of the product of the optimal path length of the distributed aggregate single roadway and the first difficulty coefficient and the product of the optimal path length of the distributed aggregate single storage position and the second difficulty coefficient.
Preferably, for any non-single order in the non-single order set which can be added, the difference value between the picking difficulty and the logical area number multiplied by the third coefficient after the non-single order is distributed to the non-single order set is calculated, the non-single orders are sorted from small to large according to the difference value and are sequentially distributed to the non-single order set until the preset non-single order set upper limit requirement is met.
As still another example, as shown in FIG. 2, the order combination method based on multi-objective optimization may include:
step S201, an order is acquired to generate an order set.
Preferably, the orders are captured and categorized to generate a single order set and a non-single order set. The non-single order set comprises a multi-non-order set and a multi-order set. The single order is a single order according to the number of the items 1. The multiple non-orders refer to the situation that if one order has multiple articles and is in the same logic area. The multi-order is that one order has a plurality of articles and is not in the same logic area.
Step S202, one order in the order set is allocated to a preset order set, and other orders that are not allocated and can be covered by the logic area of the order set are allocated to a preset order set that can be added.
Preferably, for the generated single-piece order set, step S202 is to allocate one single-piece order in the single-piece order set to a preset single-piece order set, and allocate other single-piece orders in the single-piece order set that are not allocated and can be covered by the logic area of the single-piece order set to a preset joinable single-piece order set.
In addition, for the generated non-single-piece order set, in step S202, one non-single-piece order in the non-single-piece order set is allocated to a preset non-single-piece order set, and other non-single-piece orders in the non-single-piece order set, which are not allocated and can be covered by the logic area of the non-single-piece order set, are allocated to a preset joinable non-single-piece order set.
Preferably, any non-single order in the non-single order set is sorted from large to small according to the comprehensive numerical values of the number of logic areas, the number of lanes and the number of storage digits, and then the sorted first non-single order is distributed to a preset non-single order set. Wherein, the integrated value is the logical area number multiplied by 100 plus the lane number multiplied by 10 plus the storage bit number.
And S203, sequencing according to the roadway and the storage position information which can be added into the order set order, and sequentially distributing the sequenced orders into the collection list until the preset collection list upper limit requirement is met.
Preferably, for any single order in the addable single order set, the picking difficulty after the order is distributed to the single order set is calculated, the single orders are sorted from small to large according to the picking difficulty and are distributed to the single order set in sequence until the preset upper limit requirement of the single order set is met. And the picking difficulty is the sum of the product of the optimal path length of the distributed aggregate single roadway and the first difficulty coefficient and the product of the optimal path length of the distributed aggregate single storage position and the second difficulty coefficient.
Preferably, for any non-single order in the non-single order set which can be added, the difference value between the picking difficulty and the logical area number multiplied by the third coefficient after the non-single order is distributed to the non-single order set is calculated, the non-single orders are sorted from small to large according to the difference value and are sequentially distributed to the non-single order set until the preset non-single order set upper limit requirement is met.
Step S204, judging whether the added order set is empty, if so, performing step S205, otherwise, generating a new order set, sequentially distributing the remaining orders in the added order set to the new order set in sequence until the preset upper limit requirement of the order set is met, and then, executing step S204 in a circulating manner, namely, judging whether the added order set is empty.
Step S205 determines whether the order set is empty, if so, step S208 is performed, otherwise, step S206 is performed.
Step S206, judging whether the collection list meets the upper limit requirement, if so, returning to step S202, otherwise, performing step S207.
In an embodiment, if the current assembly sheet meets the upper limit requirement, the order cannot be reallocated, and it is necessary to return to step S202 to set a new assembly sheet.
Step S207, selecting one order from the remaining orders in the order set to allocate to the collection sheet, adding the logical area corresponding to the order to the logical area set of the collection sheet, so as to allocate other orders that are not allocated and can be covered by the logical area of the current collection sheet in the order set to the addable order set, and returning to step S203.
