WO2022095706A1 - 商品布局数据的获取方法、装置、货柜、设备和介质 - Google Patents

商品布局数据的获取方法、装置、货柜、设备和介质 Download PDF

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WO2022095706A1
WO2022095706A1 PCT/CN2021/125244 CN2021125244W WO2022095706A1 WO 2022095706 A1 WO2022095706 A1 WO 2022095706A1 CN 2021125244 W CN2021125244 W CN 2021125244W WO 2022095706 A1 WO2022095706 A1 WO 2022095706A1
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layout
combinations
commodity
combination
valid
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PCT/CN2021/125244
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English (en)
French (fr)
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郑若辰
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北京京东乾石科技有限公司
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Priority to JP2023523246A priority Critical patent/JP2023545544A/ja
Priority to US18/249,675 priority patent/US20230394417A1/en
Priority to EP21888403.9A priority patent/EP4273767A4/en
Publication of WO2022095706A1 publication Critical patent/WO2022095706A1/zh

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063Operations research, analysis or management
    • G06Q10/0639Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06395Quality analysis or management
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q10/00Administration; Management
    • G06Q10/08Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation
    • G06F30/27Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063Operations research, analysis or management
    • G06Q10/0631Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00Details relating to CAD techniques
    • G06F2111/04Constraint-based CAD
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00Details relating to CAD techniques
    • G06F2111/06Multi-objective optimisation, e.g. Pareto optimisation using simulated annealing [SA], ant colony algorithms or genetic algorithms [GA]
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00Details relating to the application field
    • G06F2113/20Packaging, e.g. boxes or containers
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30Computing systems specially adapted for manufacturing

Definitions

  • the present disclosure relates to the field of computer technology, and in particular, to a method for acquiring commodity layout data, a device for acquiring commodity layout data, a gravity container, an electronic device, and a computer-readable storage medium.
  • the embodiments of the present disclosure provide a method for acquiring commodity layout data, a device for acquiring commodity layout data, a gravity container, an electronic device, and a computer readable, which can make the gravity container have better recognition effect and higher user experience. storage medium.
  • One aspect of the present disclosure provides a method for acquiring commodity layout data, including: determining a minimum weight difference of each effective layout combination in multiple effective layout combinations; and acquiring at least one effective layout combination from the multiple effective layout combinations according to preset constraints
  • the two current layout combinations are used as commodity layout data for the commodity layout of the gravity container; wherein, the preset constraint conditions include the difference between the lower limit weight difference corresponding to the multiple valid layout combinations and a current layout combination corresponding to the at least two current layout combinations. Weight constraint between minimum weight differences.
  • the method before determining the minimum weight difference of each valid layout combination in the multiple valid layout combinations, the method further includes: determining multiple potential layout combinations according to the number of commodity categories to be arranged; A plurality of valid layout combinations are determined from among the plurality of potential layout combinations.
  • the business constraints include a height constraint between the commodity height of each category of commodities in each valid layout combination and the cargo lane height of the gravity container, and the corresponding height of each cargo lane of the gravity container.
  • Mutually exclusive constraints between items in at least two categories in a valid layout combination are mutually exclusive constraints between items in at least two categories in a valid layout combination.
  • determining the minimum weight difference of each valid layout combination in the plurality of valid layout combinations includes: determining a mixed integer model corresponding to the minimum weight difference according to the weight of at least two sub-combinations in each valid layout combination ; Get the minimum weight difference for each valid layout combination according to the mixed integer model.
  • the method before acquiring at least two current layout combinations from a plurality of valid layout combinations as commodity layout data according to a preset constraint condition, the method further includes: acquiring a data corresponding to each category in each valid layout combination Valid layout vector for merchandise.
  • the preset constraint conditions further include: category constraints between the combined layout model and the effective layout vector of each effective layout combination, and the relationship between the combined layout model, the effective layout vector, and the number of cargo lanes of the gravity container cargo lane constraints.
  • the method further includes: when the number of commodity categories in the at least two current layout combinations is equal to the number of commodity categories to be If the number of product categories in the layout is the same, the lower limit weight difference is maximized to determine the combination of at least two current layouts as product layout data.
  • an acquisition device for commodity layout data including a weight determination module and a layout acquisition module.
  • the weight determination module is used to determine the minimum weight difference of each valid layout combination in the multiple valid layout combinations;
  • the layout acquisition module is used to obtain at least two current layout combinations from the multiple valid layout combinations as commodity layouts according to preset constraints
  • the data is used for the commodity layout of a cargo lane in a gravity container; wherein, the preset constraint conditions include a lower limit weight difference corresponding to a plurality of valid layout combinations and a minimum weight difference corresponding to a current layout combination of at least two current layout combinations weight constraints between.
  • Another aspect of the present disclosure provides a gravity cargo container, comprising: the above-mentioned device for implementing the above-mentioned method.
  • Another aspect of the present disclosure provides an electronic device, comprising: one or more processors and a storage device; the storage device is used to store one or more programs, wherein when the one or more programs are processed by one or more When executed, the processor causes one or more processors to implement the above-mentioned method.
  • Another aspect of the present disclosure provides a computer-readable storage medium having executable instructions stored thereon, the instructions, when executed by a processor, cause the processor to implement the above-described method.
  • the above-mentioned one or more embodiments have the following advantages or beneficial effects: through the method for acquiring commodity layout data of the present disclosure, the commodity layout scheme of the unmanned gravity container can be quickly obtained, and on the basis of the commodity layout scheme, the gravity In the case of a container with many commodity categories, the user's recognition accuracy and recognition speed of picking up commodities can be effectively improved according to gravity. At the same time, each cargo lane is bound to a specific commodity category to maximize the use of the storage space of the cargo lane.
  • FIG. 1 schematically shows a flowchart of a method for acquiring commodity layout data according to an embodiment of the present disclosure
  • FIG. 2 schematically shows a flowchart of a method for acquiring commodity layout data according to another embodiment of the present disclosure
  • FIG. 3 schematically shows a flowchart of a method for acquiring commodity layout data according to another embodiment of the present disclosure
  • FIG. 4 schematically shows a flowchart of a method for acquiring commodity layout data according to another embodiment of the present disclosure
  • FIG. 5 schematically shows a flowchart of a method for acquiring commodity layout data according to another embodiment of the present disclosure
  • FIG. 6 schematically shows a composition diagram of an apparatus for acquiring commodity layout data according to an embodiment of the present disclosure
  • FIG. 7 schematically shows a block diagram of an electronic device suitable for implementing the above method for acquiring commodity layout data according to an embodiment of the present disclosure.
  • At least one of the “systems” shall include, but not be limited to, systems with A alone, B alone, C alone, A and B, A and C, B and C, and/or A, B, C, etc. ).
  • Unmanned gravity containers (referred to as gravity containers) generally have multi-layer shelves, each layer of shelves can have multiple cargo lanes, an electronic scale is placed at the bottom of each cargo lane, and the goods sold are placed on the electronic scale. There are multiple commodities on each electronic scale, which can be of the same category or a combination of different categories.
  • Gravity Container identifies the category and quantity of goods taken away by the user through the change of gravity, which can maximize the use of the sales space, the degree of freedom in commodity placement is higher, no electronic labels are required, the calculation speed is faster and more accurate, and the application is more Extensive, and has the advantages of scalability and low operating costs. Therefore, in the field of intelligent vending technology, with the rapid development of artificial intelligence technology, more and more gravity containers appear in people's social life.
  • Commodities of different categories may have similar weights.
  • the unit weights of category A commodities and category B commodities placed on the same electronic scale are equal to M, then when the weight of the commodity taken by the user changes to M, it cannot be Determine whether the product taken is a category A commodity or a category B commodity.
  • Commodities of different categories may have similar weights corresponding to different quantities.
  • the combined weight of 1 category A commodity and 2 category B commodities placed on the same electronic scale is relatively M, then when the user takes it When the weight of the product changes to M, it is impossible to determine whether the picked-up product is one A-category product or two B-category products.
  • the embodiments of the present disclosure provide a method for acquiring commodity layout data, a device for acquiring commodity layout data, a gravity container, an electronic device, and a computer readable, which can make the gravity container have better recognition effect and higher user experience. storage medium.
