Self-adaptive commodity layout optimization method and system based on intelligent vending machine

Abstract

The invention discloses a self-adaptive commodity layout optimization method and system based on an intelligent vending machine, and the method comprises the steps: recording the width information of each commodity, and calculating the minimum number of holes needed when each commodity is placed; operating each layer of goods channel, and when the current goods cannot be placed in the set layer, if the set layer is not the last layer, finding out the widest goods on the current layer, exchanging positions of the widest goods on the current layer and the last goods, adjusting the widest goods to the rightmost standard hole position, and then re-arranging the current layer; if the set layer is the last layer, checking whether the height of the commodity conforms to the limit or not, checking the use condition of the expansion width, and processing the placement position of the last commodity; and checking whether the layout of each layer of commodities meets all set constraint conditions or not, and calculating the space utilization rate of the commodity channels. The problems that in the prior art, the goods channel space utilization rate is low, space is prone to being wasted, flexibility is poor, and sales and inventory changes are difficult to adapt are solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of vending machines, and particularly relates to an adaptive commodity layout optimization method and system based on an intelligent vending machine. Background Art

[0002] In modern commerce, vending machines are widely used to provide convenience for people. However, at present, there are prominent problems in commodity layout and space utilization.

[0003] On the one hand, the layout of the cargo channels of traditional vending machines is fixed and difficult to adapt to commodities of different sizes. Large-sized commodities may not fit in or cause space waste, while small-sized commodities cannot make full use of the cargo channel space. This not only increases the replenishment cost but also limits the variety and quantity of commodities. Moreover, the existing goods loading algorithm is simple and only arranges them in the order of arrival, without considering the commodity size, sales volume, and cargo channel structure, resulting in low space utilization.

[0004] On the other hand, even if some vending machines are equipped with adjustable partitions, they lack intelligent space optimization algorithms. Staff can only rely on experience to adjust the partitions and cannot effectively improve space utilization. In addition, the existing system does not take into account the coordination of commodity characteristics and machine structure characteristics. For example, ignoring the height limit of the anti-theft board may lead to difficulties and damage in commodity delivery; the safe distance between commodities is not reasonably set, and they are easily squeezed against each other during delivery, affecting commodity quality and sales. Summary of the Invention

[0005] Therefore, the present invention provides an adaptive commodity layout optimization method and system based on an intelligent vending machine to solve the problems of low space utilization rate of the cargo channels in traditional technologies, easy space waste, poor flexibility, and difficulty in adapting to sales and inventory changes.

[0006] To achieve the above object, the present invention provides the following technical solutions: An adaptive commodity layout optimization method based on an intelligent vending machine, including the following steps:

[0007] Initialization stage: Obtain the basic parameters of the cargo channel, where the basic parameters include the total width and the available number of holes; read the size and quantity information of the commodities to be shelved; initialize the constraint conditions of the commodity layout;

[0008] Commodity preprocessing: Record the width information of each commodity and calculate the minimum number of holes required for placing each commodity;

[0009] Dynamic layout: Operate on each layer of the cargo channel. When the current commodity cannot be placed in the set layer:

[0010] If the set layer is not the last layer, find the widest item in the current layer, swap the position of the widest item in the current layer with the last item, adjust the widest item to the rightmost standard hole position, and then re-layout the current layer;

[0011] If the set layer is the last layer, check whether the height of the item meets the limit, check the usage of the extended width, and handle the placement position of the last item;

[0012] Optimization verification: Check whether the layout of the items on each layer meets all the set constraints, and calculate the space utilization rate of the aisle.

[0013] As a preferred solution of the adaptive commodity layout optimization method based on the intelligent vending machine, the formula for calculating the minimum number of holes required for placing each item is:

[0014]

[0015] In the formula, n i is the minimum number of holes required for the i-th item, w i is the width of the i-th item, and s is the width of a single standard hole;

[0016] The formula for adjusting the widest item to the width of the standard hole is:

[0017] w′ max =α·w max

[0018] In the formula, w′ max is the width of the widest item after adjustment, w max is the width of the widest item before adjustment, α is the compression coefficient, and 0 < α < 1. The adjusted width needs to satisfy w′ max ≤s, where s is the width of a single standard hole.

[0019] As a preferred solution of the adaptive commodity layout optimization method based on the intelligent vending machine, the formula for calculating the space utilization rate of the aisle is:

[0020]

[0021] In the formula, U is the space utilization rate, l i is the occupied length of the i-th item in the depth direction of the aisle, W is the total width of the aisle, L is the total depth of the aisle, and n is the number of items placed on this layer.

[0022] As a preferred solution of the adaptive commodity layout optimization method based on the intelligent vending machine, the dynamic layout further includes an adaptive width adjustment mechanism, compressing the occupied width of the item using the compression coefficient α, and automatically adjusting the distance d between adjacent items, d ≥ d min ;

[0023] The adaptive width adjustment mechanism includes dynamically calculating the remaining space. The formula for dynamically calculating the remaining space is:

[0024] W remain = W - W used

[0025] In the formula, W remain is the width of the remaining space, W is the total width of the cargo channel, and W used is the total width occupied by the goods already placed on the current layer.

