CN111127107A - Dynamic goods picking path planning system - Google Patents
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Abstract
The invention relates to the technical field of market planning and discloses a dynamic goods picking path planning system which comprises data uploading modules, wherein the data uploading modules are connected with a computing module and a data statistical module through electric signals, the data statistical module comprises a primary classification acquisition module, a goods shelf data statistical module, a refrigeration and freezer cabinet data statistical module and a cost data statistical module, the data statistical module is connected with the first-level classification acquisition module, the goods shelf data statistical module, the refrigeration and freezer data statistical module and the cost data statistical module through electric signals, this developments route planning system of picking up goods, the mode that the automatic matching of use system calculated plans market inside, has guaranteed that the place in the market can be the most reasonable use, also distributes the most efficient in place simultaneously, has increased the rational utilization ratio in market place.
Description
Technical Field
The invention relates to the technical field of market planning, in particular to a dynamic goods picking path planning system.
Background
Along with the development of the times, modern markets are more and more, when the markets sell, the layout of commodities is required to be planned, the waste of space in the markets is avoided as much as possible, but when the layout of the markets is planned at present, the layout is generally manually planned, the planning mode may cause the omission of partial areas in the markets, and therefore a dynamic goods picking path planning system capable of planning the layout in the markets is required.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a dynamic goods picking path planning system which has the advantages of planning the layout of a shopping mall through the automatic calculation of the system and the like, and solves the problems.
(II) technical scheme
In order to achieve the above purpose, the invention provides the following technical scheme: dynamic goods route planning system of choosing, including data upload module, between the data upload module and between calculation module and the data statistics module through electric signal connection, the data statistics module includes that the one-level classification acquires the module, goods shelves data statistics module, it is cold-stored, freezer data statistics module and cost data statistics module, and data statistics module and one-level classification acquire the module, goods shelves data statistics module, it is cold-stored, pass through electric signal connection between freezer data statistics module and the cost data statistics module, calculation module includes goods shelves data calculation module, cost data calculation module, it is cold-stored, freezer data calculation module and income calculation module, and calculation module and goods shelves data calculation module, cost data calculation module, it is cold-stored, pass through electric signal connection between freezer data calculation module and the income calculation module. The data that the data upload module can receive user's upload, and the data of uploading specifically includes the volume data of loads such as skuID, goods shelves, market daily average sales volume, market cost data and commodity classification data, and wherein market daily average sales volume calculation mode specifically is:
(1) if the mode is uploading, the daily average sales is the uploaded sku sales/sales period;
(2) if the method is not in an uploading mode, the average daily sales volume is calculated according to the order
a) Counting the order range: the order has been completed;
b) time definition: order completion time;
c) sales volume: the sku pieces are summed.
Thereby the calculation module can with goods shelves data calculation module, cost data calculation module, cold-stored, freezer cabinet data calculation module and profit calculation module between cooperate and calculate the availability factor of goods shelves, concrete calculation mode is:
(1) acquiring all sku daily average sales of current store in historical N days (considering no sales of new stores, adopting an uploading mode);
(2) acquiring an inventory period (the default value is 3);
(3) the number of the stocks in each sku is sku daily average sales volume and stock period;
(4) acquiring a first-level classification of the commodity;
(5) counting all commodities under a certain primary classification, sum (stock depth x of each sku and single volume of each sku) being the total volume of the primary classification;
(6) calculating the volume of the shelf: the length x is wide, the x layers are high, and the number of the x layers is large;
(7) single shelf footprint (typical 0.5m shelf width + aisle width) x shelf length;
(8) shelf utilization rate: inputting parameters, and defaulting to 60%;
(9) outputting parameters:
a) the number of shelves required by the commodity classification 1 is equal to the total volume/single shelf volume of the commodity classification;
b) the number of shelves required by the commodity classification 2 is equal to the total volume/single shelf volume of the commodity classification;
c) .., and so on;
(10) the theoretical total shelf floor area value is sum (number of shelves required for product classification 1. single shelf floor area);
(11) floor space utilization (input value, typically 80%);
(12) the total occupied area of the goods shelf is equal to the theoretical value of the total occupied area of the goods shelf/the utilization rate of the occupied area.