  • FIG. 1 schematically shows a flowchart of a method for acquiring commodity layout data according to an embodiment of the present disclosure.
  • the gravity container may have 5 layers of shelves, and each layer of the shelves may have 2 cargo lanes.
  • One electronic scale can be set correspondingly, and the specifications of each cargo lane are the same, so the specifications of each shelf are also the same.
  • an aspect of the present disclosure provides a method for acquiring commodity layout data, including operations S101 and S102.
  • the preset constraint condition includes a weight constraint between a lower limit weight difference corresponding to a plurality of valid layout combinations and a minimum weight difference corresponding to a current layout combination of at least two current layout combinations.
  • the commodity layout data corresponds to a combination of commodity categories that can be placed on each cargo lane of the container.
  • three categories of products namely A category, B category, and C category
  • the combination of product categories A-B-C corresponding to the cargo lane is a piece of data in the commodity layout data.
  • each shelf has a gravity container with 2 cargo lanes. Since some cargo lanes can be vacant, and multiple cargo lanes can be set with the same product category combination, it can have up to 10 commodity category combinations as product layout data. .
  • a commodity of a category represents a commodity, that is, a commodity of each category can have multiple or multiple pieces of the commodity.
  • the effective layout combination is obtained according to the number of commodity categories to be laid out in the commodity pool used for the commodity combination, so as to obtain the commodity category combination from multiple valid layout combinations. Specifically, when the number of commodity categories to be laid out in the commodity pool is 100, there are 100 categories of commodities to be laid out in the commodity pool.
  • the effective layout combination is the product category combination obtained after screening the potential layout combinations described below. Among them, in each effective layout combination, multiple sub-combinations can also be obtained through the weight combination between the commodities of each category, and the weight difference between each sub-combination can be compared in size, and the minimum weight of the effective layout combination can be obtained. Poor, see below for details.
  • the current layout combinations are equivalent to the above-mentioned commodity category combinations, and the layout data of the at least two current layout combinations can be used as the final commodity layout data.
  • the selection of effective layout combinations needs to be performed through preset constraints.
  • the preset constraint conditions are defined by the relationship between the fixed characteristic attributes of the gravity container that the technicians of the gravity container need to consider when laying out the goods to the gravity container, the number of categories of goods actually taken by the user, and the fixed characteristic attributes of the goods themselves.
  • the screening rules can include weight constraints, category constraints, height constraints, etc. For details, please refer to the following.
  • the effective layout combination that satisfies the filtering rules is the current layout combination, and the effective layout combination that does not meet the filtering rules is eliminated and not regarded as the current layout combination.
  • the fixed characteristic attributes of the gravity container include the maximum number of commodity categories placed on the electronic scale of the cargo lane, the height of the cargo lane, and the number of cargo lanes, etc.
  • the fixed characteristic attributes of the commodity itself include the height of the commodity, the mutually exclusive relationship between the commodities, and so on.
  • the weight constraint in the preset constraint conditions is a weight screening rule between the lower limit weight difference in multiple valid layout combinations and the minimum weight difference of a current layout combination corresponding to at least two current layout combinations. Layout combinations need to satisfy this weight filter rule.
  • the lower limit weight difference in the multiple valid layout combinations is the minimum value of the minimum weight difference in each valid layout combination in the multiple valid layout combinations.
  • multiple valid layout combinations include a, b, and c, a total of 3 combinations, wherein the minimum weight difference in the valid layout combination a is ⁇ ma, the minimum weight difference in the corresponding valid layout combination b is ⁇ mb, and the valid layout combination c
  • the minimum weight difference of ⁇ mc is ⁇ mc, then the minimum value among ⁇ ma, ⁇ mb and ⁇ mc is the lower limit weight difference in the above-mentioned multiple effective layout combinations.
  • the commodity layout scheme of the unmanned gravity container can be quickly obtained, and on the basis of the commodity layout scheme, in the case that the gravity container has many commodity categories, it can be effectively lifted according to gravity
  • the recognition accuracy and recognition speed of the product taken by the user, and at the same time bind a specific product category for each cargo lane, so as to maximize the use of the placement space of the cargo lane.
  • FIG. 2 schematically shows a flowchart of a method for acquiring commodity layout data according to another embodiment of the present disclosure.
  • the method before determining the minimum weight difference of each of the plurality of valid layout combinations in operation S101 , the method further includes operations S201 and S202 .
  • a plurality of valid layout combinations are determined from a plurality of potential layout combinations according to business constraints.
  • the business constraints include a height constraint between the commodity height of each category of commodities in each valid layout combination and the cargo lane height of the gravity container, and the corresponding height of each cargo lane of the gravity container.
  • Mutually exclusive constraints between items in at least two categories in a valid layout combination are mutually exclusive constraints between items in at least two categories in a valid layout combination.
  • the commodity data of multiple categories to be laid out are set in the commodity pool.
  • the commodity pool is the selection of the total commodities drawn up by the operator (such as the merchant) of the gravity container for the commodity placement of each gravity container according to factors such as market sales and its own inventory. It can give the weight of each commodity, the individual weight error and the error information of the electronic scale at the same time.
  • the quantity Q of multiple potential layout combinations is the combined quantity of all commodity categories that can be placed in a single cargo lane, namely:
  • the service constraint can be understood as a kind of preset constraint, which is used to preliminarily screen multiple potential layout combinations to obtain multiple valid layout combinations.
  • Business constraints mainly include height constraints and mutual exclusion constraints. In addition, it also includes restrictions on user access, the existence of goods in the cargo lane, the constraints on the number of categories placed in the cargo lane, and the constraints on the placement of products of the same category.
  • the number of product categories that the user can take from a single electronic scale is at most two categories;
  • the storage area is limited, and a maximum of 3 categories of commodities are required to be placed in a single cargo lane;
  • the existence of cargo lane constraints can be understood as each cargo lane in a gravity container needs to be placed with at least one category of commodities, and there must be no vacancy.
  • the situation of the cargo lane; the placement constraints of the same category of goods can be understood as the same category of goods can only be placed in a few cargo lanes.
  • the commodity height of each category of commodities must not exceed the cargo lane height of the gravity container, otherwise it cannot be placed into the cargo lane, which is the height constraint in the business constraints.
  • the mutually exclusive constraints are met
  • the height constraint is met, that is, when the height of each product in the potential layout combination is less than the height of the cargo lane, the potential layout combination is an effective layout combination, otherwise, The potential layout combination is eliminated and cannot be used as a valid layout combination.
  • height i is the height of the product of the ith category in the combination S
  • height scale is the height of the cargo lane of the gravity container
  • some commodities have a mutually exclusive relationship and cannot be placed in the same cargo lane, which is the mutual exclusion constraint in the business constraints.
  • the commercial coffee is required to be warm, but the commercial ice cream is required to be iced, then the warm coffee commodity and the cold ice cream are mutually exclusive commodities and cannot be placed on the same cargo lane as the constituent commodities of the same combination.
  • the potential layout combination is an effective layout combination, otherwise, the potential layout combination The combination is eliminated and cannot be used as a valid layout combination.
  • FIG. 3 schematically shows a flowchart of a method for acquiring commodity layout data according to another embodiment of the present disclosure.
  • the operation S101 of determining the minimum weight difference of each valid layout combination among the plurality of valid layout combinations includes sub-operation S310 and sub-operation S320 .
  • a mixed integer model corresponding to the minimum weight difference is determined according to the weight of at least two sub-combinations in each valid layout combination
  • each valid layout combination S it needs to have at least two sub-combinations, for example, a single valid layout combination S includes a sub-combination comb1 and a sub-combination comb2.
  • Each sub-combination has at least two categories of commodities, that is, each effective layout combination has at least 3 categories of commodities.
  • the number of commodity categories formed in each sub-combination is limited by the user's taking constraint, that is, if the user takes multiple commodities at one time during the actual use of the gravity container, the user takes the product from a single electronic scale.
  • the number of product categories to be retrieved can be up to 2 categories. Therefore, the number of product categories in each sub-combination can be 2 categories.
  • the weight of each sub-combination satisfies a certain planning constraint
  • the planning constraint is the weight of the i-th category commodity of the corresponding one effective layout combination S, the weight of each electronic scale of the gravity container
  • a single valid layout combination S includes sub-combinations comb1 and sub-combinations comb2, which satisfy formula (3) of the following planning constraints:
  • E scale is the limit measurement error of the electronic scale
  • E i is the limit individual error of the product of the ith category.