[0026] As a preferred solution of the adaptive commodity layout optimization method based on an intelligent vending machine, the dynamic layout further includes in-layer optimization, inter-layer optimization, and overall optimization;

[0027] During in-layer optimization, by adjusting the arrangement order and compression width of the goods within the layer, make maximized and meet the constraint conditions, where w i is the width of the i-th commodity within the layer, and n is the number of goods placed on this layer;

[0028] During inter-layer optimization, make the height difference Δh between adjacent layers of goods within a preset range;

[0029] During overall optimization, aim to maximize the overall space utilization rate of the machine:

[0030]

[0031] In the formula, U total is the overall space utilization rate of the machine, t is the number of layers of the cargo channel, n j is the number of goods placed on the j-th layer, w ij , l ij are respectively the width and the length occupied in the depth direction of the i-th commodity on the j-th layer, W is the total width of the cargo channel, and L is the total depth of the cargo channel.

[0032] As a preferred solution of the adaptive commodity layout optimization method based on an intelligent vending machine, when dealing with the position of the last commodity, combine the volume of the commodity and the volume of the remaining available space in the cargo channel;

[0033] Volume of the commodity:

[0034] V j = w j ·h j ·l j

[0035] Volume of the remaining available space in the cargo channel:

[0036] V remain = W remain ·H remain ·Lremain

[0037] In the formula, V j is the volume of the j-th commodity, and w j , h j , l j are the width, height and depth lengths of the j-th commodity respectively, and V remain is the remaining available space volume of the goods channel, and W remain , H remain , L remain are the remaining width, height and depth lengths of the goods channel respectively.

[0038] The present invention also provides an adaptive commodity layout optimization system based on an intelligent vending machine, including:

[0039] An initialization module, configured to obtain basic parameters of the goods channel, where the basic parameters include the total width and the available number of holes; read the size and quantity information of the goods to be put on the shelf; initialize the constraint conditions of the commodity layout;

[0040] A commodity preprocessing module, configured to record the width information of each commodity and calculate the minimum number of holes required for placing each commodity;

[0041] A dynamic layout module, configured to operate on each layer of the goods channel. When the current commodity cannot be placed in the set layer:

[0042] If the set layer is not the last layer, find the widest commodity in the current layer, exchange the position of the widest commodity in the current layer with the last commodity, adjust the widest commodity to the rightmost standard hole and then re-layout the current layer;

[0043] If the set layer is the last layer, check whether the height of the commodity meets the limit, check the usage of the extended width, and process the placement position of the last commodity;

[0044] An optimization verification module, configured to check whether the layout of the commodities on each layer meets all the set constraint conditions and calculate the space utilization rate of the goods channel.

[0045] As a preferred solution of the adaptive commodity layout optimization system based on an intelligent vending machine, in the commodity preprocessing module, the formula for calculating the minimum number of holes required for placing each commodity is:

[0046]

[0047] In the formula, n i is the minimum number of holes required for the i-th commodity, w i is the width of the i-th commodity, and s is the width of a single standard hole;

[0048] In the dynamic layout module, the formula for adjusting the widest product to the standard aperture width is:

[0049] w′ max = α·w max

[0050] In the formula, w′ max is the width of the widest product after adjustment, w max is the width of the widest product before adjustment, α is the compression coefficient, and 0 < α < 1. The width after adjustment needs to satisfy w′ max ≤ s, where s is the width of a single standard aperture;

[0051] In the dynamic layout module, when dealing with the position of the last product, the volume of the product and the remaining available space volume of the aisle are combined;

[0052] Volume of the product:

[0053] V j = w j ·h j ·l j

[0054] Remaining available space volume of the aisle:

[0055] V remain = W remain ·H remain ·L remain

[0056] In the formula, V j is the volume of the j-th product, w j , h j , l j are the width, height, and depth direction lengths of the j-th product respectively, V remain is the remaining available space volume of the aisle, W remain , H remain , L remain are the remaining width, height, and depth direction lengths of the aisle respectively.

[0057] As an optimal solution of the adaptive product layout optimization system based on an intelligent vending machine, in the optimization verification module, the formula for calculating the space utilization rate of the aisle is:

[0058]

[0059] In the formula, U is the space utilization rate, l i is the occupied length of the i-th product in the depth direction of the aisle, W is the total width of the aisle, L is the total depth of the aisle, and n is the number of products placed on this layer.

[0060] As an optimal solution for the adaptive commodity layout optimization system based on intelligent vending machines, the dynamic layout module further includes an adaptive width adjustment unit, a commodity compression unit, and a spacing adjustment unit;

[0061] The adaptive width adjustment unit is used to dynamically calculate the remaining space. The formula for dynamically calculating the remaining space is:

[0062] W remain = W - W used

[0063] In the formula, W remain is the width of the remaining space, W is the total width of the cargo channels, and W used is the total width occupied by the commodities already placed on the current layer;

[0064] The commodity compression unit is used to compress the width occupied by the commodities with a compression coefficient α;

[0065] The spacing adjustment unit is used to automatically adjust the spacing d between adjacent commodities, where d ≥ d min ;

[0066] The dynamic layout module further includes an in-layer optimization unit, an inter-layer optimization unit, and an overall optimization unit;

[0067] The in-layer optimization unit is used to maximize and satisfy the constraint conditions by adjusting the arrangement order and compressed width of the commodities within the layer, where w is the width of the i-th commodity within the layer, and n is the number of commodities placed on this layer; i ;

[0068] The inter-layer optimization unit is used to make the height difference Δh between adjacent layers of commodities within a preset range when performing inter-layer optimization;

[0069] The overall optimization unit aims to maximize the overall space utilization rate of the whole machine:

[0070]

[0071] In the formula, U total is the overall space utilization rate of the whole machine, t is the number of layers of the cargo channels, n j is the number of commodities placed on the j-th layer, w ij , l ij are respectively the width and the length occupied in the depth direction of the i-th commodity on the j-th layer, W is the total width of the cargo channels, and L is the total depth of the cargo channels.