Preferably, the first-level classification module can acquire all first-level classifications from the capital to the capital of the capital from the capital system, and simultaneously transmit the classification data to the data statistics module for big data operation, the shelf data statistics module can receive the volume data of the shelf uploaded by the data uploading module, and simultaneously upload the data to the calculation module for data calculation, the refrigeration and freezer data statistics module can count the volume data of the refrigeration and freezer uploaded by the data uploading module, and upload the data of the refrigeration and freezer to the calculation module for data calculation, and the cost data statistics module can count the market cost data uploaded by the data uploading module, and upload the counted data to the calculation module for data calculation.
Preferably, the calculation mode of the data calculation module for the refrigerating and freezing cabinets is as follows:
(1) calculating the total number of the frozen skus;
(2) the number of the freezers is equal to the total number of the freezers sku/the number of skus which can be contained in a single freezer;
(3) the total freezer footprint (number of freezers) and length of individual freezer (width of individual freezer + width of channel half 1 m);
(4) the refrigerator is also so counted.
Preferably, the calculation mode of the cost calculation module is specifically:
bin area-preceding calculation
One unit price (yuan/square meter per day) ═ input item
Monthly warehouse rental cost (ten thousand yuan) ═ warehouse area monovalent 30/10000
Number of people being input items
Input item of per capita wage (yuan)
Monthly labor cost (ten thousand yuan) ═ number of people per average wage/10000
The total cost per month (ten thousand yuan) is the monthly lease cost plus the monthly labor cost.
Preferably, the revenue calculating module calculates the revenue in a manner that:
area of storehouse (square meter) ═ area of storehouse calculated above
Unit price (Yuan/Single) is the average price of order (price is the price before discount, calculated by order table)
Annual sale (ten thousand yuan) ═ passenger unit price per day unit (calculated from order table) × 365/10000
Gross interest rate (%) ═ input term
Picking up goods warehouse floor effect (ten thousand/planch years) ═ annual sales volume/warehouse area
Shang Chao super plateau effect (ten thousand/one year) ═ input item
Average picking cost (labor + rent) ═ monthly total cost/monthly order number
Supermarket single average cost (manual + rent) ═ passenger single price (lease rate + manual rate)
Other sale cost (ten thousand per year) is guest unit price 0.03
The selling rate of the goods picking warehouse is (the average cost of goods picking warehouse bills + other selling costs)/the over-selling rate of the goods picking bill supplier is input item
Yield (year) of goods-picking storehouse is year sale amount (gross profit rate-goods-picking storehouse sale charge rate)
The net profit (year) is the annual sales amount (gross rate-the excess sales cost rate).
(III) advantageous effects
Compared with the prior art, the invention provides a dynamic goods picking path planning system, which has the following beneficial effects:
1. this developments route planning system of picking up goods, the mode that the automatic matching of use system calculated plans market inside, has guaranteed that the place in the market can be the most reasonable use, also distributes the most efficient in place simultaneously, has increased the rational utilization ratio in market place.
2. This developments route planning system of picking up goods uses calculation module to come to calculate the occupation of goods, can carry out the optimum position with goods and goods shelves and set up, avoids the unable normal goods of placing in the position that sets up of goods shelves, has improved the rate of utilization of goods shelves.
3. This dynamic route planning system of picking up goods uses the cost calculation module to calculate required cost, can let the user know required cost when planning, lets the user can be convenient under the condition of contrasting with the profit know profit and loss, has made things convenient for the user to calculate the profit.
4. This dynamic route planning system of picking up goods uses the income calculating module to calculate final income, and after long-time sale, the user can use the income calculating module to come to calculate fast and know the normal income after sale, and convenience of customers knows the income after long-time sale.