  • the mixed integer model corresponding to the minimum weight difference in the above single effective layout combination satisfies the formula (5) of the following objective function:
  • the minimum weight difference Z corresponding to any sub-combination of each effective layout combination can be obtained.
  • the minimum weight difference is mainly used in the weight constraints, as an important indicator for evaluating the effective layout combination S.
  • the minimum weight difference Z is smaller, the weight discrimination of the combination S is lower, and two sub-combinations are more likely to occur.
  • the weights are similar, so that the electronic scale cannot judge the category of goods taken by the user based on the weight.
  • the minimum weight difference Z is larger, the weight distinction degree of the combination S is higher in the description, and the combination S can be better used as the commodity category combination data in the embodiment of the present disclosure.
  • FIG. 4 schematically shows a flowchart of a method for acquiring commodity layout data according to another embodiment of the present disclosure.
  • the method before obtaining at least two current layout combinations from a plurality of valid layout combinations as commodity layout data according to preset constraints in operation S102 , the method further includes operation S401 .
  • the commodities of each category included in the combination S correspond to the following vector relationships: in, represents the ith component of the vector V t , 1 ⁇ i ⁇ n, if when When it means that the combination S contains the product of the i-th category, on the contrary, when and when When it means that the combination S does not contain the product of the i-th category. That is, the effective layout vector V t can be used to determine that the combination S has information such as the number of commodity categories and commodity names.
  • the preset constraint conditions further include: category constraints between the combined layout model and the effective layout vector of each effective layout combination, and the relationship between the combined layout model, the effective layout vector, and the number of cargo lanes of the gravity container cargo lane constraints.
  • the effective layout combinations can be further screened, and a plurality of current layout combinations among the multiple effective layout combinations can be determined as the commodity layout data in the embodiment of the present disclosure.
  • the layout premise of the embodiment of the present disclosure is that only one commodity combination is allocated to a single cargo lane of a single gravity container. Therefore, for multiple valid layout combinations, the commodity combination layout in it needs to satisfy the following formula (7):
  • allot jt is used to reflect whether the t-th commodity combination is allocated in the j-th cargo lane. Specifically, when the sum of allot jt of the above formula (7) is 1, it means that the t-th commodity combination is allocated to the j-th cargo lane of the gravity container. On the contrary, the t-th commodity combination cannot be allocated. to the jth cargo lane.
  • the combination layout model is the objective function of the commodity category combination in the embodiment of the present disclosure, and is the same type of model as the mixed integer model described above.
  • the corresponding combination S for the effective layout vector V t contains the product vector of the ith category. In this way, it can be used to fix the relationship between c i and allot jt to satisfy the maximum number of commodity categories included in the corresponding single current layout combination S, that is, formula (8) is the above category constraint.
  • R is the maximum number of cargo lanes that can be divided into steps for a single category of goods, which belongs to the upper limit of the number of cargo lanes.
  • diff t is the above-mentioned minimum weight difference Z corresponding to any sub-combination of each valid layout combination, which is the maximum error recognized by the electronic scale.
  • is the threshold value of the weight difference change that can be recognized by an electronic scale, so that the electronic can recognize the gravity change corresponding to each user's taking action, and the change must be a valid value, which is used to reflect the weight of the electronic scale. Change recognition ability.
  • the commodity layout data corresponding to each cargo lane in the gravity container can be obtained, that is, a plurality of current layout combinations, and the commodity layout data can be applied to the gravity container for commodity layout, then It can improve the recognition rate of the container for the change of commodity category and the number of pieces when the user picks up the commodity, and at the same time, it can also ensure that the utilization rate of the container is maximized and the commodity category is diversified.
  • FIG. 5 schematically shows a flowchart of a method for acquiring commodity layout data according to another embodiment of the present disclosure
  • the method further includes operation S501 .
  • a plurality of valid layout combinations can be screened by preset constraints, and a plurality of current layout combinations can be obtained as commodity layout data and applied to the commodity layout of the gravity container.
  • FIG. 6 schematically shows a composition diagram of an apparatus for acquiring commodity layout data according to an embodiment of the present disclosure. It should be noted that FIG. 6 is only an example of the composition structure of the obtaining apparatus 600 to which the embodiment of the present disclosure can be applied, so as to help those skilled in the art to understand the technical content of the present disclosure, but it does not mean that the embodiment of the present disclosure does not Can be used in other devices, systems, environments or scenarios.
  • an apparatus 600 for acquiring commodity layout data including: a weight determination module 610 and a layout acquisition module 620, the weight determination module 610 is configured to determine each of the multiple valid layout combinations The minimum weight difference of the valid layout combinations; the layout obtaining module 620 is configured to obtain at least two current layout combinations from the multiple valid layout combinations according to the preset constraint conditions as commodity layout data, which are used for the data of a cargo lane in the gravity container.
  • Commodity layout wherein the preset constraint condition includes a weight constraint between a lower limit weight difference corresponding to a plurality of valid layout combinations and a minimum weight difference corresponding to a current layout combination of at least two current layout combinations.
  • the above-mentioned obtaining device is used to realize the above-mentioned method for obtaining the commodity layout data, which will not be repeated here.
  • any of the modules, sub-modules, units, sub-units, or at least part of the functions of any of them according to the embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be divided into multiple modules for implementation.
  • any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented at least in part as hardware circuits, such as field programmable gate arrays (FPGA), programmable logic arrays (PLA), A system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or any other reasonable means of hardware or firmware that integrates or packages circuits, or can be implemented in software, hardware, and firmware Any one of these implementations or an appropriate combination of any of them is implemented.
  • FPGA field programmable gate arrays
  • PLA programmable logic arrays
  • ASIC application specific integrated circuit
  • any one of these implementations or an appropriate combination of any of them is implemented.
  • one or more of the modules, sub-modules, units, and sub-units according to embodiments of the present disclosure may be implemented at least in part as computer program modules that, when executed, may perform corresponding functions.
  • any one of the weight determination module 610 and the layout acquisition module 620 may be implemented in one module combined, or any one of the modules may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of other modules and implemented in one module. According to embodiments of the present disclosure, at least one of the weight determination module 610 and the layout acquisition module 620 may be implemented at least in part as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a System-on-Chip , a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or any other reasonable way to integrate or package a circuit, etc.
  • FPGA Field Programmable Gate Array
  • PLA Programmable Logic Array
  • ASIC application specific integrated circuit
  • weight determination module 610 and the layout acquisition module 620 may be implemented at least in part as a computer program module that, when executed, may perform corresponding functions.
  • Another aspect of the present disclosure provides a gravity container, comprising: the above-mentioned device for acquiring commodity layout data, which is used to realize the above-mentioned method for acquiring commodity layout data, and the function implementation thereof will not be repeated here.
  • the gravity container can have 5 layers of shelves, each layer of shelves can have 2 cargo lanes, and one electronic scale can be correspondingly arranged at the bottom of each cargo lane.
  • the gravity container can be used in the method described above.
  • FIG. 7 schematically shows a block diagram of an electronic device suitable for implementing the above method for acquiring commodity layout data according to an embodiment of the present disclosure.
  • the electronic device shown in FIG. 7 is only an example, and should not impose any limitations on the functions and scope of use of the embodiments of the present disclosure.
  • Another aspect of the present disclosure provides an electronic device, comprising: one or more processors and a storage device; the storage device is used to store one or more programs, wherein when the one or more programs are processed by one or more When executed, the processor causes one or more processors to implement the above-mentioned method.
  • an electronic device 700 includes a processor 701 that can be loaded into a random access memory (RAM) 703 according to a program stored in a read only memory (ROM) 702 or from a storage part 708 program to perform various appropriate actions and processes.
  • the processor 701 may include, for example, a general-purpose microprocessor (eg, a CPU), an instruction set processor and/or a related chipset, and/or a special-purpose microprocessor (eg, an application specific integrated circuit (ASIC)), among others.
  • the processor 701 may also include on-board memory for caching purposes.
  • the processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to the embodiments of the present disclosure.
  • the processor 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704.