[0072] The beneficial effects of the present invention are as follows:

[0073] First, efficient use of space: Layout optimization combined with an adaptive width adjustment mechanism can flexibly adjust the aisle layout according to the size of the goods, effectively improving aisle space utilization, increasing the number of goods on display, reducing the number of replenishments, and lowering operating costs.

[0074] Second, the multi-level optimization strategy achieves comprehensive optimization from within the layer to the entire machine, automatically generates layout plans based on product and channel information, reduces manual intervention, improves layout efficiency and rationality, and enhances the level of intelligent operation management.

[0075] Third, the constraint treatment fully considers the height limit of the anti-theft board and the safe distance between goods, avoiding damage to goods due to structural problems or poor shipment, ensuring the quality of goods and normal sales, and reducing economic losses.

[0076] Fourth, the dynamic adjustment plan of goods can optimize the layout in real time according to sales and inventory conditions, ensure that popular goods are easy to obtain and slow-moving goods are reasonably placed, improve customer purchase convenience, enhance user shopping experience, and thus improve the overall sales performance of vending machines. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the drawings required for the implementation methods or the prior art descriptions are briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0078] The structures, proportions, sizes, etc. illustrated in this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with the technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantial technical significance. Any structural modification, change in proportion or adjustment of size shall still fall within the scope of the technical contents disclosed in the present invention without affecting the effects and purposes that can be achieved by the present invention.

[0079] Figure 1 A schematic flow chart of a method for optimizing the adaptive merchandise layout based on an intelligent vending machine provided by an embodiment of the present invention;

[0080] Figure 2 A schematic diagram of a channel movement scenario in the adaptive commodity layout optimization method based on an intelligent vending machine provided in an embodiment of the present invention;

[0081] Figure 3 A schematic diagram of a second aisle movement scenario in the adaptive commodity layout optimization method based on an intelligent vending machine provided in an embodiment of the present invention;

[0082] Figure 4Schematic diagram of lane movement scenario three in the adaptive commodity layout optimization method based on an intelligent vending machine provided by an embodiment of the present invention;

[0083] Figure 5 Schematic diagram of lane movement scenario four in the adaptive commodity layout optimization method based on an intelligent vending machine provided by an embodiment of the present invention;

[0084] Figure 6 Schematic diagram of the architecture of the adaptive commodity layout optimization system based on an intelligent vending machine provided by an embodiment of the present invention. Detailed implementation manners

[0085] The following specific embodiments illustrate the implementation manners of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0086] Embodiment 1

[0087] Refer to Figure 1 , Embodiment 1 of the present invention provides an adaptive commodity layout optimization method based on an intelligent vending machine, including the following steps:

[0088] S1. Initialization stage: Obtain the basic parameters of the lanes, where the basic parameters include the total width and the available number of holes; Read the size and quantity information of the commodities to be shelved; Initialize the constraint conditions of the commodity layout;

[0089] S2. Commodity preprocessing: Record the width information of each commodity, and calculate the minimum number of holes required for placing each commodity;

[0090] S3. Dynamic layout: Operate on each layer of lanes. When the current commodity cannot be placed in the set layer:

[0091] If the set layer is not the last layer, find the widest commodity in the current layer, exchange the positions of the widest commodity in the current layer and the last commodity, adjust the widest commodity to the rightmost standard hole, and then re-layout the current layer;

[0092] If the set layer is the last layer, check whether the height of the commodity meets the limit, check the usage of the extended width, and handle the placement position of the last commodity;

[0093] S4. Optimization verification: Check whether the layout of the commodities on each layer meets all the set constraint conditions, and calculate the space utilization rate of the lanes.

[0094] In this embodiment, in step S1, the total width of the aisle and the number of available holes determine the space range and quantity limit for the placement of goods, which is the basic framework for the layout. By reading the size and quantity information of the goods to be put on the shelves, the "materials" that need to be laid out can be clearly identified, which is convenient for subsequent planning. Initializing the constraints of the product layout, such as setting the height limit of the anti-theft plate and the safe spacing of the goods, ensures that the placement of the goods in the vending machine is both safe and meets the machine structure requirements, avoiding safety hazards or space waste caused by unreasonable product placement.

[0095] In this embodiment, in step S2, the formula for calculating the minimum number of holes required for placing each product is:

[0096]

[0097] Where n i is the minimum number of holes required for the i-th product, w i is the width of the i-th product, and s is the width of a single standard hole;

[0098] The formula for adjusting the widest product to the standard hole width is:

[0099] w′ max =α·w max

[0100] Where w′ max is the maximum width of the product after adjustment, w max is the widest product width before adjustment, α is the compression coefficient, and 0<α<1. The width after adjustment must satisfy w′ max ≤s, s is the width of a single standard hole.

[0101] Specifically, recording the product width information facilitates accurate arrangement of product positions during subsequent layout. The calculation of the minimum number of holes is based on the product width and the standard hole width. Because the product must be placed completely in the hole, dividing the product width by the standard hole width and rounding up can ensure that enough hole space is allocated for each product. For example, if the product width is 1.2 times the standard hole width, rounding up will result in 2 holes, ensuring that there is enough space to place the product and it will not be too small or placed unstably.