Drawings
FIG. 1 is a block diagram of the system of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the dynamic picking path planning system includes data uploading modules electrically connected to the calculating module and the data counting module, the data counting module includes a first-level classification obtaining module, a shelf data counting module, a refrigerating and freezing cabinet data counting module and a cost data counting module, the data statistical module is connected with the primary classification acquisition module, the goods shelf data statistical module, the refrigeration and freezer data statistical module and the cost data statistical module through electric signals, the calculation module comprises a goods shelf data calculation module, a cost data calculation module, a refrigeration and freezer data calculation module and a profit calculation module, and the calculation module is connected with the goods shelf data calculation module, the cost data calculation module, the refrigeration and freezer data calculation module and the income calculation module through electric signals.
The data that the data upload module can receive user's upload, and the data of uploading specifically includes the volume data of loads such as skuID, goods shelves, market daily average sales volume, market cost data and commodity classification data, and wherein market daily average sales volume calculation mode specifically is:
(1) if the mode is uploading, the daily average sales is the uploaded sku sales/sales period;
(2) if the method is not in an uploading mode, the average daily sales volume is calculated according to the order
a) Counting the order range: the order has been completed;
b) time definition: order completion time;
c) sales volume: the sku pieces are summed.
The first-level classification module can acquire all first-level classifications from the capital east to the capital east in the home system, the classification data are transmitted to the data statistics module for big data operation, the goods shelf data statistics module can receive the volume data of the goods shelves uploaded by the data uploading module, the data are uploaded to the calculation module for data calculation, the data statistics module can count the volume data of the refrigerated cabinets and the refrigerated cabinets uploaded by the data uploading module and upload the data of the refrigerated cabinets and the refrigerated cabinets to the calculation module for data calculation, and the cost data statistics module can count the market cost data uploaded by the data uploading module and upload the counted data to the calculation module for data calculation.
Thereby the calculation module can with goods shelves data calculation module, cost data calculation module, cold-stored, freezer cabinet data calculation module and profit calculation module between cooperate and calculate the availability factor of goods shelves, concrete calculation mode is:
(1) acquiring all sku daily average sales of current store in historical N days (considering no sales of new stores, adopting an uploading mode);
(2) acquiring an inventory period (the default value is 3);
(3) the number of the stocks in each sku is sku daily average sales volume and stock period;
(4) acquiring a first-level classification of the commodity;
(5) counting all commodities under a certain primary classification, sum (stock depth x of each sku and single volume of each sku) being the total volume of the primary classification;
(6) calculating the volume of the shelf: the length x is wide, the x layers are high, and the number of the x layers is large;
(7) single shelf footprint (typical 0.5m shelf width + aisle width) x shelf length;
(8) shelf utilization rate: inputting parameters, and defaulting to 60%;
(9) outputting parameters:
a) the number of shelves required by the commodity classification 1 is equal to the total volume/single shelf volume of the commodity classification;
b) the number of shelves required by the commodity classification 2 is equal to the total volume/single shelf volume of the commodity classification;
c) .., and so on;
(10) the theoretical total shelf floor area value is sum (number of shelves required for product classification 1. single shelf floor area);
(11) floor space utilization (input value, typically 80%);
(12) the total occupied area of the goods shelf is equal to the theoretical value of the total occupied area of the goods shelf/the utilization rate of the occupied area.
The data calculation module of the refrigerating and freezing cabinet calculates the refrigerating and freezing cabinet in the following way:
(1) calculating the total number of the frozen skus;
(2) the number of the freezers is equal to the total number of the freezers sku/the number of skus which can be contained in a single freezer;
(3) the total freezer footprint (number of freezers) and length of individual freezer (width of individual freezer + width of channel half 1 m);
(4) the refrigerator is also so counted.