  • the processor 701 performs various operations of the method flow according to an embodiment of the present disclosure by executing programs in the ROM 702 and/or the RAM 703. Note that the program may also be stored in one or more memories other than ROM 702 and RAM 703.
  • the processor 701 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in one or more memories.
  • the device 700 may also include an input/output (I/O) interface 705 that is also connected to the bus 704 .
  • I/O interface 705 may also include one or more of the following components connected to I/O interface 705: input portion 706 including keyboard, mouse, etc.; including components such as cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers
  • I/O interface 705 input portion 706 including keyboard, mouse, etc.
  • components such as cathode ray tube (CRT), liquid crystal display (LCD), etc.
  • a storage section 708 including a hard disk, etc.
  • a communication section 709 including a network interface card such as a LAN card, a modem, and the like.
  • the communication section 709 performs communication processing via a network such as the Internet.
  • a drive 710 is also connected to the I/O interface 705 as needed.
  • a removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is mounted on the drive 710 as needed so that a computer program read therefrom is installed into the storage section 708 as needed.
  • the method flow according to an embodiment of the present disclosure may be implemented as a computer software program.
  • embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the method illustrated in the flowchart.
  • the computer program may be downloaded and installed from the network via the communication portion 709 and/or installed from the removable medium 711 .
  • the above-described functions defined in the system of the embodiment of the present disclosure are performed.
  • the above-described systems, apparatuses, apparatuses, modules, units, etc. can be implemented by computer program modules.
  • Another aspect of the present disclosure provides a computer-readable storage medium having executable instructions stored thereon, the instructions, when executed by a processor, cause the processor to implement the above-described method.
  • the computer-readable storage medium of the present disclosure may be included in the apparatus/apparatus/system described in the above embodiments; or may exist alone without being assembled into the apparatus/apparatus/system.
  • the above-mentioned computer-readable storage medium carries one or more programs, and when the above-mentioned one or more programs are executed, implement the method according to the embodiment of the present disclosure.
  • the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as, but not limited to, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM) , erasable programmable read only memory (EPROM or flash memory), portable compact disk read only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.
  • a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.
  • a computer-readable storage medium may include one or more memories other than ROM 702 and/or RAM 703 and/or ROM 702 and RAM 703 described above.
  • Another aspect of embodiments of the present disclosure provides a computer program comprising computer-executable instructions, which when executed, are used to implement the method as described above.
  • each block in the flowchart or block diagrams may represent a module, segment, or portion of code that contains one or more logical functions for implementing the specified functions executable instructions.
  • the functions noted in the blocks 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.

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Abstract

本公开提供了一种商品布局数据的获取方法,包括:确定多个有效布局组合中每个有效布局组合的最小重量差;根据预设约束条件,从多个有效布局组合中获取至少两个当前布局组合作为商品布局数据,用于重力货柜的商品布局;其中,预设约束条件包括对应多个有效布局组合中的下限重量差与对应至少两个当前布局组合的一当前布局组合的最小重量差之间的重量约束。此外,本公开还提供了一种商品布局数据的获取装置、重力货柜、电子设备和计算机可读存储介质。