In step S208, all the collection sheets are output.
As another example, there may be several items in a warehouse from which customers order and need to supply items over a period of time. Assuming that the warehouse items are enough to satisfy all orders in the time period, the warehouse needs to pick, pack and deliver all items required by the orders, wherein all orders need to be grouped into a plurality of collection sheets, and one collection sheet is divided into a plurality of task sheets for picking. That is, the orders and the task orders are grouped to maximize overall picking efficiency under order constraints of the orders and the task orders. FIG. 3 is a schematic diagram of a main flow of a multi-objective optimization-based order combination method according to another embodiment of the present invention, which may include:
step S301, orders are obtained and classified to generate a single-piece order set and a non-single-piece order set.
In an embodiment, the orders obtained are divided into two categories: single-piece order collections and non-single-piece (multiple non-and multiple-combination) order collections. The non-single order set comprises a multi-non-order set and a multi-order set. The single order is a single order according to the number of the items 1. The multiple non-orders refer to the situation that if one order has multiple articles and is in the same logic area. The multi-order is that one order has a plurality of articles and is not in the same logic area.
In addition, the logical area refers to the category of a kind of articles, such as clothing, fresh fruits, digital electronics, and the like.
Step S302, acquiring an order set, determining whether the order set is a single-order set, if so, performing step S303 to step S309, otherwise, performing step S310 to step S318.
Step S303, generating an empty single-piece collection list, and distributing one single-piece order in the single-piece order collection to a new single-piece collection list.
In an embodiment, an empty new singleton collection singleton O is generated1Optionally selecting a single order to be distributed to the O1In (1).
In step S304, other unallocated single-piece orders in the single-piece order set that can be covered by the logic area of the current single-piece order set are allocated to a preset joinable single-piece order set.
In an embodiment, the order set A may be added to other unassigned and potentially overlayed logical areas of the current order set1. Wherein, the logical area of the current order sheet collection can be the logical area of the order sheet allocated therein.
Step S305, calculating the picking difficulty of any single order which can be added into the single order set and sorting the order from small to large if the order is distributed to the current single order set, and distributing the order to the current single order set in sequence until the preset upper limit requirement of the single order set is met.
In an embodiment, for any single piece order d ∈ A1Calculate to put the order sheet inSingle piece set single O1And sorting all the obtained picking difficulties from small to large, and sequentially distributing the single order to the current single collection list until the preset collection list upper limit requirement is met. Preferably, for a non-empty aggregation sheet, the picking difficulty after a new order is allocated to the aggregation sheet is defined as the optimal path length of the allocated aggregation sheet lane x the first difficulty coefficient + the optimal path length of the allocated aggregation sheet storage location x the second difficulty coefficient, for example, the first difficulty coefficient is 10 and the second difficulty coefficient is 1. And if the two lanes are not in the same lane, the optimal path length of the storage position is not considered. In addition, the optimal path length of the roadway and the optimal path length of the storage bit may be shortest path lengths of the roadway and the storage bit.
It should be noted that the preset upper limit requirement of the single-piece collection list includes an upper limit of the order number, an upper limit of the item number, an upper limit of the weight, an upper limit of the item number, an upper limit of the volume, and the like of the collection list. Wherein, a task list refers to the picking task for a logic area, that is, one task list only corresponds to one logic area.
Step S306, determining whether the joinable single-order set is empty, if yes, performing step S307, otherwise, generating a new single-order set, sequentially allocating the remaining single-orders in the joinable single-order set to the new single-order set in sequence until the preset upper limit requirement of the single-order set is met, and then performing step S306 in a recycling manner.
In an embodiment, a singleton order set A may be added if empty description is available1The orders in (1) are all distributed into the single-piece aggregate sheet, and if the orders are not null descriptions, the single-piece order set A can be added1There are orders not allocated to the single-piece aggregated sheet, because the current single-piece aggregated sheet has satisfied the upper limit requirement, a new empty single-piece aggregated sheet needs to be set, so as to add the available single-piece order set A1The remaining orders are allocated.