[0102] In this embodiment, in step S3, the dynamic layout also includes an adaptive width adjustment mechanism, using a compression coefficient α to compress the width occupied by the product and automatically adjusting the distance d between adjacent products, d≥d min ;

[0103] The adaptive width adjustment mechanism includes dynamically calculating the remaining space. The formula for dynamically calculating the remaining space is:

[0104] Wremain = W - W used

[0105] Wherein, W remain is the remaining space width, W is the total width of the aisle, and W used is the total width occupied by the goods already placed on the current layer.

[0106] Specifically, the adaptive width adjustment mechanism can be adjusted in real time according to the usage of the aisle space. Dynamically calculate the remaining space, and you can always know how much more goods width can be accommodated in the aisle. When the remaining space is insufficient, compress the width occupied by the goods through the compression coefficient, and reasonably adjust the placement width of the goods without damaging the goods. Automatically adjust the spacing between adjacent goods, which can not only ensure that the goods are closely arranged to make full use of the space, but also ensure that the spacing is not less than the safety spacing d min , to avoid mutual extrusion and damage of the goods, and achieve efficient utilization of space and safe storage of goods.

[0107] In a possible embodiment, in step S3, the dynamic layout further includes intra-layer optimization, inter-layer optimization, and overall optimization;

[0108] When performing intra-layer optimization, by adjusting the arrangement order and compression width of the goods within the layer, make maximized and meet the constraint conditions, where w i is the width of the i-th good within the layer, and n is the number of goods placed on this layer;

[0109] When performing inter-layer optimization, make the height difference Δh between adjacent layers of goods within a preset range;

[0110] When performing overall optimization, with the goal of maximizing the overall space utilization rate of the whole machine:

[0111]

[0112] Wherein, U total is the overall space utilization rate of the whole machine, t is the number of layers of the aisle, n j is the number of goods placed on the j-th layer, w ij , l ij are respectively the width and the occupied length in the depth direction of the i-th good on the j-th layer, W is the total width of the aisle, and L is the total depth of the aisle.

[0113] Specifically, intra-layer optimization adjusts the order of goods and compresses the width to maximize the total width of goods placed on each layer, while meeting constraints such as safety spacing and product height restrictions to make full use of the space on each layer. Inter-layer optimization controls the height difference of goods on adjacent layers within a preset range to avoid space waste caused by uncoordinated layouts of the upper and lower layers, such as the situation where the goods on the upper layer are too high and the space on the lower layer is idle. Overall optimization starts from the perspective of the entire machine, comprehensively considers the width and depth of goods on each layer, and optimizes with the goal of maximizing the space utilization of the entire machine to ensure that the space of the entire vending machine is used in the most reasonable way.

[0114] In this embodiment, in step S3, when processing the last commodity position, the volume of the commodity and the remaining available space volume of the aisle are combined;

[0115] Volume of the product:

[0116] V j =w j ·h j ·l j

[0117] The remaining available space volume in the cargo aisle:

[0118] V remain =W remain ·H remain ·L remain

[0119] Where V j is the volume of the jth product, w j 、h j , l j are the width, height and depth of the jth product, V remain W is the remaining available space volume in the cargo aisle. remain , H remain , L remain They are the remaining width, height and depth lengths of the aisle respectively.

[0120] Specifically, the last layer needs special treatment because there is no subsequent layer to adjust. Checking whether the height of the product meets the limit is to prevent the product from exceeding the height range allowed by the machine, affecting the normal operation of the machine or the safety of the product. Checking the use of the extended width is to make full use of the special design of the machine to place the product. Combining the volume of the product and the remaining available space volume of the aisle to handle the last product position can more accurately determine whether the product can be placed in the remaining space, and how to place it to maximize the use of the remaining space, ensuring the rationality and stability of space utilization.

[0121] In this embodiment, in step S4, the formula for calculating the space utilization of the cargo lane is:

[0122]

[0123] Wherein, U is the space utilization rate, l i is the occupied length of the i-th commodity in the depth direction of the aisle, W is the total width of the aisle, L is the total depth of the aisle, and n is the number of commodities placed on this layer.

[0124] Specifically, by checking whether the layout of commodities on each layer meets the constraint conditions, it is possible to promptly discover areas in the layout that do not meet the requirements, such as commodities exceeding the height limit of the anti-theft board, the distance between commodities being less than the safety distance, etc., ensuring the safety and rationality of commodity placement. Calculating the space utilization rate can quantify the optimization effect of the layout. By comparing the space utilization rates of different layout schemes, it is possible to determine whether the current layout has reached the optimal state. If not, the layout can be further adjusted and continuously improved to increase the space utilization rate.

[0125] The following provides application scenarios of the embodiments of the present invention, specifically as follows:

[0126] See Figure 2 , which shows the width composition of the aisle, divided into "formal width" and "expansion width". There are three commodities A, B, and C placed on the aisle, and the circular marks represent the fixed points on the aisle. This figure presents the initial state of commodity placement on the aisle, reflecting the basic concept of using different width areas for commodity layout in the present invention, laying the foundation for subsequent flexible adjustment of commodity positions and utilization of expansion space. See Figure 3 , compared with Figure 2 , the positions of the commodities on the aisle have changed, marked with "width vacated by moving the aisle". This indicates that during the commodity layout process, the space can be adjusted by moving the aisle to create space for the placement of new commodities (such as B), demonstrating the dynamic layout and adaptive width adjustment mechanism in the present invention, and improving the space utilization rate by flexibly changing the aisle layout to adapt to the placement requirements of different-sized commodities.