Description

商品布局数据的获取方法、装置、货柜、设备和介质 技术领域
本公开涉及计算机技术领域,尤其涉及一种商品布局数据的获取方法、商品布局数据的获取装置、重力货柜、电子设备和计算机可读存储介质。
背景技术
在智能零售技术领域中,智能无人货柜越来越多的出现在人们的日常生活中。相对于现有技术中的自动售货机,智能无人货柜通过应用人工智能等先进技术,能够给用户带来更好的购物体验。其中,作为智能无人货柜的一种新型产品,重力货柜在智能零售技术领域中发展迅速。对于重力货柜而言,当用户拿走其中某件商品后,设置在商品下的电子秤会计算重量变化来识别用户所拿商品品类,并进行结算。然而,随着用户的需求不断的提升,对重力货柜的品类、数量的要求越来越高,造成现有重力货柜无法有效识别用户所拿商品的品类和/或数量,极大降低了用户体验。
发明内容
有鉴于此,本公开实施例提供了一种能够使得重力货柜具有更好识别效果、用户体验更高的商品布局数据的获取方法、商品布局数据的获取装置、重力货柜、电子设备和计算机可读存储介质。
本公开的一个方面提供了一种商品布局数据的获取方法,包括:确定多个有效布局组合中每个有效布局组合的最小重量差;根据预设约束条件,从多个有效布局组合中获取至少两个当前布局组合作为商品布局数据,用于重力货柜的商品布局;其中,预设约束条件包括对应多个有效布局组合中的下限重量差与对应至少两个当前布局组合的一当前布局组合的最小重量差之间的重量约束。
根据本公开的实施例,在确定多个有效布局组合中每个有效布局组合的最小重量差之前,方法还包括:根据待布局商品品类数,确定多个潜在布局组合;根据业务约束条件,从多个潜在布局组合中确定多个有效布局组合。
根据本公开的实施例,业务约束条件包括每个有效布局组合中的每个品类的商品的商品高度与重力货柜的货道高度之间的高度约束,以及对应 重力货柜的任一货道的每个有效布局组合中的至少两个品类的商品之间的互斥约束。
根据本公开的实施例,确定多个有效布局组合中每个有效布局组合的最小重量差,包括:根据每个有效布局组合中的至少两个子组合的重量,确定对应最小重量差的混合整数模型;根据混合整数模型,获取每个有效布局组合的最小重量差。
根据本公开的实施例,根据预设约束条件,从多个有效布局组合中获取至少两个当前布局组合作为商品布局数据之前,方法还包括:获取对应每个有效布局组合中的每个品类的商品的有效布局向量。
根据本公开的实施例,预设约束条件还包括:每个有效布局组合的组合布局模型和有效布局向量之间的品类约束,以及组合布局模型、有效布局向量与重力货柜的货道数量之间的货道约束。
根据本公开的实施例,根据预设约束条件,从多个有效布局组合中获取至少两个当前布局组合作为商品布局数据,方法还包括:当至少两个当前布局组合中的商品品类数与待布局商品品类数相同,则对下限重量差进行最大化,以确定至少两个当前布局组合为商品布局数据。
本公开的另一个方面提供了一种商品布局数据的获取装置,包括重量确定模块和布局获取模块。重量确定模块用于确定多个有效布局组合中每个有效布局组合的最小重量差;布局获取模块用于根据预设约束条件,从多个有效布局组合中获取至少两个当前布局组合作为商品布局数据,用于重力货柜中的一货道的商品布局;其中,预设约束条件包括对应多个有效布局组合中的下限重量差与对应至少两个当前布局组合的一当前布局组合的最小重量差之间的重量约束。
本公开的另一个方面提供了一种重力货柜,包括:上述的装置,用以实现上述的方法。
本公开的另一个方面提供了一种电子设备,包括:一个或多个处理器和存储装置;存储装置用于存储一个或多个程序,其中,当一个或多个程序被一个或多个处理器执行时,使得一个或多个处理器实现上述的方法。
本公开的另一个方面提供了一种计算机可读存储介质,其上存储有可执行指令,该指令被处理器执行时使处理器实现上述的方法。
上述一个或多个实施例具有如下优点或益效果:通过本本公开的商品布局数据的获取方法,可以快速获得无人重力货柜的商品布局方案,并且在此商品布局方案的基础上,可以在重力货柜具有较多商品品类的情况下,根据重力有效提升用户拿取商品的识别准确度和识别速度,同时为每个货道绑定具体的商品品类,实现最大化利用货道的摆放空间。
附图说明
图1示意性示出了根据本公开一实施例的商品布局数据的获取方法的流程图;
图2示意性示出了根据本公开另一实施例的商品布局数据的获取方法的流程图;
图3示意性示出了根据本公开另一实施例的商品布局数据的获取方法的流程图;
图4示意性示出了根据本公开另一实施例的商品布局数据的获取方法的流程图;
图5示意性示出了根据本公开另一实施例的商品布局数据的获取方法的流程图;
图6示意性示出了根据本公开一实施例的商品布局数据的获取装置的组成图;
图7示意性示出了根据本公开实施例的适于实现上述商品布局数据的获取方法的电子设备的方框图。
具体实施方式
以下,将参照附图来描述本公开的实施例。但是应该理解,这些描述只是示例性的,而并非要限制本公开的范围。在下面的详细描述中,为便于解释,阐述了许多具体的细节以提供对本公开实施例的全面理解。然而,明显地,一个或多个实施例在没有这些具体细节的情况下也可以被实施。此外,在以下说明中,省略了对公知结构和技术的描述,以避免不必要地混淆本公开的概念。
在此使用的术语仅仅是为了描述具体实施例,而并非意在限制本公开。在此使用的术语“包括”、“包含”等表明了特征、步骤、操作和/或部件的存在,但是并不排除存在或添加一个或多个其他特征、步骤、操作或部 件。
在此使用的所有术语(包括技术和科学术语)具有本领域技术人员通常所理解的含义,除非另外定义。应注意,这里使用的术语应解释为具有与本说明书的上下文相一致的含义,而不应以理想化或过于刻板的方式来解释。
在使用类似于“A、B和C等中至少一个”这样的表述的情况下,一般来说应该按照本领域技术人员通常理解该表述的含义来予以解释(例如,“具有A、B和C中至少一个的系统”应包括但不限于单独具有A、单独具有B、单独具有C、具有A和B、具有A和C、具有B和C、和/或具有A、B、C的系统等)。在使用类似于“A、B或C等中至少一个”这样的表述的情况下,一般来说应该按照本领域技术人员通常理解该表述的含义来予以解释(例如,“具有A、B或C中至少一个的系统”应包括但不限于单独具有A、单独具有B、单独具有C、具有A和B、具有A和C、具有B和C、和/或具有A、B、C的系统等)。
无人重力货柜(简称重力货柜)一般具有多层货架,每层货架可以具有多个货道,每个货道的底部放置电子秤,并在电子秤上放置所售商品。每个电子秤上的商品有多个,可以是同一品类,也可以是不同品类的组合。重力货柜通过重力的变化来识别用户购物所拿走的商品类别和数量,可以最大程度的利用售货空间,商品摆放自由度更高,无需电子标签,计算速度更快更准,应用更为广泛,且具有可规模化,运营成本低等优势。因此,在智能售货技术领域中,随着人工智能技术的快速发展,重力货柜越来越多的出现在人们的社会生活之中。
具体地,由于用户的需求不断的提升,对重力货柜的品类、数量的要求越来越高,造成现有重力货柜无法有效识别用户所拿商品的品类和/或数量,极大降低了用户体验,具体体现于以下方面:
(1)同一电子秤上可能放置不止一品类的商品,需要根据电子秤上商品总重量变化,识别用户所拿商品。
(2)不同品类的商品可能具有相似的重量,例如同一电子秤上放置的A品类商品和B品类商品的单位重量相等均为M,则当用户拿取的商品重量变化为M时,则无法判断拿取的商品是A品类商品还是B品类商 品。
(3)不同品类的商品对应不同数量情况下可能具有相似的重量,例如同一电子秤上放置的1个A品类商品和2个B品类商品的组合的重量相对均为M,则当用户拿取的商品重量变化为M时,则无法判断拿取的商品是1个A品类商品还是2个B品类商品。
(4)相同品类的商品个体之间重量有差异,例如对于同一电子秤上设置的3个A品类商品A1、A2、A3,其标定的规格重量设定为M,但实际上的A品类商品A1重量为M+Δm1、A2重量为M+Δm2、A3重量为M+Δm3,Δm1、Δm2和Δm3均小于特定阈值Δm0。因此,在电子秤本身存在测量误差的情况下,这进一步给商品的识别带来困难。
此外,考虑到运营成本,还无法要求运营人员精确摆放确定品类的商品,同时还要最大化利用货道的摆放空间。
有鉴于此,本公开实施例提供了一种能够使得重力货柜具有更好识别效果、用户体验更高的商品布局数据的获取方法、商品布局数据的获取装置、重力货柜、电子设备和计算机可读存储介质。
图1示意性示出了根据本公开一实施例的商品布局数据的获取方法的流程图。
需要说明的是,在本公开的实施例中,为便于本领域技术人员对本公开技术内容的理解,重力货柜可以具有5层货架,每层货架可以有2个货道,每个货道的底部可以对应设置1个电子秤,每个货道的规格一致,因此,每个货架的规格也一致。
如图1所示,本公开的一个方面提供了一种商品布局数据的获取方法,包括操作S101和S102。
在操作S101中,确定多个有效布局组合中每个有效布局组合的最小重量差;
在操作S102中,根据预设约束条件,从多个有效布局组合中获取至少两个当前布局组合作为商品布局数据,用于重力货柜的商品布局;
其中,预设约束条件包括对应多个有效布局组合中的下限重量差与对应至少两个当前布局组合的一当前布局组合的最小重量差之间的重量约束。