Step S307, determine whether the single-piece order set is empty, if yes, go to step S318, otherwise go to step S308.
Step S308, judging whether the current single-piece collection list meets the upper limit requirement, if so, returning to the step S303, and if not, performing the step S309.
In the embodiment, if the current order collection sheet meets the upper limit requirement, the order cannot be reallocated, and it is necessary to return to step S303 to set a new empty order collection sheet.
Step S309, selecting one single order from the rest single orders in the single order set to distribute to the single order set, adding the logic area corresponding to the single order into the logic area set of the current single order set, and returning to the step S304.
In an embodiment, for the case that the orders which can be covered under the current logical area are not saturated after all the orders are inserted into the single-piece aggregate list (the upper limit is not reached), for all other orders in the single-piece order set, the order number of each order in the single-piece order set corresponding to the logical area added after the order is inserted into the single-piece aggregate list is calculated, and the logical area with the largest order number is selected to be added into the logical area set of the current single-piece aggregate list.
Step S310, the non-single-piece orders in the non-single-piece order set are sorted from large to small according to the comprehensive numerical values of the number of the logic areas, the number of the lanes and the number of the storage digits.
In an embodiment, the order sorting is a comprehensive value based on three-dimensional information of the number of logical zones, the number of lanes and the number of storage positions of the orders, and further defines that the comprehensive value of one order is the number of logical zones × 100+ the number of lanes × 10+ the number of storage positions, and then sorts L for all orders according to the obtained values from large to small. The number of logic areas refers to several logic areas, the number of lanes refers to several lanes, and the number of storage bits refers to several storage bits.
Step S311 is to generate an empty non-singleton assembly list and assign the first non-singleton order to the non-singleton assembly list.
In step S312, other unallocated non-single-piece orders that can be covered by the logic area of the current non-single-piece assembly list are allocated to a preset joinable non-single-piece order set.
In an embodiment, the logical area of the non-singleton aggregation sheet may be the logical area of the non-singleton order that has been allocated thereto.
In an embodiment, the third coefficient is obtained by training through massive historical data, and is arranged in front of the large number of the logical areas. The difference value of the picking difficulty and the number of the logic areas multiplied by a third coefficient is the picking difficulty-number of the logic areas multiplied by the third coefficient.
In addition, the preset non-single-piece collection list upper limit requirements comprise an order number upper limit and an article number upper limit of the collection list, and a weight upper limit, an article number upper limit and a volume upper limit of the task list. Wherein, a task list refers to the picking task for a logic area, that is, one task list only corresponds to one logic area.
Step S314, determining whether the joinable non-single-piece order set is empty, if so, performing step S315, otherwise, generating a new non-single-piece order set, sequentially allocating the remaining non-single-piece orders in the joinable non-single-piece order set to the new non-single-piece order set in sequence until the preset upper limit requirement of the non-single-piece order set is met, and then performing step S314 in a circulating manner.
In an embodiment, if the joinable non-order set is not empty, indicating that the current non-order set has met the predetermined upper limit requirement, and there are no non-order orders in the joinable non-order set that have not been placed in the current non-order set, only an empty new non-order set can be generated, and the remaining orders in the joinable non-order set are allocated.
Step S315, determine whether the non-single-piece order set is empty, if yes, go to step S318, otherwise go to step S316.
Step S316, determining whether the current non-singleton collection sheet meets the upper limit requirement, if yes, returning to step S311, otherwise, performing step S317.
Step S317, selecting one non-single order from the remaining non-single orders in the non-single order collection to allocate to the non-single order collection, adding the logical area corresponding to the non-single order into the logical area collection of the current non-single order collection, and returning to step S312.