[0127] See Figure 4 , the aisle is divided into formal width and expansion width areas, and at this time, there are only commodities A and B on the aisle. Figure 4 Presents a state of the anti-theft board layer before new commodities are put on the shelves. Since it is the anti-theft board layer, the placement space of commodities needs to be within the formal width and expansion width ranges. At the same time, various constraint conditions brought by the anti-theft board need to be considered when new commodities are put on the shelves in the future, such as possible height restrictions, space layout requirements, etc.

[0128] See Figure 5 , on the basis of Figure 4 , a new commodity C is added to the aisle, and commodity B is placed in the expansion width area. Figure 5The annotation " Verify whether the height of the product using the extended width meets the standard. If not, cancel the listing of the new product." reflects the special feature of the anti-theft board layer. Due to the existence of the anti-theft board, when placing products using the extended width, in addition to paying attention to the space utilization in the width direction, it is also necessary to strictly verify the height of the product. If the height of the product does not meet the standard, it may affect the function of the anti-theft board or cause problems such as the product being unable to be shipped normally. Therefore, it is necessary to cancel the listing, which further reflects the consideration of the constraints of the special structure (anti-theft board) in the process of optimizing the product layout of the present invention to ensure the normal operation of the vending machine and the safe display of products.

[0129] Suppose there is an intelligent vending machine with 5 cargo channels, and the total width of each cargo channel is 500 mm, and the width of a single standard hole is 50 mm. There are 3 products to be listed, and the specific information is as follows:

[0130] Product Number Width (mm) Height (mm) Depth (mm) Quantity 1 80 100 120 5 2 120 110 130 3 3 60 90 110 8

[0131] Traditional layout method (without using the method of the present invention)

[0132] Place the products in sequence according to the product order without considering space optimization. Taking the first layer as an example, first place Product 1, occupying holes, and the remaining width is 500 - 80 = 420 mm; then place Product 2, occupying holes, and the remaining width is 420 - 120 = 300 mm; then place Product 3, occupying holes. Placing in this way will result in space waste and may also cause the situation that larger-sized products cannot be placed later. According to this method, the total number of products placed on the 5 layers of this vending machine is limited. For example, only 18 products may be placed.

[0133] Calculation process using the layout method of the present invention:

[0134] First, initialization and preprocessing

[0135] Obtain the cargo channel parameters and product information: It is known that the intelligent vending machine has 5 cargo channels, the total width of each cargo channel is W = 500 mm, and the width of a single standard hole is s = 50 mm. The information of the products to be listed is as follows:

[0136] Product Number Width (mm) Height (mm) Depth (mm) Quantity 1 80 100 120 5 2 120 110 130 3 3 60 90 110 8

[0137] Calculate the minimum number of holes required for each product:

[0138] Product 1: holes;

[0139] Product 2: holes;

[0140] Product 3: holes.

[0141] Second, dynamic layout (taking the first layer as an example, the other layers are similar)

[0142] Start placing products: Give priority to considering the space occupied by large-sized products, and try to place Product 2.

[0143] Place Product 2, which occupies a width of 120 mm and 3 holes. At this time, the remaining space width W remain = W - 120 = 500 - 120 = 380 mm.

[0144] Place Product 1: Then place Product 1. Since Product 1 has a width of 80 mm and occupies 2 holes. However, considering the subsequent product placement and space utilization, calculate the impact of the remaining space after placing Product 1 on the subsequent product placement. After placing Product 1, the remaining space width W remain = 380 - 80 = 300 mm.

[0145] Place Product 3: Product 3 has a width of 60 mm and occupies 2 holes. At this time, when placing Product 3, apply the adaptive width adjustment mechanism, and appropriately adjust the product spacing according to the remaining space situation (assuming the minimum spacing is 10 mm) to ensure that more products can be placed in the limited space. After placing Product 3, record the total width W of the products already placed on the current layer used = 120 + 80 + 60 = 260 mm.

[0146] Optimization within the layer: Check whether the product layout on the current layer meets the requirement of maximizing the total width of the products placed on each layer. By calculating and comparing the total widths in different arrangement orders, determine whether the current layout is optimal. For example, try to exchange the placement orders of Product 1 and Product 3, calculate the total width and compare it with the current layout. If the total width in the new order is larger and still meets the constraints such as hole positions and spacing, then make adjustments. After inspection, in the current layout (w1 = 80, w2 = 120, w3 = 60), and it meets the constraint condition that the product spacing is greater than or equal to 10 mm, so no adjustment is needed.

[0147] Consider expanding the width (if necessary): Assume that after placing the above products, there are still other products to be placed, but the remaining space is insufficient. At this time, check whether there is available expanded width (assuming this vending machine has an expanded width function, and the expanded width is 100 mm). Calculate whether the sum of the expanded width and the remaining space can meet the placement requirements of the subsequent products. If it can meet the requirements, then re-adjust the product layout according to the product size and the expanded width situation, and at the same time verify whether the product height meets the standard (assuming there is a height limit of 150 mm, and the heights of all products meet the requirements).