The calculation mode of the cost calculation module is specifically as follows:
bin area-preceding calculation
One unit price (yuan/square meter per day) ═ input item
Monthly warehouse rental cost (ten thousand yuan) ═ warehouse area monovalent 30/10000
Number of people being input items
Input item of per capita wage (yuan)
Monthly labor cost (ten thousand yuan) ═ number of people per average wage/10000
The total cost per month (ten thousand yuan) is the monthly lease cost plus the monthly labor cost.
The profit calculation module calculates the profit in the following way:
area of storehouse (square meter) ═ area of storehouse calculated above
Unit price (Yuan/Single) is the average price of order (price is the price before discount, calculated by order table)
Annual sale (ten thousand yuan) ═ passenger unit price per day unit (calculated from order table) × 365/10000
Gross interest rate (%) ═ input term
Picking up goods warehouse floor effect (ten thousand/planch years) ═ annual sales volume/warehouse area
Shang Chao super plateau effect (ten thousand/one year) ═ input item
Average picking cost (labor + rent) ═ monthly total cost/monthly order number
Supermarket single average cost (manual + rent) ═ passenger single price (lease rate + manual rate)
Other sale cost (ten thousand per year) is guest unit price 0.03
The selling rate of the goods picking warehouse is (the average cost of goods picking warehouse bills + other selling costs)/the over-selling rate of the goods picking bill supplier is input item
Yield (year) of goods-picking storehouse is year sale amount (gross profit rate-goods-picking storehouse sale charge rate)
The net profit (year) is the annual sales amount (gross rate-the excess sales cost rate).
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (7)
1. Dynamic route planning system of picking up goods, including data upload module, its characterized in that: the data uploading module is connected with the calculating module and the data statistics module through electric signals, the data statistics module comprises a first-level classification acquisition module, a goods shelf data statistics module, refrigeration, a freezer data statistics module and a cost data statistics module, the data statistics module and the first-level classification acquisition module, the goods shelf data statistics module, refrigeration, the freezer data statistics module is connected with the cost data statistics module through electric signals, the calculating module comprises a goods shelf data calculating module, the cost data calculating module, refrigeration, the freezer data calculating module and a profit calculating module, the calculating module is connected with the goods shelf data calculating module through electric signals, the cost data calculating module, refrigeration, the freezer data calculating module and the profit calculating module are connected through electric signals.
2. The dynamic pick path planning system of claim 1, wherein: the data upload module can receive the data that the user uploaded, and the data of uploading specifically includes the volume data of loads such as skuID, goods shelves, market daily average sales volume, market cost data and commodity classification data, and wherein market daily average sales volume calculation mode specifically is:
(1) if the mode is uploading, the daily average sales is the uploaded sku sales/sales period;
(2) if the method is not in an uploading mode, the average daily sales volume is calculated according to the order
a) Counting the order range: the order has been completed;
b) time definition: order completion time;
c) sales volume: the sku pieces are summed.
3. The dynamic pick path planning system of claim 1, wherein: the first-level classification module can acquire all first-level classifications from the capital east to the capital east in the arriving system, simultaneously, the classification data are transmitted to the data statistics module for big data operation, the goods shelf data statistics module can receive the volume data of the goods shelves uploaded by the data uploading module, simultaneously, the data are uploaded to the calculation module for data calculation, the data statistics module for refrigeration and freezer can count the volume data of the refrigeration and freezer uploaded by the data uploading module, and upload the data of the refrigeration and freezer to the calculation module for data calculation, the cost data statistics module can count the market cost data uploaded by the data uploading module, and upload the counted data to the calculation module for data calculation.