In the embodiment, for all other orders in the non-single order set, the order number in the non-single order set corresponding to the logic area added after each order is inserted into the non-single order set is calculated, and the logic area with the largest order number is selected to be added into the logic area set of the current non-single order set.
And step S318, merging all the single-piece collection lists and the non-single-piece collection lists for output.
As a specific example, assuming that the upper limit of the order number of the single-piece collective list or the non-single-piece collective list is required to be not more than 3, the number of articles of the task list is not more than 5, and the distance between the lanes is simply defined as the difference between the lane numbers. For example, 10 orders in a time period require a group order as shown in table 1.
Table 1: order information table
It can be seen that orders 1, 2, 4, 5, 7, 8, 9, 10 are all single-piece orders, 3 are multiple non-orders, and 6 are multiple orders.
Processing the single order: first, define a new singleton assembly single O1The orders assigned to the single-piece collection sheet are 4, 5 and 7, and the picking difficulty assigned to the single-piece collection sheet is calculated respectively, so as to obtain the ranks 7, 5 and 4. So that the insert 7, 5, respectively, finds exactly equal to the task order ceiling, and exits the singleton collection sheet. Creating a new singleton Collection sheet O2Each of the orders 8, 9, 10 is found to be assigned to the sheet collection sheet, and the difficulty of picking after adding the order is calculated and the order 8, 10, 9 is obtained, so that the insert 8, 10 is found to be exactly equal to the upper limit of the order. Newly building a single piece set single O3When the calculation can be assigned to this singleton set {4}, the calculation can now be assigned to this singleton setFor a single order, it is found that no order can be allocated, at this time, the logical area set (currently { JH0}) of the assembly list needs to be added, and since the remaining unallocated single-piece orders are only 9, that is, the logical area that can be added is only { JH1}, the logical area set { JH0, JH1} of the assembly list is obtained, and 9 is allocated to the single-piece assembly list. And finishing processing all the single orders.
For the non-single-piece orders, only 3 and 6 are needed, the orders are obtained according to the logical area number from large to small (6, 3), and a non-single-piece assembly list O is newly established4The unallocated orders that are covered by the logical region of the non-singleton order and that can be allocated to, are computed, resulting in 3 that can be allocated to the current non-singleton order.
Thereby obtaining all the collection sheets as O1，O2，O3，O4。
Thus, according to the various embodiments described above, the present invention is based on the optimization of order three-dimensional positioning information (logical zones, lanes, bins) aggregated sheets with the goal of minimizing the overall picking difficulty and maximizing the aggregated sheet saturation as much as possible. In addition, because the task order is the task of actual picking, the collection order and the task order are not required to be processed separately, and the invention considers the optimization under the constraint of the task order aiming at the inseparable relationship between the collection order and the task order, thereby being flexible and changeable and being capable of configuring various constraints according to requirements.
In addition, the invention carries out hierarchical optimization decision according to three targets with different priorities, only considers the distance information of the roadway position and the storage distance only considers the storage distance with the storage area aiming at the condition of variable warehouse environments, thereby having better robustness.
FIG. 4 is a multi-objective optimization based order combining apparatus according to an embodiment of the present invention, and as shown in FIG. 4, the multi-objective optimization based order combining apparatus 400 includes an obtaining module 401, a preprocessing module 402, and an allocating module 403. The obtaining module 401 obtains the order to generate an order set. The preprocessing module 402 allocates one order in the order set to a preset order set, and allocates other orders in the order set that are not allocated and can be covered by the logic area of the order set to a preset order set that can be added. The allocating module 403 sorts the orders according to the lane and storage location information that can be added to the order set, so as to allocate the sorted orders to the collection list in sequence until the preset collection list upper limit requirement is met.
Preferably, if the preset collection upper limit requirement is not met and the addable order set is empty after the sequential allocation, the preprocessing module 402 selects one order from the remaining orders in the order set to allocate to the collection, and adds the logical area corresponding to the order to the logical area set of the collection, so as to allocate other unassigned orders in the order set that can be covered by the logical area of the current collection to the addable order set.