[0148] Third, inter-layer optimization

[0149] After placing the first layer, when placing the second layer of goods, consider the height difference between adjacent layers of goods. The maximum height of the goods in the first layer is 110 mm (the height of Goods 2), and the reasonable range of the height difference between adjacent layers of goods is set to ±20 mm. Therefore, for the second layer, it is preferred to place goods with a height between 110 - 20 = 90 mm and 110 + 20 = 130 mm. According to this principle, combined with the quantity and size of the goods, place the goods in sequence. The process is similar to that of the first layer, and at the same time, in-layer optimization is continuously carried out during the placement process.

[0150] Fourth, overall optimization

[0151] After each layer is placed, according to the formula (where t is the number of lanes, here t = 5; n j is the number of goods placed on the j-th layer; w ij and l ij are the occupied lengths in the width and depth directions of the i-th good on the j-th layer respectively; assuming the total depth of the lane L = 200 mm), calculate the overall space utilization rate of the whole machine.

[0152] According to the calculation results, if the overall space utilization rate of the whole machine does not reach the expected value, return to the previous steps to adjust the layout of the goods on each layer. For example, readjust the arrangement order of the goods within the layer, further optimize the spacing between the goods, and reasonably utilize the expanded width, etc., to improve the overall space utilization rate of the whole machine.

[0153] Fifth, optimization verification

[0154] Check the constraint conditions: Check whether the layout of the goods on each layer meets all the set constraint conditions, including whether the spacing between the goods is greater than or equal to the minimum spacing of 10 mm, whether the height of the goods meets the height limit of 150 mm, etc. If there are situations that do not meet the constraint conditions, adjust the layout of the goods in a timely manner.

[0155] Calculate the space utilization rate: Calculate the space utilization rate of each layer (n is the number of goods placed on this layer), and then calculate the overall space utilization rate of the whole machine. For example, if Goods 2, 1, and 3 are each placed 1 piece on the first layer, calculate its space utilization rate:

[0156]

[0157] Calculate the space utilization rate of other layers in the same way, and finally calculate the overall space utilization rate U total . After multiple adjustments and optimizations, finally make the overall space utilization rate of the whole machine reach a relatively high level, and achieve the goal of placing 25 goods.

[0158] Through the above comparison process, it can be seen that compared with the traditional layout method, the present invention can place a larger number of products in the same vending machine space, effectively improving the space utilization rate, and thus may reduce the replenishment frequency and lower the operating cost.

[0159] Embodiment 2

[0160] Refer to Figure 6 , Embodiment 2 of the present invention also provides an adaptive product layout optimization system based on an intelligent vending machine, including:

[0161] Initialization module 001, configured to obtain the basic parameters of the cargo channel, where the basic parameters include the total width and the available number of holes; read the size and quantity information of the products to be shelved; initialize the constraint conditions of the product layout;

[0162] Product preprocessing module 002, configured to record the width information of each product and calculate the minimum number of holes required for placing each product;

[0163] Dynamic layout module 003, configured to operate on each layer of the cargo channel. When the current product cannot be placed in the set layer:

[0164] If the set layer is not the last layer, find the widest product on the current layer, exchange the positions of the widest product on the current layer and the last product, adjust the widest product to the rightmost standard hole position, and then re-layout the current layer;

[0165] If the set layer is the last layer, check whether the product height meets the limit, check the usage of the extended width, and process the placement position of the last product;

[0166] Optimization verification module 004, configured to check whether the layout of the products on each layer meets all the set constraint conditions and calculate the space utilization rate of the cargo channel.

[0167] In this embodiment, in the product preprocessing module 002, the formula for calculating the minimum number of holes required for placing each product is:

[0168]

[0169] In the formula, n i is the minimum number of holes required for the i-th product, w i is the width of the i-th product, and s is the width of a single standard hole;

[0170] In the dynamic layout module 003, the formula for adjusting the widest product to the standard hole width is:

[0171] w′ max =α·w max

[0172] Where, w' max is the adjusted maximum product width, w max is the maximum product width before adjustment, α is the compression coefficient, and 0 < α < 1. The adjusted width needs to satisfy w' max ≤ s, where s is the width of a single standard hole position;

[0173] In the dynamic layout module 003, when processing the position of the last product, the volume of the product and the remaining available space volume in the goods channel are combined;

[0174] Volume of the product:

[0175] V j = w j ·h j ·l j

[0176] Remaining available space volume in the goods channel:

[0177] V remain = W remain ·H remain ·L remain

[0178] Where, V j is the volume of the jth product, w j , h j , l j are respectively the width, height, and depth direction lengths of the jth product, V remain is the remaining available space volume in the goods channel, W remain , H remain , L remain are respectively the remaining width, height, and depth direction lengths of the goods channel.

[0179] In this embodiment, in the optimization verification module 004, the formula for calculating the space utilization rate of the goods channel is:

[0180]

[0181] Where, U is the space utilization rate, l i is the occupied length of the ith product in the depth direction of the goods channel, W is the total width of the goods channel, L is the total depth of the goods channel, and n is the number of products placed on this layer.