4. The dynamic pick path planning system of claim 1, wherein: thereby the calculation module can cooperate between with goods shelves data calculation module, cost data calculation module, cold-stored, freezer cabinet data calculation module and the income calculation module and calculate the availability factor of goods shelves, and concrete calculation mode is:
(1) acquiring all sku daily average sales of current store in historical N days (considering no sales of new stores, adopting an uploading mode);
(2) acquiring an inventory period (the default value is 3);
(3) the number of the stocks in each sku is sku daily average sales volume and stock period;
(4) acquiring a first-level classification of the commodity;
(5) counting all commodities under a certain primary classification, sum (stock depth x of each sku and single volume of each sku) being the total volume of the primary classification;
(6) calculating the volume of the shelf: the length x is wide, the x layers are high, and the number of the x layers is large;
(7) single shelf footprint (typical 0.5m shelf width + aisle width) x shelf length;
(8) shelf utilization rate: inputting parameters, and defaulting to 60%;
(9) outputting parameters:
a) the number of shelves required by the commodity classification 1 is equal to the total volume/single shelf volume of the commodity classification;
b) the number of shelves required by the commodity classification 2 is equal to the total volume/single shelf volume of the commodity classification;
c) .., and so on;
(10) the theoretical total shelf floor area value is sum (number of shelves required for product classification 1. single shelf floor area);
(11) floor space utilization (input value, typically 80%);
(12) the total occupied area of the goods shelf is equal to the theoretical value of the total occupied area of the goods shelf/the utilization rate of the occupied area.
5. The dynamic pick path planning system of claim 4, wherein: the refrigerating and freezing cabinet data calculation module calculates the refrigerating and freezing cabinets in the following way:
(1) calculating the total number of the frozen skus;
(2) the number of the freezers is equal to the total number of the freezers sku/the number of skus which can be contained in a single freezer;
(3) the total freezer footprint (number of freezers) and length of individual freezer (width of individual freezer + width of channel half 1 m);
(4) the refrigerator is also so counted.
6. The dynamic pick path planning system of claim 1, wherein: the calculation mode of the cost calculation module is specifically as follows:
bin area-preceding calculation
One unit price (yuan/square meter per day) ═ input item
Monthly warehouse rental cost (ten thousand yuan) ═ warehouse area monovalent 30/10000
Number of people being input items
Input item of per capita wage (yuan)
Monthly labor cost (ten thousand yuan) ═ number of people per average wage/10000
The total cost per month (ten thousand yuan) is the monthly lease cost plus the monthly labor cost.
7. The dynamic pick path planning system of claim 1, wherein: the income calculation mode of the income calculation module is as follows:
area of storehouse (square meter) ═ area of storehouse calculated above
Unit price (Yuan/Single) is the average price of order (price is the price before discount, calculated by order table)
Annual sale (ten thousand yuan) ═ passenger unit price per day unit (calculated from order table) × 365/10000
Gross interest rate (%) ═ input term
Picking up goods warehouse floor effect (ten thousand/planch years) ═ annual sales volume/warehouse area
Shang Chao super plateau effect (ten thousand/one year) ═ input item
Average picking cost (labor + rent) ═ monthly total cost/monthly order number
Supermarket single average cost (manual + rent) ═ passenger single price (lease rate + manual rate)
Other sale cost (ten thousand per year) is guest unit price 0.03
The sales expense rate of the picking warehouse is (average picking warehouse order cost + other sales cost)/the price of the passenger order
Input term for business over sale rate
Yield (year) of goods-picking storehouse is year sale amount (gross profit rate-goods-picking storehouse sale charge rate)
The net profit (year) is the annual sales amount (gross rate-the excess sales cost rate).
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| CN202257679U (en) * | 2011-01-25 | 2012-05-30 | 郭曦 | Intelligent commodity and promotion recommendation system based on cloud analysis |
| CN104933381A (en) * | 2015-06-18 | 2015-09-23 | 潘杰 | Intelligent mobile picking system and method based on RFID |
| CN107067158A (en) * | 2017-03-01 | 2017-08-18 | 安徽谷之润食品有限公司 | A kind of New-style refrigeration house management system |
| CN108550008A (en) * | 2018-04-11 | 2018-09-18 | 南昌大学 | A kind of auxiliary based on mobile phone app matches goods and inventory management system |
| CN109447536A (en) * | 2018-08-28 | 2019-03-08 | 浙江工业大学 | A kind of warehouse Real-time Monitor Management method based on GIS |
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