在本公开的实施例中,商品布局数据即对应所述货柜的每一个货道上可以放置的商品品类组合。例如A品类商品、B品类商品和C品类商品共三个品类的商品作为一个组合放置在一个货道上,在对应该货道的A-B-C的商品品类组合即属于该商品布局数据中的一个数据。对于5层货架,每层货架有2个货道的重力货柜,由于一些货道可以空置,而且多个货道可以设置相同商品品类组合,因此其可以具有最多10个商品品类组合作为商品布局数据。其中,一个品类的商品即代表一种商品,即每个品类的商品可以有多个或多件该商品。
有效布局组合是根据用于商品组合的商品池的待布局商品品类数进行来获得的,以用于从多个有效布局组合中获取商品品类组合。具体地,当商品池中的待布局商品品类数为100时,则该商品池中具有100个品类的待布局商品。有效布局组合是对下文所述潜在布局组合进行筛选之后得到的商品品类组合。其中,每个有效布局组合中还可以通过每个品类的商品之间的重量组合,得到多个子组合,对各个子组合之间的重量差进行大小比对,可以获得该有效布局组合的最小重量差,具体参照下文。
对多个有效布局组合进行筛选,可以获得至少两个当前布局组合,该当前布局组合即相当于上述的商品品类组合,至少两个当前布局组合的布局数据可以用于作为最终的商品布局数据。其中,对有效布局组合的筛选,需要通过预设约束条件进行。预设约束条件为根据商品向重力货柜进行布局时,重力货柜的技术人员需要考虑的重力货柜的固定特征属性以及用户的实际拿取商品品类数、商品本身的固定特征属性之间的关系所限定的筛选规则,可以包括重量约束、品类约束、高度约束等,具体可以参照下文。满足筛选规则的有效布局组合为当前布局组合,不满足筛选规则的有效布局组合则被刨除,不作为当前布局组合。其中,重力货柜的固定特征属性包括货道的电子秤最多放置的商品品类数、货道高度、货道数量等,商品本身的固定特征属性包括商品高度、商品之间的互斥关系等。
此外,预设约束条件中的重量约束是多个有效布局组合中的下限重量差与对应至少两个当前布局组合的一当前布局组合的最小重量差之间的重量筛选规则,本公开的上述当前布局组合则需要满足该重量筛选规则。其中,多个有效布局组合中的下限重量差为该多个有效布局组合中的每个 有效布局组合中的最小重量差的最小值。例如,多个有效布局组合中包括a、b、c共3个组合,其中有效布局组合a中的最小重量差为Δma,对应有效布局组合b中的最小重量差为Δmb,有效布局组合c中的最小重量差为Δmc,则Δma、Δmb和Δmc中的最小值即上述多个有效布局组合中的下限重量差。
通过本本公开的商品布局数据的获取方法,可以快速获得无人重力货柜的商品布局方案,并且在此商品布局方案的基础上,可以在重力货柜具有较多商品品类的情况下,根据重力有效提升用户拿取商品的识别准确度和识别速度,同时为每个货道绑定具体的商品品类,实现最大化利用货道的摆放空间。
图2示意性示出了根据本公开另一实施例的商品布局数据的获取方法的流程图。
如图2所示,根据本公开的实施例,在操作S101的确定多个有效布局组合中每个有效布局组合的最小重量差之前,方法还包括操作S201和操作S202。
在操作S201中,根据待布局商品品类数,确定多个潜在布局组合;
在操作S202中,根据业务约束条件,从多个潜在布局组合中确定多个有效布局组合。
根据本公开的实施例,业务约束条件包括每个有效布局组合中的每个品类的商品的商品高度与重力货柜的货道高度之间的高度约束,以及对应重力货柜的任一货道的每个有效布局组合中的至少两个品类的商品之间的互斥约束。
多个品类数的待布局商品数据设置于商品池中,商品池是重力货柜的运营方(如商家)根据市场销量、自身库存等因素,为每个重力货柜的商品摆放所拟定总商品选取源,可以同时给出每个商品的重量、个体重量误差以及电子秤的误差信息等。
对于重力货柜的单个货道,若要求最多摆放的商品品类数不超过3个时,同时商品池中待布局商品品类数为n,则潜在布局组合的数量Q满足如下公式(1):
Figure PCTCN2021125244-appb-000001
例如,当待布局商品品类数为100,则多个潜在布局组合的数量Q为所有可以摆放至单个货道的商品品类的组合数量,即:
Figure PCTCN2021125244-appb-000002
在本公开的实施例中,业务约束条件可以理解为是预设约束条件的一种,用于对多个潜在布局组合进行初步筛选,以获得多个有效布局组合。业务约束条件主要包括高度约束和互斥约束两类。除此之外,还包括用户拿取约束、货道商品存在约束、货道摆放品类数约束以及同品类商品摆放约束,其中,用户拿取约束可以理解为预设用户在实际的使用重力货柜过程中,一次性拿取多件商品的情况下,其中用户从单个电子秤上拿取的商品品类数最多为2个品类;货道商品存在约束可以理解为由于货道中电子秤的商品摆放的面积限制,要求单个货道内所摆放的商品品类最多为3个品类;货道商品存在约束可以理解为重力货柜中的每个货道都需要摆放至少一个品类的商品,不得存在空置货道的情况;同品类商品摆放约束可以理解为同一品类的商品只能集中放置在少数货道内。需要说明的是,上述具体的数字仅作为对本公开实施例的说明,并非是用于限制本公开的保护范围,在此不作赘述。
在本公开的实施例中,每个品类的商品的商品高度不得超过重力货柜的货道高度,否则无法摆放进入货道,此即业务约束条件中的高度约束。其中,在满足互斥约束条件的情况下,当满足高度约束,即潜在布局组合中的每个商品的商品高度均小于货道高度的情况下,该潜在布局组合即为有效布局组合,反之,该潜在布局组合即被刨除,不能作为有效布局组合。
具体地,对于任一潜在布局组合S,height i为该组合S中第i个品类的商品高度,height scale为重力货柜的货道高度,依次判断该组合S中每个品类的商品高度,得到其中第i个品类的商品高度最大H满足如下公式(2):
H=max|height i|,i∈S
判断H与货道高度height scale的关系,如果满足max|height i|>height scale,i∈S,则排除该组合S,否则,该组合S即有效布局组合(在满足互斥约束条件的情况下)。
同理,某些商品之间具有互斥关系,不得摆放在同一货道中,此即业 务约束条件中的互斥约束。例如,商品咖啡要求是温的,但是商品雪糕要求是冰的,则温热的咖啡商品与冰凉的雪糕属于互斥商品,不得作为同一组合的组成商品放置在同一货道上。其中,在满足高度约束条件的情况下,当满足互斥约束的情况下,即潜在布局组合中的各个商品之间均不互斥,该潜在布局组合即为有效布局组合,反之,该潜在布局组合即被刨除,不能作为有效布局组合。
具体地,若对于一潜在布局组合S,其中,包括至少两个品类的商品sku 1及sku 2,若满足(sku 1,sku 2)互为互斥品类,则排除该组合S,相反,该组合S即有效布局组合(在满足高度约束条件的情况下)。
需要说明的是,在本公开的实施例中,上述的互斥约束和高度约束的业务约束条件实际上是可以同时对所有潜在布局组合进行的约束,此处不再赘述。
图3示意性示出了根据本公开另一实施例的商品布局数据的获取方法的流程图。
如图3所示,根据本公开的实施例,在操作S101的确定多个有效布局组合中每个有效布局组合的最小重量差中,包括子操作S310和子操作S320。
在子操作S310中,根据每个有效布局组合中的至少两个子组合的重量,确定对应最小重量差的混合整数模型;
在子操作S320中,根据混合整数模型,获取每个有效布局组合的最小重量差。
在每个有效布局组合S中,需要具有至少两个子组合,例如单个有效布局组合S包括子组合comb1和子组合comb2。每个子组合中至少具有两个品类的商品组成,也即每个有效布局组合中具有至少具有3个品类的商品。其中,每个子组合中组成的商品品类数由用户拿取约束来限定,即设用户在实际的使用重力货柜过程中,一次性拿取多件商品的情况下,其中用户从单个电子秤上拿取的商品品类数最多可以为2个品类。因此,每个子组合中的商品品类数可以为2个品类。其中,各个子组合之间具有商品品类的差异,即各个子组合不相同。
其中,在本公开的实施例中,每个子组合的重量满足一定的规划约束, 该规划约束为根据相应的一个有效布局组合S的第i个品类商品的重量、重力货柜的每个电子秤的测量误差以及第i个品类的商品的个体误差等所限定的计算条件。例如,单个有效布局组合S包括子组合comb1和子组合comb2,其满足如下规划约束的公式(3):
Figure PCTCN2021125244-appb-000003
Figure PCTCN2021125244-appb-000004
其中,
Figure PCTCN2021125244-appb-000005
w i代表S中第i个品类商品的重量,ε scale代表电子秤的测量误差,ε i代表第i个品类商品的个体误差,a,b满足:a+b≤p,c,d满足:c+d≤p,p为用户拿取约束所限定的用户单次拿取的最大商品品类数。需要说明的是,误差ε i和ε j均为决策变量,且上述参数均可以满足如下公式(4):
scale|≤E scale
i|≤E i
其中,E scale为电子秤的极限测量误差,E i为第i个品类的商品的极限个体误差。
进一步地,在上述的公开内容基础上,可以进一步地确定,对应上述单个有效布局组合中的最小重量差的混合整数模型满足如下目标函数的公式(5):
Figure PCTCN2021125244-appb-000006
对上述公式(5)作进一步的目标等价转换可以得到如下公式(6):
min z
Figure PCTCN2021125244-appb-000007
Figure PCTCN2021125244-appb-000008