As another embodiment of the invention, the acquisition module 401 acquires and categorizes orders to generate a singleton order set and a non-singleton order set. The allocating module 403 sorts the orders according to the lane and storage location information that can be added to the order set order, so as to allocate the sorted orders to the collection list in sequence until the preset collection list upper limit requirement is met, and the specific implementation process includes:
and calculating the picking difficulty of any single order which can be added into the single order set and distributed to the single collection list, sequencing the single orders from small to large according to the picking difficulty, and distributing the single orders to the single collection list in sequence until the preset upper limit requirement of the single collection list is met. And the picking difficulty is the sum of the product of the optimal path length of the distributed aggregate single roadway and the first difficulty coefficient and the product of the optimal path length of the distributed aggregate single storage position and the second difficulty coefficient.
And calculating the difference between the picking difficulty and the logical area number multiplied by a third coefficient after the non-single order can be added into the non-single order set, sorting the non-single orders from small to large according to the difference, and sequentially allocating the non-single orders to the non-single order set until the preset upper limit requirement of the non-single order set is met.
In addition, it should be noted that, for any non-single order in the non-single order set, the preprocessing module 402 may sort the non-single order from large to small according to the comprehensive values of the number of logic areas, the number of lanes, and the number of storage bits, and then allocate the first non-single order after sorting to a preset non-single order set. Wherein, the integrated value is the logical area number multiplied by 100 plus the lane number multiplied by 10 plus the storage bit number.
It should be noted that the order combining method based on multi-objective optimization and the order combining device based on multi-objective optimization according to the present invention have corresponding relationships in the specific implementation content, and therefore, the repeated content is not described again.
FIG. 5 illustrates an exemplary system architecture 500 for a multiobjective optimization-based order combining method or a multiobjective optimization-based order combining apparatus to which embodiments of the present invention may be applied.
As shown in fig. 5, the system architecture 500 may include terminal devices 501, 502, 503, a network 504, and a server 505. The network 504 serves to provide a medium for communication links between the terminal devices 501, 502, 503 and the server 505. Network 504 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 501, 502, 503 to interact with a server 505 over a network 504 to receive or send messages or the like. The terminal devices 501, 502, 503 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 501, 502, 503 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 505 may be a server providing various services, such as a background management server (for example only) providing support for shopping websites browsed by users using the terminal devices 501, 502, 503. The backend management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (for example, target push information, product information — just an example) to the terminal device.
It should be noted that the order combination method based on multi-objective optimization provided by the embodiment of the present invention is generally executed by the server 505, and accordingly, an order combination apparatus based on multi-objective optimization is generally disposed in the server 505.
It should be understood that the number of terminal devices, networks, and servers in fig. 5 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 6, a block diagram of a computer system 600 suitable for use with a terminal device implementing an embodiment of the invention is shown. The terminal device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU)601 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM603, various programs and data necessary for the operation of the system 600 are also stored. The CPU601, ROM602, and RAM603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 601.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes an acquisition module, a pre-processing module, and a distribution module. Wherein the names of the modules do not in some cases constitute a limitation of the module itself.
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise: acquiring orders to generate an order set; allocating one order in an order set to a preset order set so as to determine a logic area of a current order set according to the item type of the order; distributing other unallocated orders in the order set which can be covered by the logic area of the current order set to a preset order set which can be added; and sequencing according to the roadway and the storage position information which can be added into the order set order so as to sequentially distribute the sequenced orders into the collection list until the preset collection list upper limit requirement is met.
According to the technical scheme of the embodiment of the invention, the problems of low efficiency of combining orders and poor quality of the obtained set in the prior art can be solved.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. A multi-objective optimization-based order combination method is characterized by comprising the following steps:
acquiring orders to generate an order set;
allocating one order in an order set to a preset order set so as to determine a logic area of a current order set according to the item type of the order;
distributing other unallocated orders in the order set which can be covered by the logic area of the current order set to a preset order set which can be added;
and sequencing according to the roadway and the storage position information which can be added into the order set order so as to sequentially distribute the sequenced orders into the collection list until the preset collection list upper limit requirement is met.