[0182] In a possible embodiment, the dynamic layout module 003 further includes an adaptive width adjustment unit 301, a product compression unit 302, and a spacing adjustment unit 303;

[0183] The adaptive width adjustment unit 301 is used to dynamically calculate the remaining space, and the formula for dynamically calculating the remaining space is:

[0184] W remain = W - W used

[0185] Wherein, W remain is the remaining space width, W is the total width of the goods aisle, and W used is the total width occupied by the goods already placed on the current layer;

[0186] The commodity compression unit 302 is used to compress the occupied width of the commodity with a compression coefficient α;

[0187] The spacing adjustment unit 303 is used to automatically adjust the spacing d between adjacent commodities, d ≥ d min ;

[0188] The dynamic layout module 003 further includes an in-layer optimization unit 304, an inter-layer optimization unit 305, and an overall optimization unit 306;

[0189] The in-layer optimization unit 304 is used to maximize and meet the constraint conditions by adjusting the arrangement order and compression width of the commodities within the layer, where w is the width of the i-th commodity within the layer, and n is the number of commodities placed on this layer; i is the width of the i-th commodity within the layer, and n is the number of commodities placed on this layer;

[0190] The inter-layer optimization unit 305 is used to make the height difference Δh between adjacent layers of commodities within a preset range when performing inter-layer optimization;

[0191] The overall optimization unit 306 aims to maximize the overall space utilization rate of the machine:

[0192]

[0193] Wherein, U total is the overall space utilization rate of the machine, t is the number of layers of the goods aisle, n j is the number of commodities placed on the j-th layer, w ij , l ij are respectively the width and the occupied length in the depth direction of the i-th commodity on the j-th layer, W is the total width of the goods aisle, and L is the total depth of the goods aisle.

[0194] It should be noted that for the information interaction, execution process, etc. between the above-mentioned system modules, since they are based on the same concept as the method embodiment in Embodiment 1 of the present application, the technical effects brought by them are the same as those of the method embodiment of the present application. For the specific content, reference can be made to the description in the method embodiment shown above in the present application, and details will not be repeated here.

[0195] Embodiment 3

[0196] Embodiment 3 of the present invention provides a non-transitory computer-readable storage medium, in which program codes for an adaptive commodity layout optimization method based on an intelligent vending machine are stored, and the program codes include instructions for executing the adaptive commodity layout optimization method based on the intelligent vending machine in Embodiment 1 or any possible implementation manner thereof.

[0197] The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center integrating one or more available media. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid-state disk (SSD)), etc.

[0198] Embodiment 4

[0199] Embodiment 4 of the present invention provides an electronic device, including: a memory and a processor;

[0200] The processor and the memory complete communication with each other through a bus; the memory stores program instructions executable by the processor, and the processor can execute the adaptive commodity layout optimization method based on the intelligent vending machine in Embodiment 1 or any possible implementation manner thereof by calling the program instructions.

[0201] Specifically, the processor can be implemented by hardware or by software. When implemented by hardware, the processor can be a logic circuit, an integrated circuit, etc.; when implemented by software, the processor can be a general-purpose processor, which is implemented by reading software codes stored in the memory. The memory can be integrated in the processor or can be located outside the processor and exist independently.

[0202] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.).

[0203] Obviously, those skilled in the art should understand that the above-mentioned modules or steps of the present invention can be implemented by a general-purpose computing device. They can be concentrated on a single computing device or distributed over a network composed of multiple computing devices. Optionally, they can be implemented by program codes executable by the computing device. Thus, they can be stored in a storage device and executed by the computing device. And in some cases, the steps shown or described can be executed in a sequence different from that here, or they can be separately fabricated into individual integrated circuit modules, or multiple modules or steps among them can be fabricated into a single integrated circuit module for implementation. In this way, the present invention is not limited to any specific combination of hardware and software.

[0204] Although the present invention has been described in detail above with general descriptions and specific embodiments, based on the present invention, some modifications or improvements can be made, which are obvious to those skilled in the art. Therefore, these modifications or improvements made without departing from the spirit of the present invention all fall within the scope of the present invention claimed.

Claims

1. An adaptive commodity layout optimization method based on intelligent vending machines, characterized in that: The following steps are involved: Initialization phase: obtain the basic parameters of the aisle, including the total width and the number of available holes; read the size and quantity information of the goods to be put on the shelves; initialize the constraints of the product layout; Product preprocessing: record the width information of each product and calculate the minimum number of holes required for placing each product; Dynamic layout: Operate on each aisle. When the current product cannot be placed in the set layer: If the set layer is not the last layer, find the widest product in the current layer, swap the widest product with the last product in the current layer, adjust the widest product to the rightmost standard hole position, and then rearrange the current layer; If the set layer is the last layer, check whether the product height meets the limit, check the usage of the expanded width, and process the placement of the last product; Optimization verification: Check whether the layout of each layer of goods meets all the set constraints and calculate the space utilization of the aisle.

2. The method for optimizing the adaptive commodity layout based on the intelligent vending machine according to claim 1 is characterized in that: The formula for calculating the minimum number of holes required for placing each product is: Where n i is the minimum number of holes required for the i-th product, w i is the width of the i-th product, and s is the width of a single standard hole; The formula for adjusting the widest product to the standard hole width is: w′ max =α·w max Where w′ max is the maximum width of the product after adjustment, w max is the widest product width before adjustment, α is the compression coefficient, and 0<α<1. The width after adjustment must satisfy w′ max ≤s, s is the width of a single standard hole.

3. The method for optimizing the adaptive commodity layout based on the intelligent vending machine according to claim 1 is characterized in that: The formula for calculating the space utilization of the cargo lane is: Where U is the space utilization rate, l i is the length occupied by the ith product in the depth direction of the aisle, W is the total width of the aisle, L is the total depth of the aisle, and n is the number of products placed on this layer.

4. The method for optimizing the adaptive commodity layout based on the intelligent vending machine according to claim 1 is characterized in that: The dynamic layout also includes an adaptive width adjustment mechanism, using a compression coefficient α to compress the width occupied by the product and automatically adjusting the distance d between adjacent products, d≥d min ; The adaptive width adjustment mechanism includes dynamically calculating the remaining space. The formula for dynamically calculating the remaining space is: IN remain =WW used Where W remain is the remaining space width, W is the total width of the aisle, and W used The total width occupied by the products placed on the current layer.

5. The method for optimizing the adaptive commodity layout based on the intelligent vending machine according to claim 1 is characterized in that: The dynamic layout also includes intra-layer optimization, inter-layer optimization and overall optimization; When optimizing within a layer, by adjusting the order of products within the layer and compressing the width, Maximize and satisfy the constraints, where w i is the width of the i-th product in the layer, and n is the number of products placed in the layer; When optimizing between layers, the height difference Δh of commodities on adjacent layers is kept within a preset range; When optimizing the whole system, the goal is to maximize the space utilization of the whole system: Where U total is the space utilization rate of the whole machine, t is the number of cargo aisles, n j is the number of goods placed on the jth layer, w ij , l ij are the width and depth occupied lengths of the ith product in the jth layer, W is the total width of the aisle, and L is the total depth of the aisle.

6. The method for optimizing the adaptive commodity layout based on an intelligent vending machine according to claim 1, characterized in that: When processing the last product location, consider the volume of the product and the remaining available space in the aisle. Volume of the product: V j =w j ·h j ·l j The remaining available space volume in the cargo aisle: V remain =W remain ·H remain ·L remain Where V j is the volume of the jth product, w j 、h j , l j are the width, height and depth of the jth product, V remain W is the remaining available space volume in the cargo aisle. remain , H remain , L remain They are the remaining width, height and depth lengths of the aisle respectively.

7. The adaptive commodity layout optimization system based on intelligent vending machines is characterized by: include: An initialization module is used to obtain basic parameters of the cargo channel, including the total width and the number of available holes; Read the size and quantity information of the products to be put on the shelves; initialize the constraints of the product layout; The product pre-processing module is used to record the width information of each product and calculate the minimum number of holes required for placing each product; The dynamic layout module is used to operate each layer of the cargo aisle. When the current product cannot be placed in the set layer: If the set layer is not the last layer, find the widest product in the current layer, swap the widest product with the last product in the current layer, adjust the widest product to the rightmost standard hole position, and then rearrange the current layer; If the set layer is the last layer, check whether the product height meets the limit, check the usage of the expanded width, and process the placement of the last product; The optimization verification module is used to check whether the layout of each layer of goods meets all the set constraints and calculate the space utilization of the aisle.

8. The adaptive commodity layout optimization system based on intelligent vending machines according to claim 7 is characterized in that: In the commodity preprocessing module, the formula for calculating the minimum number of holes required for placing each commodity is: Where n i is the minimum number of holes required for the i-th product, w i is the width of the i-th product, and s is the width of a single standard hole; In the dynamic layout module, the formula for adjusting the widest product to the standard hole width is: w′ max =α·w max Where w′ max is the maximum width of the product after adjustment, w max is the widest product width before adjustment, α is the compression coefficient, and 0<α<1. The width after adjustment must satisfy w′ max ≤s, s is the width of a single standard hole; In the dynamic layout module, when processing the last product position, the volume of the product and the remaining available space volume of the aisle are combined; Volume of the product: V j =w j ·h j ·l j The remaining available space volume in the cargo aisle: V remain =W remain ·H remain ·L remain Where V j is the volume of the jth product, w j 、h j , l j are the width, height and depth of the jth product, V remain W is the remaining available space volume in the cargo aisle. remain , H remain , L remain They are the remaining width, height and depth lengths of the aisle respectively.

9. The adaptive commodity layout optimization system based on intelligent vending machines according to claim 7 is characterized in that: In the optimization verification module, the formula for calculating the space utilization of the cargo lane is: Where U is the space utilization rate, l i is the length occupied by the ith product in the depth direction of the aisle, W is the total width of the aisle, L is the total depth of the aisle, and n is the number of products placed on this layer.

10. The adaptive commodity layout optimization system based on intelligent vending machines according to claim 7, characterized in that: The dynamic layout module also includes an adaptive width adjustment unit, a commodity compression unit and a spacing adjustment unit; The adaptive width adjustment unit is used to dynamically calculate the remaining space. The formula for dynamically calculating the remaining space is: IN remain =WW used Where W remain is the remaining space width, W is the total width of the aisle, and W used The total width occupied by the products placed on the current layer; The commodity compression unit is used to compress the width occupied by the commodity using a compression coefficient α; The spacing adjustment unit is used to automatically adjust the spacing d between adjacent commodities, d≥d min ; The dynamic layout module also includes an intra-layer optimization unit, an inter-layer optimization unit and an overall optimization unit; The layer optimization unit is used to adjust the order of commodities in the layer and the compression width so that Maximize and satisfy the constraints, where w i is the width of the i-th product in the layer, and n is the number of products placed in the layer; The inter-layer optimization unit is used to make the height difference Δh of commodities on adjacent layers within a preset range during inter-layer optimization; The overall optimization unit is used to maximize the space utilization of the entire machine: Where U total is the space utilization rate of the whole machine, t is the number of cargo aisles, n j is the number of goods placed on the jth layer, w ij , l ij are the width and depth occupied lengths of the ith product in the jth layer, W is the total width of the aisle, and L is the total depth of the aisle.

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