以上述的公式(6)作为混合整数模型,采用上述的公式(3)、(4)对其进行求解,即可以得到对应每个有效布局组合的任意子组合的最小重量差Z。该最小重量差主要用于重量约束条件中,作为评价该有效布局组合S的重要指标,当最小重量差Z越小,则说明该组合S的重量区分度越 低,越有可能发生两种子组合的重量相似的情况,导致电子秤无法根据重量判断用户拿取的商品品类。相反,当最小重量差Z越大,则说明书该组合S的重量区分度越高,该组合S可以更好地作为本公开实施例的商品品类组合数据。
图4示意性示出了根据本公开另一实施例的商品布局数据的获取方法的流程图。
如图4所示,根据本公开的实施例,在操作S102的根据预设约束条件,从多个有效布局组合中获取至少两个当前布局组合作为商品布局数据之前,方法还包括操作S401。
在操作S401中,获取对应每个有效布局组合中的每个品类的商品的有效布局向量。
具体地,对于每个有效布局组合S而言,假定该组合S包含的各个品类的商品对应满足如下向量关系:
Figure PCTCN2021125244-appb-000009
其中,
Figure PCTCN2021125244-appb-000010
代表向量V t的第i个分量,1≤i≤n,若
Figure PCTCN2021125244-appb-000011
Figure PCTCN2021125244-appb-000012
时则代表该组合S包含第i个品类的商品,相反,当当
Figure PCTCN2021125244-appb-000013
时则代表该组合S不包含该第i个品类的商品。也即有效布局向量V t可以用于确定该组合S中具有商品品类数和商品名称等信息。
根据本公开的实施例,预设约束条件还包括:每个有效布局组合的组合布局模型和有效布局向量之间的品类约束,以及组合布局模型、有效布局向量与重力货柜的货道数量之间的货道约束。
此时,基于上述最小重量差和的求解,则可以对有效布局组合作进一步地筛选,将多个有效布局组合中的多个当前布局组合确定出作为本公开实施例的商品布局数据。
首先,本公开实施例的布局前提是,针对单个重力货柜的单个货道只分配一种商品组合,因此对于多个有效布局组合而言,其中的商品组合布局需要满足如下公式(7):
Figure PCTCN2021125244-appb-000014
Figure PCTCN2021125244-appb-000015
其中,其中allot jt用于反映是否在第j个货道分配第t种商品组合。具体地,当上述公式(7)的allot jt的求和值为1时,则说明把第t种商品组合分配到重力货柜的第j个货道上,相反,则不能将第t种商品组合分配到该第j个货道上。
其中,c i用于构成每个有效布局组合的商品组合布局模型,用于反映所有货道中被分配的商品布局数据的当前商品组合是否包含第i个品类的商品。具体地,当为所有货道分配的当前商品组合包含第i个品类的商品的次数大于1时,则c i=1,即该当前商品组合中包括该第i个品类的商品。当该次数等于0时,c i=0,则该当前商品组合中不包括该第i个品类的商品。也即根据该组合布局模型,可以求解出所有有效布局组合中的多个当前布局组合。其中,该组合布局模型即为本公开实施例的商品品类组合的目标函数,与上述的混合整数模型为同一类模型。
进一步地,为求解上述目标函数对应的组合布局模型,上述的目标函数需要满足如下公式(8):
Figure PCTCN2021125244-appb-000016
Figure PCTCN2021125244-appb-000017
其中,M为大数,可以设定满足:M=10 6
Figure PCTCN2021125244-appb-000018
为有效布局向量V t的对应该组合S包含第i个品类的商品向量。借此,可以用于固定c i与allot jt的之间的关系,以满足对应的单个当前布局组合S中包括的商品品类数最大,即公式(8)为上述的品类约束。
此外,对于上述的同品类商品摆放约束,对于同一品类商品,需要尽可能放置在较少的货道中,最多不要超过R个货道,因此货道约束满足如下公式(9):
Figure PCTCN2021125244-appb-000019
R即单个品类的商品可以分步的最多个货道数量,属于货道数量的上限。
需要说明的是,若实现对多个有效布局组合的筛选,并获得多个当前 布局组合,则需要同时以上述的品类约束和货道约束以及重量约束作为预设约束条件进行筛选。其中,对于多个有效布局组合中的下限重量差lb,其需要满足如下公式(10):
Figure PCTCN2021125244-appb-000020
lb≥θ
其中,diff t为上述的对应每个有效布局组合的任意子组合的最小重量差Z,其为电子秤所识别的最大误差。其中,θ为一电子秤所能识别的重量差变化的阈值,以使得电子能够识别每一次用户拿取动作对应的重力变化,且该变化必须为有效值,用于反映电子秤所具有的重量变化识别能力。
据此,对上述的公式(7)进行求解,即可以得到对应重力货柜中各个货道的商品布局数据,即多个当前布局组合,将该商品布局数据应用到重力货柜中进行商品布局,则可以在最小的运营成本下,提升用户在拿取商品时货柜对商品品类和件数变化的识别率,同时还可以保证货柜的利用率最大化,商品品类的多样化。
图5示意性示出了根据本公开另一实施例的商品布局数据的获取方法的流程图;
如图5所示,根据本公开的实施例,在操作S102的根据预设约束条件,从多个有效布局组合中获取至少两个当前布局组合作为商品布局数据之后,方法还包括操作S501。
在操作S501中,当至少两个当前布局组合中的商品品类数与待布局商品品类数相同,则对下限重量差进行最大化,以确定至少两个当前布局组合为商品布局数据。
在上述的组合布局模型的目标函数求解过程中,可以通过预设约束条件对多个有效布局组合的筛选,得到多个当前布局组合作为商品布局数据,应用至重力货柜的商品布局中。其中,若这些当前布局组合中所具有的商品品类数∑ ic i与商品池中商家所拟定的待布局商品品类数n完全相同时,即满足:s.t.∑ ic i=n时,则需要对上述的多个当前布局组合中的下限重量差进行最大化处理,即满足:max lb,然后对上述的组合布局模型对应的目标函数等作二次求解,以保证最终的商品布局数据的准确性和适用性。
因此,依据本公开的上述实施例,可以在考虑到商品个体误差以及电子秤测量误差的情况下,依据商品、货道等固定特征属性获取最优的商品品类组合作为商品布局数据,从而才能在已知电子秤读数发生变化的情况下唯一确定用户所拿取的商品品类。
图6示意性示出了根据本公开一实施例的商品布局数据的获取装置的组成图。需要注意的是,图6所示仅为可以应用本公开实施例的获取装置600的组成架构的示例,以帮助本领域技术人员理解本公开的技术内容,但并不意味着本公开实施例不可以用于其他设备、系统、环境或场景。
如图6所示,本公开的另一个方面提供了一种商品布局数据的获取装置600,包括:重量确定模块610和布局获取模块620,重量确定模块610用于确定多个有效布局组合中每个有效布局组合的最小重量差;布局获取模块620用于根据预设约束条件,从多个有效布局组合中获取至少两个当前布局组合作为商品布局数据,用于重力货柜中的一货道的商品布局;其中,预设约束条件包括对应多个有效布局组合中的下限重量差与对应至少两个当前布局组合的一当前布局组合的最小重量差之间的重量约束。
需要说明的是,上述的获取装置用于实现上述的商品布局数据的获取方法,在此不作赘述。
本领域技术人员应当理解,根据本公开的实施例的模块、子模块、单元、子单元中的任意多个、或其中任意多个的至少部分功能可以在一个模块中实现。根据本公开实施例的模块、子模块、单元、子单元中的任意一个或多个可以被拆分成多个模块来实现。根据本公开实施例的模块、子模块、单元、子单元中的任意一个或多个可以至少被部分地实现为硬件电路,例如现场可编程门阵列(FPGA)、可编程逻辑阵列(PLA)、片上系统、基板上的系统、封装上的系统、专用集成电路(ASIC),或可以通过对电路进行集成或封装的任何其他的合理方式的硬件或固件来实现,或以软件、硬件以及固件三种实现方式中任意一种或以其中任意几种的适当组合来实现。或者,根据本公开实施例的模块、子模块、单元、子单元中的一个或多个可以至少被部分地实现为计算机程序模块,当该计算机程序模块被运行时,可以执行相应的功能。
例如,重量确定模块610和布局获取模块620中的任意多个可以合并 在一个模块中实现,或者其中的任意一个模块可以被拆分成多个模块。或者,这些模块中的一个或多个模块的至少部分功能可以与其他模块的至少部分功能相结合,并在一个模块中实现。根据本公开的实施例,重量确定模块610和布局获取模块620中的至少一个可以至少被部分地实现为硬件电路,例如现场可编程门阵列(FPGA)、可编程逻辑阵列(PLA)、片上系统、基板上的系统、封装上的系统、专用集成电路(ASIC),或可以通过对电路进行集成或封装的任何其他的合理方式等硬件或固件来实现,或以软件、硬件以及固件三种实现方式中任意一种或以其中任意几种的适当组合来实现。或者,重量确定模块610和布局获取模块620中的至少一个可以至少被部分地实现为计算机程序模块,当该计算机程序模块被运行时,可以执行相应的功能。
本公开的另一个方面提供了一种重力货柜,包括:上述的商品布局数据的获取装置,用以实现上述的商品布局数据的获取方法,在此对其功能实现不作赘述。
其中,该重力货柜可以具有5层货架,每层货架可以有2个货道,每个货道的底部可以对应设置1个电子秤。该重力货柜可以用于上述的方法。
图7示意性示出了根据本公开实施例的适于实现上述商品布局数据的获取方法的电子设备的方框图。其中,图7示出的电子设备仅仅是一个示例,不应对本公开实施例的功能和使用范围带来任何限制。
本公开的另一个方面提供了一种电子设备,包括:一个或多个处理器和存储装置;存储装置用于存储一个或多个程序,其中,当一个或多个程序被一个或多个处理器执行时,使得一个或多个处理器实现上述的方法。
如图7所示,根据本公开实施例的电子设备700包括处理器701,其可以根据存储在只读存储器(ROM)702中的程序或者从存储部分708加载到随机访问存储器(RAM)703中的程序而执行各种适当的动作和处理。处理器701例如可以包括通用微处理器(例如CPU)、指令集处理器和/或相关芯片组和/或专用微处理器(例如,专用集成电路(ASIC)),等等。处理器701还可以包括用于缓存用途的板载存储器。处理器701可以包括用于执行根据本公开实施例的方法流程的不同动作的单一处理单元或者是多个处理单元。
在RAM 703中,存储有设备700操作所需的各种程序和数据。处理器701、ROM 702以及RAM 703通过总线704彼此相连。处理器701通过执行ROM 702和/或RAM 703中的程序来执行根据本公开实施例的方法流程的各种操作。需要注意,所述程序也可以存储在除ROM 702和RAM 703以外的一个或多个存储器中。处理器701也可以通过执行存储在一个或多个存储器中的程序来执行根据本公开实施例的方法流程的各种操作。
根据本公开的实施例,设备700还可以包括输入/输出(I/O)接口705,输入/输出(I/O)接口705也连接至总线704。设备700还可以包括连接至I/O接口705的以下部件中的一项或多项:包括键盘、鼠标等的输入部分706;包括诸如阴极射线管(CRT)、液晶显示器(LCD)等以及扬声器等的输出部分707;包括硬盘等的存储部分708;以及包括诸如LAN卡、调制解调器等的网络接口卡的通信部分709。通信部分709经由诸如因特网的网络执行通信处理。驱动器710也根据需要连接至I/O接口705。可拆卸介质711,诸如磁盘、光盘、磁光盘、半导体存储器等等,根据需要安装在驱动器710上,以便于从其上读出的计算机程序根据需要被安装入存储部分708。
根据本公开的实施例,根据本公开实施例的方法流程可以被实现为计算机软件程序。例如,本公开的实施例包括一种计算机程序产品,其包括承载在计算机可读存储介质上的计算机程序,该计算机程序包含用于执行流程图所示的方法的程序代码。在这样的实施例中,该计算机程序可以通过通信部分709从网络上被下载和安装,和/或从可拆卸介质711被安装。在该计算机程序被处理器701执行时,执行本公开实施例的系统中限定的上述功能。根据本公开的实施例,上文描述的系统、设备、装置、模块、单元等可以通过计算机程序模块来实现。
本公开的另一个方面提供了一种计算机可读存储介质,其上存储有可执行指令,该指令被处理器执行时使处理器实现上述的方法。
本公开的计算机可读存储介质可以是上述实施例中描述的设备/装置/系统中所包含的;也可以是单独存在,而未装配入该设备/装置/系统中。上述计算机可读存储介质承载有一个或者多个程序,当上述一个或者多个程序被执行时,实现根据本公开实施例的方法。
根据本公开的实施例,计算机可读存储介质可以是非易失性的计算机可读存储介质,例如可以包括但不限于:便携式计算机磁盘、硬盘、随机访问存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、便携式紧凑磁盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。在本公开中,计算机可读存储介质可以是任何包含或存储程序的有形介质,该程序可以被指令执行系统、装置或者器件使用或者与其结合使用。例如,根据本公开的实施例,计算机可读存储介质可以包括上文描述的ROM 702和/或RAM 703和/或ROM 702和RAM 703以外的一个或多个存储器。
本公开实施例的另一方面提供了一种计算机程序,计算机程序包括计算机可执行指令,指令在被执行时用于实现如上述的方法。
至此,已经结合附图对本公开实施例进行了详细描述。
附图中的流程图和框图,图示了按照本公开各种实施例的系统、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上,流程图或框图中的每个方框可以代表一个模块、程序段、或代码的一部分,上述模块、程序段、或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意,在有些作为替换的实现中,方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如,两个接连地表示的方框实际上可以基本并行地执行,它们有时也可以按相反的顺序执行,这依所涉及的功能而定。也要注意的是,框图或流程图中的每个方框、以及框图或流程图中的方框的组合,可以用执行规定的功能或操作的专用的基于硬件的系统来实现,或者可以用专用硬件与计算机指令的组合来实现。
本领域技术人员可以理解,本公开的各个实施例和/或权利要求中记载的特征可以进行多种组合和/或结合,即使这样的组合或结合没有明确记载于本公开中。特别地,在不脱离本公开精神和教导的情况下,本公开的各个实施例和/或权利要求中记载的特征可以进行多种组合和/或结合。所有这些组合和/或结合均落入本公开的范围。
以上对本公开的实施例进行了描述。但是,这些实施例仅仅是为了说明的目的,而并非为了限制本公开的范围。尽管在以上分别描述了各实施例,但是这并不意味着各个实施例中的措施不能有利地结合使用。本公开 的范围由所附权利要求及其等同物限定。不脱离本公开的范围,本领域技术人员可以做出多种替代和修改,这些替代和修改都应落在本公开的范围之内。
以上所述的具体实施例,对本发明的目的、技术方案和有益效果进行了进一步详细说明,所应理解的是,以上所述仅为本发明的具体实施例而已,并不用于限制本发明,凡在本发明的精神和原则之内,所做的任何修改、等同替换、改进等,均应包含在本发明的保护范围之内。

Claims (11)

  1. 一种商品布局数据的获取方法,包括:
    确定多个有效布局组合中每个有效布局组合的最小重量差;
    根据预设约束条件,从所述多个有效布局组合中获取至少两个当前布局组合作为所述商品布局数据,用于重力货柜的商品布局;
    其中,所述预设约束条件包括对应多个有效布局组合中的下限重量差与对应所述至少两个当前布局组合的一当前布局组合的最小重量差之间的重量约束。
  2. 根据权利要求1所述的方法,其中:
    在所述确定多个有效布局组合中每个有效布局组合的最小重量差之前,所述方法还包括:
    根据待布局商品品类数,确定多个潜在布局组合;
    根据业务约束条件,从所述多个潜在布局组合中确定所述多个有效布局组合。
  3. 根据权利要求2所述的方法,其中:
    所述业务约束条件包括所述每个有效布局组合中的每个品类的商品的商品高度与所述重力货柜的货道高度之间的高度约束,以及对应所述重力货柜的任一货道的每个有效布局组合中的至少两个品类的商品之间的互斥约束。
  4. 根据权利要求1所述的方法,其中:
    所述确定多个有效布局组合中每个有效布局组合的最小重量差,包括:
    根据所述每个有效布局组合中的至少两个子组合的重量,确定对应所述最小重量差的混合整数模型;
    根据所述混合整数模型,获取所述每个有效布局组合的最小重量差。
  5. 根据权利要求1所述的方法,其中:
    所述根据预设约束条件,从所述多个有效布局组合中获取至少两个当前布局组合作为所述商品布局数据之前,方法还包括:
    获取对应所述每个有效布局组合中的每个品类的商品的有效布局向量。
  6. 根据权利要求5所述的方法,其中:
    所述预设约束条件还包括:所述每个有效布局组合的组合布局模型和所述有效布局向量之间的品类约束,以及所述组合布局模型、所述有效布局向量与所述重力货柜的货道数量之间的货道约束。
  7. 根据权利要求1所述的方法,其中:
    所述根据预设约束条件,从所述多个有效布局组合中获取至少两个当前布局组合作为所述商品布局数据,所述方法还包括:
    当所述至少两个当前布局组合中的商品品类数与待布局商品品类数相同,则对所述下限重量差进行最大化,以确定所述至少两个当前布局组合为所述商品布局数据。
  8. 一种商品布局数据的获取装置,包括:
    重量确定模块,用于确定多个有效布局组合中每个有效布局组合的最小重量差;
    布局获取模块,用于根据预设约束条件,从所述多个有效布局组合中获取至少两个当前布局组合作为所述商品布局数据,用于重力货柜中的一货道的商品布局;
    其中,所述预设约束条件包括对应多个有效布局组合中的下限重量差与对应所述至少两个当前布局组合的一当前布局组合的最小重量差之间的重量约束。
  9. 一种重力货柜,包括:权利要求8所述的装置,以实现权利要求1-7中任一项所述的方法。
  10. 一种电子设备,包括:
    一个或多个处理器;
    存储装置,用于存储一个或多个程序,
    其中,当所述一个或多个程序被所述一个或多个处理器执行时,使得所述一个或多个处理器实现权利要求1-7中任一项所述的方法。
  11. 一种计算机可读存储介质,其上存储有可执行指令,该指令被处理器执行时使处理器实现权利要求1-7中任一项所述的方法。
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