2. The method of claim 1, further comprising:
if the preset collection sheet upper limit requirement is not met and the addable order set is empty after the sequential allocation, one order is selected from the remaining orders in the order set and allocated to the collection sheet, and the logic area corresponding to the order is added to the logic area set of the collection sheet, so that other unassigned orders in the order set which can be covered by the logic area of the current collection sheet are allocated to the addable order set.
3. The method of claim 1, wherein obtaining the order to generate the set of orders comprises:
acquiring and classifying orders to generate a single order set and a non-single order set;
the method comprises the following steps of sequencing according to roadway and storage position information which can be added into orders in an order set so as to sequentially distribute the sequenced orders into a collection list until the preset collection list upper limit requirement is met:
for any single order which can be added into the single order set, calculating the picking difficulty after the order is distributed to the single order set, sequencing the single orders from small to large according to the picking difficulty, and distributing the single orders to the single order set in sequence until the preset upper limit requirement of the single order set is met; the picking difficulty is the sum of the product of the optimal path length of the distributed aggregate single roadway and the first difficulty coefficient and the product of the optimal path length of the distributed aggregate single storage position and the second difficulty coefficient;
and calculating the difference between the picking difficulty and the logical area number multiplied by a third coefficient after the non-single order can be added into the non-single order set, sorting the non-single orders from small to large according to the difference, and sequentially allocating the non-single orders to the non-single order set until the preset upper limit requirement of the non-single order set is met.
4. The method of claim 3, wherein allocating one of the set of orders into a preset collection comprises:
sorting any non-single order in the non-single order set from large to small according to the comprehensive numerical values of the number of logic areas, the number of lanes and the number of storage digits; wherein, the comprehensive value is the sum of the logical area number multiplied by 100 and the lane number multiplied by 10 and the storage digit number;
and distributing the sorted first non-single order to a preset non-single collection list.
5. An order combining device based on multi-objective optimization, comprising:
the acquisition module is used for acquiring orders to generate an order set;
the system comprises a preprocessing module, a data processing module and a data processing module, wherein the preprocessing module is used for distributing an order in an order set to a preset order set so as to determine a logic area of a current order set according to the article type of the order; distributing other unallocated orders in the order set which can be covered by the logic area of the current order set to a preset order set which can be added;
and the distribution module is used for sequencing according to the roadway and the storage position information which can be added into the order set order so as to distribute the sequenced orders into the collection list in sequence until the preset collection list upper limit requirement is met.
6. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-4.
7. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910550365.4A CN112132642A (en) | 2019-06-24 | 2019-06-24 | Order combination method and device based on multi-objective optimization |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910550365.4A CN112132642A (en) | 2019-06-24 | 2019-06-24 | Order combination method and device based on multi-objective optimization |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112132642A true CN112132642A (en) | 2020-12-25 |
Family
ID=73849071
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910550365.4A Pending CN112132642A (en) | 2019-06-24 | 2019-06-24 | Order combination method and device based on multi-objective optimization |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112132642A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113052536A (en) * | 2021-04-06 | 2021-06-29 | 北京京东振世信息技术有限公司 | Order processing method, device and system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150073963A1 (en) * | 2013-09-11 | 2015-03-12 | Chicago Mercantile Exchange Inc. | Matching with Level Residual Allocation |
| CN106809586A (en) * | 2017-03-28 | 2017-06-09 | 北京京东尚科信息技术有限公司 | Method and apparatus for determining picking path |
| CN108205739A (en) * | 2016-12-20 | 2018-06-26 | 北京京东尚科信息技术有限公司 | Gather single group construction method and system |
| CN108345952A (en) * | 2017-01-24 | 2018-07-31 | 北京京东尚科信息技术有限公司 | Generate set single method, apparatus, electronic equipment and readable storage medium storing program for executing |
-
2019
- 2019-06-24 CN CN201910550365.4A patent/CN112132642A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150073963A1 (en) * | 2013-09-11 | 2015-03-12 | Chicago Mercantile Exchange Inc. | Matching with Level Residual Allocation |
| CN108205739A (en) * | 2016-12-20 | 2018-06-26 | 北京京东尚科信息技术有限公司 | Gather single group construction method and system |
| CN108345952A (en) * | 2017-01-24 | 2018-07-31 | 北京京东尚科信息技术有限公司 | Generate set single method, apparatus, electronic equipment and readable storage medium storing program for executing |
| CN106809586A (en) * | 2017-03-28 | 2017-06-09 | 北京京东尚科信息技术有限公司 | Method and apparatus for determining picking path |
Non-Patent Citations (1)
| Title |
|---|
| 高丽;徐克林;毛道晓;李艳冰;: "基于规则及多色集合的多品种订单调度方法", 同济大学学报(自然科学版), no. 02 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113052536A (en) * | 2021-04-06 | 2021-06-29 | 北京京东振世信息技术有限公司 | Order processing method, device and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110348771B (en) | Method and device for order grouping of orders | |
| CN107845012B (en) | Order processing method and device | |
| CN110472899B (en) | Method and device for distributing articles out of warehouse | |
| CN108734559B (en) | Order processing method and device | |
| CN110889656B (en) | Warehouse rule configuration method and device | |
| CN110717697A (en) | Warehouse-out positioning method and device | |
| CN110304385B (en) | Warehouse racking method and device | |
| CN111507651A (en) | Order data processing method and device applied to man-machine mixed warehouse | |
| CN109934427B (en) | Method and device for generating item distribution scheme | |
| CN113259144A (en) | Storage network planning method and device | |
| CN111950830A (en) | Task allocation method and device | |
| CN111768145A (en) | Method and device for distributing grid openings | |
| CN110555641A (en) | storage allocation method and device | |
| CN112132642A (en) | Order combination method and device based on multi-objective optimization | |
| CN113222490A (en) | Inventory allocation method and device | |
| CN113650997A (en) | Method and device for positioning articles in warehouse-out process | |
| CN113344234A (en) | Method and apparatus for sorting items | |
| CN112966992A (en) | Order production method and device | |
| CN112784212A (en) | Method and device for optimizing inventory | |
| CN111832980A (en) | Method and device for allocating storage positions of multi-layer warehouse | |
| CN113379173B (en) | Method and device for marking warehouse goods with labels | |
| CN113191703A (en) | Method and device for allocating storage positions | |
| CN115099865A (en) | Data processing method and device | |
| CN113554380A (en) | Method and device for positioning articles in warehouse-out process | |
| CN113762664A (en) | Method and device for distributing picking task and computer readable medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20210301 Address after: 101, 1st floor, building 2, yard 20, Suzhou street, Haidian District, Beijing 100080 Applicant after: Beijing Jingbangda Trading Co.,Ltd. Address before: 100086 8th Floor, 76 Zhichun Road, Haidian District, Beijing Applicant before: BEIJING JINGDONG SHANGKE INFORMATION TECHNOLOGY Co.,Ltd. Applicant before: BEIJING JINGDONG CENTURY TRADING Co.,Ltd. Effective date of registration: 20210301 Address after: 6 / F, 76 Zhichun Road, Haidian District, Beijing 100086 Applicant after: Beijing Jingdong Zhenshi Information Technology Co.,Ltd. Address before: 101, 1st floor, building 2, yard 20, Suzhou street, Haidian District, Beijing 100080 Applicant before: Beijing Jingbangda Trading Co.,Ltd. |
|
| TA01 | Transfer of patent application right | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |