KR102315856B1 - Rider Auto-Allocation System for Food Delivery - Google Patents

Abstract

A rider automatic dispatch management system for food delivery according to the present invention comprises: a rider DB that stores the rider information for a plurality of riders performing delivery; an order input module that receives the order information comprising a delivery item, an affiliated store name, an affiliated store location, and a delivery location from an affiliated store; an order counting module that determines the number of pieces of the order information generated during a specific perspective and time; a dispatch module that differentially adjusts the number of dispatches and dispatch time of the rider included in the rider DB by reflecting the specific perspective and time based on the number of pieces of order information; and a delivery execution module that transmits the order information to the rider based on the number of dispatches and the dispatch time. Therefore, the present invention is capable of automatically adjusting the number of dispatches and the dispatch time of the order information.

Description

Rider Auto-Allocation System for Food Delivery

The present invention relates to a rider automatic dispatch management system for food delivery, wherein the rider is automatically dispatched on the system for the food delivery order for which the delivery order is created, but by adjusting the dispatch time and the number of dispatches dispatched to the rider, the delivery efficiency is increased. , relates to a rider automated dispatch management system for food delivery.

Recently, as the non-face-to-face market becomes active and the restaurant market shrinks due to the aftermath of Corona 19, the demand for delivery is increasing rapidly, and the demand for delivery service is also increasing at a rapid pace.

Delivery agency refers to a 'delivery brokerage service' business in which a delivery service is paid to a delivery person by charging a monthly membership fee and delivery fee from the seller on behalf of the restaurant's delivery service.

With the development of the food service industry such as small business owners and small franchises, it is necessary to use an agency rather than hiring a delivery person belonging to the restaurant according to the sales and expansion of the sales area for restaurants that did not provide delivery services. It is gaining popularity because it reduces the cost of delivery and frees the delivery man from liability for accidents.

At this time, Korean Patent No. 10-1843099 (title of invention: delivery agent relay operation system using network and delivery agent relay operation method using network network) is registered in relation to the technology for relaying delivery service.

The prior art is a relay operation system that relays and operates a delivery agent between customers, product sales affiliates, delivery relay agencies, delivery drivers, and remote central servers through a network, comprising: a delivery relay operation central server; a POS terminal device provided in each delivery request affiliate store registered in the delivery relay operation central server; a delivery relay agent terminal device provided at the delivery agent agency for each area registered in the delivery relay operation central server and exchanges delivery agent information from the delivery relay operation central server and the POS terminal device; The delivery relay operation is interlocked with the central server, the delivery driver application provided in the delivery driver terminal device; and a customer application interlocked with the delivery relay operation central server and provided on the customer's terminal device, wherein the delivery relay operation central server receives delivery request information along with delivery order information from the POS terminal device. A terminal device information processing unit, an agency information processing unit that receives the processing status of the delivery agency for each area from the delivery relay agency terminal device, and a customer information processing unit that provides merchant information and delivery progress information to the customer application, and a delivery machine information processing unit for providing the merchant's delivery request and delivery order information to the delivery machine application, wherein the POS terminal device information processing unit communicates with the POS terminal device to provide merchant information, customer information, and order products. It is made to receive information, sales information, product recovery information, and the agency information processing unit allocates and designates unique ID information for each delivery driver and registers it, and communicates with the terminal device of the delivery agency agency for each area to communicate with the delivery driver information and delivery agent information and statistical information are exchanged in real time, and the customer information processing unit receives customer location information including the customer location and contact information from the POS terminal device and stores it in the database, and the delivery location from the delivery driver terminal device is provided in real time and delivers information on expected delivery arrival time and delivery progress and unique ID information given to the delivery driver to the customer's application, and the delivery driver information processing unit receives from the terminal device of the delivery agency for each area Stored merchant information, order information, customer information, fee information, and delivery completion information in a database, the POS terminal device includes a product processing unit for storing sales information in the database; a reception processing unit for storing order information including delivery location information, customer contact information and product information in a database, and receiving and processing; a delivery agent request unit for processing the delivery agent request information including the order information and information on whether or not to collect the goods to be transmitted to the delivery relay agent terminal device; Sales purchase processing unit that automatically calculates the purchase amount and sales amount, including a fee according to the customer's payment method and a delivery agent fee, upon completion of delivery; and a delivery status check unit configured to receive the delivery status provided from the delivery relay operation central server or the delivery relay agency terminal device in real time. Management; a delivery agent reception unit receiving the delivery request information including affiliate store information, order information, customer information, and product collection information from the delivery agent request unit; A location information extraction unit for extracting and monitoring the location information of the delivery driver in real time; a matching processing unit for matching between an affiliated store and a delivery driver of an optimal distance based on the delivery request information received from the delivery agency reception unit and the location information of the delivery driver extracted from the location information extraction unit; Delivery agency order unit for transmitting the delivery request information to the delivery driver extracted from the matching processing unit to the delivery driver application; a delivery completion processing unit configured to receive delivery completion information from the delivery driver's terminal device, and to settle and manage sales information according to delivery completion; a central server interworking processing unit interlocked so that all information and processes performed in the respective units are provided to the delivery relay operation central server; And when the delivery request is received from the delivery agent reception unit, the delivery request information is transmitted to a plurality of delivery driver terminal devices, and selection information indicating that a delivery driver is designated from the delivery driver application for the delivery request information is received. , including a delivery auction execution unit for designating the delivery driver as the delivery person in charge, the matching processing unit is configured to first designate the delivery driver specified in the delivery auction execution unit, and the delivery agency order unit sends the delivery request information to the designated delivery driver terminal is configured to transmit to the device, and when the delivery auction execution unit does not receive the selection information for a preset time, the corresponding delivery request information is processed by the matching processing unit, and the matching processing unit is optimal for the location information of the affiliated store Match the location information of the delivery driver on the street, firstly match the delivery driver who has received the delivery completion information from the delivery completion processing unit, and if there is no matching delivery driver, secondarily match with the delivery driver waiting at the affiliated store If the number of times information is included in the delivery request information, it is calculated whether a predetermined time has elapsed from the time when the delivery to the customer is completed, and then the optimal distance between the delivery driver and the customer and the affiliated store is extracted. to match the collection delivery driver, and to provide the matching collection delivery driver with collection information including the location of the customer and the location of the recovered goods and merchants, and the delivery driver application receives a delivery request from the terminal device of the delivery relay agency. A status processing unit that registers whether processing is possible, an acceptance processing unit that obtains delivery information from the delivery relay agency terminal device, outputs it on the screen, and accepts and processes delivery service, a completion processing unit that processes whether delivery is completed or not, and the current location in real time A location transmitting unit for transmitting, and an interlocking processing unit interworking to provide all information performed in each unit to the delivery relay operation central server and the delivery relay agency terminal device, wherein the customer application displays product information of each affiliated store A product display unit to say, and a product It includes an order processing unit that orders the product, and a location confirmation unit that receives and confirms the location and expected arrival time of the delivery driver for the ordered product in real time from the delivery relay operation central server, POS terminal device, or delivery relay agency terminal device, Information, product information, price information, order progress, and delivery status are provided, but in conjunction with the GPS system, the location and expected arrival time of the delivery driver are displayed on the map. A delivery agency relay operation system using a network configured to determine whether the unique ID information matches and display the determination result, and the location check unit is configured to display the location of the delivery driver on the map using the GPS system is presenting

In the case of rider dispatch in such a delivery agency, there was a limitation in that it is not easy to control the number of orders and dispatch times for each rider according to time zones and road conditions in matching between riders and delivery information.

Therefore, in order to solve the above-described problems, as an automatic rider dispatch management system for food delivery, the number and time of delivery trains dispatched to riders are differentially adjusted based on the number of order information generated during a specific time and time. Therefore, there is a need to develop an automatic rider dispatch management system for food delivery that maximizes delivery efficiency.

The present invention is a rider automatic dispatch management system for food delivery, which enables automatic adjustment of the number of dispatches and dispatch times of order information assigned to riders by reflecting time and time based on the number of order information input from affiliated stores Its main purpose is to provide

Another object of the present invention is to receive a time for food delivery pickup from an affiliated store, and further adjust the dispatch time based on the input pickup time.

Another object of the present invention is to generate statistical data by comparing the delivery pickup time and the actual rider's waiting time, and based on this, it is possible to adjust the number of dispatches and dispatch times.

An additional object of the present invention is to graph the waiting time by time and hour for each individual affiliated store, and to determine the trend of waiting time for affiliated stores based on this graph, and to reflect this in the dispatch time.

It is a further object of the present invention to reflect the evaluation contents to the number of dispatched vehicles and dispatch time adjustments by allowing the rider to evaluate the affiliated stores.

In order to achieve the above object, the rider automatic dispatch management system for food delivery according to the present invention, the rider DB for storing rider information for a plurality of riders performing delivery; an order input module for receiving order information including a delivery item, a merchant name, a merchant location, and a delivery location from an affiliated store; an order counting module for determining the number of the order information generated during a specific time and time; a dispatch module for differentially adjusting the number and dispatch time of the riders included in the rider DB by reflecting the specific time and time based on the number of order information; It characterized in that it comprises; a delivery execution module for transmitting the order information to the rider based on the number of dispatches and the dispatch time.

Furthermore, the order information further includes a pickup request time for the delivery item, and the system identifies the waiting time that the rider waits for the pickup of the delivery item for a specific affiliate store in the previously performed delivery. Including; and, the dispatch module differentiates the number of dispatches and dispatch times of the riders included in the rider DB by reflecting the waiting time at the specific time and time based on the number of order information characterized by regulating.

In addition, the system classifies the order information generated for each affiliate store based on at least one of an order time, a delivery item, an order amount, a payment method, a pickup request time, and a waiting time to generate and display statistical data Analysis module; further comprising, the dispatch module, the number and dispatch of the rider included in the rider DB by reflecting the waiting time and the statistical data at the specific time and time based on the number of order information It is characterized in that the time is differentially controlled.

In addition, the system includes a graph generating unit that graphs a specific time point at which the waiting time in the delivery previously performed for each affiliate store is taken as a time section, and a time section to which the time when the order information is generated in the time section belongs Specifically, a graph generating module including a fluctuation grasping unit for understanding the rising and falling trend of the waiting time for the corresponding section; further comprising, the dispatch module, the specific time and time based on the number of the order information It is characterized in that by further reflecting the rising and falling trend of the waiting time, the number and dispatch time of the riders included in the rider DB are differentially adjusted.

Rider automatic dispatch management system for food delivery according to the present invention,

1) By receiving order information including delivery item, franchise name, franchise location, and delivery location from affiliated stores, and reflecting time and time in the order information, the number and dispatch time of order information assigned to riders can be automatically adjusted. ,

2) Identify the pick-up request time for delivery items from the affiliated store and the waiting time that the rider actually waited at the affiliated store, and differentially adjust the number of dispatches and dispatch times by reflecting the rider's waiting time;

3) To generate statistical data on the order information generated for each affiliate store, and to reflect the statistical data in the differential adjustment of the number of dispatches and dispatch times, and at the same time,

4) By graphing the specific time point of waiting time for each affiliate store as a visual section, the rising and falling trend of waiting time was judged, and based on this, it was possible to differentially control the number of dispatches and dispatch times.

5) It has the effect of being able to receive the evaluation sentence for the franchisee in the delivery that has been previously performed from the rider, analyze it, calculate a numerical value, and reflect it in the differential adjustment of the number of dispatches and dispatch time.

1 is a conceptual diagram showing a schematic configuration of a system of the present invention.
Fig. 2 is a block diagram showing the overall configuration of the system of the present invention;
3 is a conceptual diagram illustrating an example of a graph of the present invention.
Figure 4 is a conceptual diagram illustrating an example of a graph showing the waiting time of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. The accompanying drawings are not drawn to scale, and like reference numbers in each drawing refer to like elements.

1 is a conceptual diagram showing a schematic configuration of a system of the present invention.

Referring to Figure 1, the rider automatic dispatch management system for food delivery of the present invention consists of an orderer (1), an affiliated store (2), a rider (3), and a central control server (4).

The orderer (1) is a person who wants to receive and use a delivery item, that is, food delivered through the food delivery of the present invention. In general, the orderer (1) enters the delivery item and delivery location on the application or website provided for the food delivery order for food. Request delivery. At this time, for food delivery order, the orderer (1) must have a separate terminal capable of installing an application for delivery order, such as a smartphone or tablet PC, or have a desktop PC or laptop computer to access the website. is of course In addition, since an order for food delivery may be made over a wire, a food delivery order may be made by calling the affiliated store 2 through a smartphone.

The affiliated store 2 is a providing entity that cooks and provides food based on the order generated by the orderer 1, and provides food to the orderer 1 who has ordered food through the rider automatic dispatch management system of the present invention. In addition, the affiliated store 2 inputs order information including the delivery item and delivery location input from the orderer 1 to the central control server 4, which will be described later, and the name of the affiliated store and the affiliated store location. At this time, the order information input is preferably may be made through a POS device input to the affiliated store 2 or an application installed on a smartphone or tablet PC owned by the affiliated store owner.

Therefore, the affiliated store 2 of the present invention is most preferably a delivery order from the orderer 1 through a POS (point-of-sale(s): point-of-sale(s)) terminal device provided in the store. , and communicates with the central control server (4) to be able to call the rider (3) to perform delivery.

Rider (3) as a subject that performs food delivery in the present invention, it serves to deliver food to the orderer (1) by receiving a delivery item from the affiliated store (2) and processing it to be delivered to the delivery location. These riders (3) communicate with the central control server (4) through a rider terminal such as a smartphone in hand, and receive an assignment for food delivery performed from the central control server (4) (distribution is made) and delivered will perform

The central control server 4 of the present invention is a subject that receives order information from the aforementioned affiliated store 2 and dispatches the rider 3 to perform delivery for each order information. That is, it can be said that it is a matching subject that matches the rider 3 for each order information, and can also serve as a management role for order information. This central control server 4 means hardware having a CPU and a storage means in a state equipped with a communication unit and a transmission means to communicate with the affiliated store terminals such as the above-described rider terminals and POS devices provided in the affiliated stores 2 . By doing so, a series of modules and specific functions thereof to be described later can be derived by software to be executed in this CPU.

Such a central control server 4 is a central processing unit (CPU) and a program that can be executed in the central processing unit on a hardware basis having storage means such as a memory and a hard disk, that is, software is installed and can execute this software. A series of specific configurations for such software will be described later as structural units called 'modules', 'parts', and 'interfaces'.

The central control server 4 temporarily and/or permanently stores signals (or data) processed therein. RAM (Random Access Memory, not shown) and ROM (ROM: Read-Only Memory, not shown) city), and may include a processor. In addition, the central control server 4 may be implemented in the form of a system on chip (SoC) including at least one of a graphic processing unit, RAM, and ROM.

The processor may include one or more cores (not shown) and a graphic processing unit (not shown) and/or a connection path (eg, a bus, etc.) for transmitting and receiving signals to and from other components.

The memory may store programs (one or more instructions) for executing and controlling a module or a unit to be described later. Programs stored in the memory may be divided into a plurality of modules according to functions.

The steps of a method or algorithm described in relation to an embodiment of the present invention may be implemented directly in hardware, as a software module executed by hardware, or by a combination thereof. A software module may contain random access memory (RAM), read only memory (ROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, hard disk, removable disk, CD-ROM, or It may reside in any type of computer-readable recording medium well known in the art to which the present invention pertains.

That is, the components of the present invention may be implemented as a program (or an application) to be executed in combination with a computer, which is hardware, and stored in a medium. The components of the present invention may be implemented as software programming or software components, and similarly, embodiments may include various algorithms implemented as data structures, processes, routines, or combinations of other programming constructs, including C, C++ , Java, assembler, etc. may be implemented in a programming or scripting language. Functional aspects may be implemented in an algorithm running on one or more processors.

The configuration of these 'modules' or 'parts' or 'interfaces' is installed and stored in the storage means of the main server (force server), and software or hardware such as FPGA or ASIC executed via the CPU and memory. it means. In this case, the configuration of 'module', 'unit', and 'interface' is not limited to hardware, and may be configured to be in an addressable storage medium or may be configured to reproduce one or more processors. As an example, 'module' or 'part' or 'interface' refers to components such as software components, object-oriented software components, class components and task components, processes, functions, and properties. , procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays and variables.

The functions provided by these 'modules' or 'units' or 'interfaces' may be combined into a smaller number of components and 'units' or 'modules' or additional components and 'units' or 'modules'. can be further separated.

Hereinafter, a detailed configuration and function thereof will be described based on such a macroscopic configuration.

2 is a block diagram showing the overall configuration of the system of the present invention.

Referring to Figure 2, the rider automatic dispatch management system for food delivery of the present invention, lidar DB 100, order input module 200, order counting module 300, dispatch module 400, delivery execution It is characterized in that it is configured to include a module (500).

The rider DB 100 performs a function of storing rider information about the rider 3 who performs delivery, where the rider information means the rider 3's name, age, gender, and the rider 3 is delivered. It includes the type of transportation used for the service (types and models of general vehicles, motorcycles, bicycles, etc.), delivery history, available working hours and days, and delivery areas (province/city/gun/gu/eup/myeon). Therefore, it can be said that the information on the individual rider (3) is integrated as rider information and made into a database as the rider DB (100).

The order input module 200 serves to receive order information through the POS terminal provided in the affiliated store 2 , preferably the affiliated store 2 . At this time, the order information refers to the delivery item that is the name of the food to be delivered as described above, the franchise name that is the name of the affiliated store (2), the affiliated store location that is the address of the affiliated store (2), and received input from the orderer (1). The shipping address, which is the shipping address, is included.

In other words, the affiliated store 2 receives an order for food delivery from the orderer 1, generates order information for the received order, and transmits it to the central control server 4, preferably the order input module 200. You will be entering your order information into the system.

The order counting module 300 is interlocked with the above-described order input module 200 to determine the number of order information input from the affiliated store 2, where preferably the order information generated by specific time and time is figure out the number

Here, the term "by specific time" refers to, for example, determining the number of order information generated at 1:40 p.m. based on 1:40 p.m., and "by specific time" is based on 1:40 p.m. In this case, the number of order information generated during one hour from 1:00 PM to 2:00 PM is identified.

Therefore, in addition to grasping the number of order information generated at a specific time (it may be xx hours xx minutes, further xx hours xx minutes xx seconds), by time (1 pm to 2 pm, 2 pm to 3 pm) (preferably at intervals of 1 hour), to determine the number of generated order information.

To give a more detailed example, for example, as of March 28, 2021, 3 order information was created at 6:25 pm, and from 6 pm to 7 pm on March 28, a total of 120 Assuming that order information has been created, the number of order information created at that time at 6:25 pm on March 28, 2021 is 3, and the number of order information created for each hour including the time is 110. do.

Therefore, as described above through the order counting module 300, the number of orders generated for each specific time and each specific time is identified, and through this, the number of dispatches of the rider 3 and the time are adjusted in the dispatch module 400 to be described later. will be used to

The dispatch module 400 is a function of differentially adjusting the number of dispatches and dispatch times of food delivery to the rider 3 based on the number of order information for each specific time and time identified in the order counting module 300 described above. carry out

Here, by reflecting the number of order information generated for each specific time and time, the number of dispatches and dispatch times of the riders 3 stored in the rider DB 100 are differentially adjusted. As identified in the order counting module 300, when 6:35 p.m. on March 28, 2021 is the standard, the time is based on 6:35, and the hourly time is based on the corresponding time zone, that is, 6:00 to 7:00. do it with

Therefore, it is to differentially control the number of dispatches and dispatch times of the rider 3 for food delivery for each hour divided by 24 hours, and for each accurate time within the corresponding time.

For example, suppose that the number of riders 3 stored in the rider DB 100 is 3 people, and 3 order information was created at 6:25 pm as of March 28, 2021, and March 28 Assume that a total of 120 order information is created from 6 pm to 7 pm on the same day. In this case, one order information is allocated to each rider (3) for the order information generated at 6:25 by time, and 40 pieces of order information are allocated to each rider (3) by time.

At this time, basically, the number of order information generated by time and time may vary, and the number of order information assigned to each rider 3 by time and time, that is, the number of dispatches, can be differentially adjusted.

In the case of dispatch time, there are many cases where orders are generally crowded during lunch/dinner time, and there are many cases of order information at a specific time, for example, around 6:30 pm in the case of dinner even in the corresponding time period. However, in this time period, the road conditions are often not good due to overlapping with commuting time, so as soon as the order information is created, the rider (3) must be dispatched to quickly pick up the food from the affiliated store (2) and deliver it to the delivery location. there will be However, at relatively off-peak hours, for example, around 3 or 4 pm, the number of order information may be relatively small, and furthermore, the traffic condition is not bad (there are not many cars on the road, so there is a high probability that there will be no traffic congestion). Therefore, even if there is a delay between the order information generation time and the rider dispatch time, the rider 3 can arrive at the affiliate store 2 on time to pick up the food and deliver it to the delivery location.

Therefore, the dispatch time here means the time to actually assign the rider 3 to the food delivery, and to provide order information to the rider 3 and perform the actual delivery. That is, after the order information is generated, the time at which the order information is provided to the actual rider 3 may be the dispatch time. To explain through the above example, if the order information is created at 6:35 pm on March 28, 2021, the dispatch time may be, for example, 3 minutes later, at 6:38 pm on March 28, 2021. have.

That is, such a dispatch time may vary depending on the number of order information generated for each hour and time (if the order information is excessively generated, the order information may not be immediately assigned to the rider 3, that is, the dispatch It may not be done, so the dispatch time may be longer.) Or it may vary depending on the traffic conditions for each hour and time. (If the route is delayed, the delivery must be made faster to deliver on time, and in a situation where the road is not blocked, delivery is possible even if the route is relaxed.) there will be

The delivery execution module 500 transmits order information to the rider 3 stored in the rider DB 100 based on the number of vehicles differentially adjusted through the dispatch module 400 and the dispatch time, thereby actually delivering food. function that makes it run. Here, the order information is preferably transmitted to the rider terminal possessed by the rider 3, and the rider 3 performs food delivery through the transmitted order information.

Therefore, through the automatic rider dispatch management system for food delivery of the present invention, in the prior art, the rider 3 catches a call for delivery order information and the rider 3 applies for delivery, and for this, the central control server (4) ), to get away from the cumbersome method in which the execution request and execution approval for delivery were doubled, and the rider (3) for the order information on the central control server (4) is automatically assigned and processed for food delivery It has the effect of increasing the efficiency.

Further here, in general, delivery means that the rider (3) stops by the location of the merchant (2), picks up food for delivery, and brings it to the delivery location designated by the orderer (1). do.

Therefore, when inputting order information, the affiliate store 2 may further receive a pickup request time for picking up the corresponding food by reflecting the time it takes for the corresponding food to be cooked. Here, the pickup request time is, for example, assuming that order information is created at 6:35 pm on March 28, and if it takes 15 minutes to cook and pack food, it is sent from the affiliate store (2) at 6:50 pm can be entered. That is, when the order information is generated, a predetermined time after the order information generation time is the pickup request time by reflecting the time taken for cooking and packaging the food from the time of creation of the order information.

That is, the pickup request time, which is input from the affiliate store (2) and can be further included in the order information, is the time when the cooking and packaging of the food to be delivered is expected to be completed, and the rider (3) arrives at the affiliate store location. It can be said that it is the scheduled time to pick up the food.

However, this is the time input from the affiliated store 2, and a specific affiliated store 2 may input the pickup request time in line with the cooking and packing time, but some affiliated stores 2 request a pickup earlier than the cooking and packing time. You can also enter the time. For example, assuming that order information is created at 6:35 pm on March 28, and it takes 15 minutes to cook and pack food, a certain merchant (2) will request pickup at 6:50 pm on March 28. may be input, but the other affiliated store (2) may input a pickup request time at 6:45 pm on March 28.

Therefore, in the former case, when the rider 3 arrives at the affiliated store 2 at 6:50, the food is cooked and packaged, so the food can be picked up and delivered immediately without waiting, but in the latter case Even if the rider (3) arrives at the affiliate store (2) at 6:45, food and packaging are not complete, so there may be cases where the rider (3) has to wait at the affiliate store (2) for at least 5 minutes.

In this case, a time loss occurs for the rider 3 due to waiting. In order to prevent such a waiting time from occurring as much as possible, the system of the present invention may further include a waiting time determination module 600, and Based on it, it is possible to differentially adjust the number and dispatch time of the rider 3 .

Such a waiting time identification module 600 identifies the waiting time waiting for the rider 3 to pick up the delivery item, that is, the food to be delivered, at the specific affiliated store 2 in the previously performed delivery, that is, the delivery that has already been completed. . This waiting time is basically different for each affiliate store (2), so it is based on understanding each affiliate store (2). it would be preferable

It is preferable that this waiting time is basically input by the rider terminal possessed by the rider 3, and in this waiting time input, the rider 3 waits for several minutes to how many hours to manually input the waiting time Alternatively, the rider 3 may input the arrival time of arrival at the affiliated store 2, and input the actual delivery item, that is, the time the food was picked up, so that the difference between the food pickup time and the arrival time is the waiting time. may be calculated. Preferably, the difference between the food pickup time and the arrival time when the rider 3 arrives at the affiliate store 2 is input as the waiting time.

For example, if the pickup request time is 6:50 pm, the rider (3) arrives at the affiliate (2) at 6:52, and the actual food pickup time is 6:55, the waiting time is calculated as 3 minutes do.

When the waiting time is calculated in this way, the number of orders generated for each specific time and time, and the waiting time are reflected, so that the number and dispatch time for food delivery of the rider 3 are differentially adjusted. Here, the waiting time may be preferentially reflected in the adjustment of the dispatch time in general.

For example, if a specific affiliated store (2) has a long waiting time, that is, if the delay from pickup request time to actual food pickup is long (2), dispatch time is more leisurely, that is, rider (3) compared to the time when order information is generated. ) takes a long time until the time allotted for the delivery of the food in question, so that other deliveries are prioritized before that, or the dispatch time can be adjusted by first distributing the order information created after that. .

Therefore, through this configuration, the number of order information generated by time and time, as well as the number of order information generated by time and time, the road traffic condition for each hour, and the delay time until the actual food pickup for each affiliate store (2), that is, the waiting time of the rider (3) By reflecting the number of food delivery dispatches for individual riders (3), and differential adjustment of dispatch times for actually performing dispatches, riders (3) can wait for food pickup at the affiliated store (2). It is possible to minimize waste of time and delays in delivery that may occur through it, and maximize delivery efficiency.

In addition, if delivery continues in this way, statistics on delivery made by affiliate store (2) based on order time, delivery item, order amount, payment method, pickup request time, and calculated waiting time for each affiliate store (2) can be calculated. To this end, the system of the present invention may further include a statistical analysis module 700 .

Statistical analysis module 700 classifies the order information generated for each affiliate store 2 based on at least one of order time, delivery item, order amount, payment method, pickup request time, and waiting time to generate and display statistical data perform the function

Such a statistical analysis module 700 may be provided to the affiliated store 2 so that the affiliated store 2 can grasp the order amount, payment method, order time, delivery item, etc. for the store at a glance, or Based on the statistical data on the system, that is, the central control server 4, based on the pickup request time and waiting time included in the statistical data, to be used for differential adjustment of the dispatch time and the number of dispatches through the dispatch module 400 You may.

If we explain statistical data for example here, in the case of order time, in which time period the order was received the most, for the item of delivery, which item received the most orders, the order amount is the amount of the total delivered items over a certain period, that is, What is the total order amount, the payment method may indicate by what method payment was made, and the like. The pick-up request time may be the pick-up request time input for an individual order or the average of the pick-up request time by hour and time input at the affiliate store (2) for a certain period of time, and the waiting time is the waiting time calculated for each order. Alternatively, it may be an average value of the waiting time for each hour and each time of the affiliated store 2 for a certain period of time.

These statistical data can be generated by analyzing order information within a certain period such as a day, a week, a month, etc. It may be displayed on the provided POS terminal, or it may be displayed on the display that the administrator who manages the central control server 4 is looking at.

In addition, when statistical data are generated in this way, the dispatch module 400 generates statistical data generated for a certain period as well as the waiting time based on the number of order information generated at a specific time and time for each affiliated store 2 . By reflecting the number of delivery dispatches of the rider 3 included in the rider DB 100 and the dispatch time for the corresponding delivery can be differentially adjusted.

Here, preferably, the statistical data can be used more directly to control the dispatch time rather than the number of dispatches, or, based on the statistical data, the delivery location, time, and time of the order information written in the order information for each rider (3). Of course, it is also possible to differentially control the number of dispatches by performing multiple dispatches by adjusting the dispatch time based on the number, statistical data, and waiting time.

3 is a conceptual diagram illustrating an example of a graph of the present invention.

Referring to FIG. 3 , the system of the present invention can generate a graph representing time on the x-axis and waiting time on the y-axis. To this end, a graph generating module 800 may be further included, and the graph generating module 800 may include a graph generating unit 810 and a variation determining unit 820 .

The graph generating unit 810 generates a graph in which the x-axis is the time and the y-axis is the waiting time in the previously performed delivery for each affiliated store (2). That is, a specific time point at which the waiting time for each order is taken is graphed as a time section, and the specific time point at which individual order information is generated and the waiting time calculated for each time point are identified.

Basically, this can be displayed on the graph with one coordinate, that is, a dot for each order information, and the time when the order information is generated (the time when the order information is input from the merchant 2), and the corresponding order information Create a graph based on the waiting time. Here, the time refers to a specific time point, and the time period may be referred to as the above-described time range. For example, a time interval of 1 hour, such as 6 pm to 7 pm, may be formed.

Therefore, the distribution of the waiting time for each time section can be checked as a graph (distribution of y values within the x-axis range section), or the waiting time for a specific time can also be checked on the graph (y value for a specific x value). Therefore, when multiple order information is generated at a specific time, multiple y values may appear for a specific x value, and thus a graph including multiple points, that is, coordinates is formed.

The change determiner 820 specifies a time section to which a time point (time) at which a specific order information is generated belongs in a time section displayed on the generated graph, and performs an analysis on the time section, thereby waiting time in the corresponding time section It performs the function of understanding whether the trend is rising or falling.

This is to understand the trend of whether the waiting time is increasing or decreasing in a specific time section, that is, a time section to which specific order information belongs.

To explain with an example in FIG. 3 , a time section including specific order information may be a time section displayed in FIG. 3 . Therefore, it shows the rising and falling trend of the waiting time in the corresponding time section. Through this, if it shows an upward trend of increasing waiting time in a specific time section, it can be understood that the rider (3) should arrive later than the pickup request time to the affiliated store (2) in that time section, and the waiting time is reduced in a specific time section If there is a downward trend, it is possible to know that you should arrive close to the pick-up request time and arrive at the pick-up request time.

Therefore, when the rising and falling trend of the waiting time in a specific time section is identified through the graph generating module 800 as described above, the dispatch module 400 calculates further on the number of order information generated at the specific time and time. The number and dispatch time of the rider 3 can be adjusted by further reflecting the rising and falling trend of the waiting time and the waiting time in the corresponding time section.

Therefore, in addition to reflecting the waiting time as described above, it further reflects the rising trend and the falling trend of the waiting time in the time section including the time when the corresponding order information is generated to further reflect the dispatch time (rider compared to the time of creation of order information). (3) The actual allocation time) can be adjusted more leisurely, or the dispatch time can be adjusted more tightly.

4 is an enlarged graph illustrating only a specific time section.

Referring to FIG. 4 , it can be said that the above graph shows the waiting time for each specific time point and each time section. Here, in the case of waiting time, there may be an acceptable waiting time, that is, a waiting time within an acceptable and predictable range, but there may also be an excessive waiting time that causes a delay in delivery.

Therefore, for each specific time section, the allowable range of the waiting time can be determined and the waiting time within the allowable range and the waiting time outside the corresponding range can be separately identified. It may further include an excess waiting time determining unit 840 and a delay index calculating unit 850 .

The allowable waiting time determining unit 830 grasps the value of the waiting time that is within the reference range in the specific time section range, that is, the coordinate value that falls within the allowable range in the graph as the allowable waiting time information, but is identified as the allowable waiting time information on the graph. It plays a role in determining the number of coordinate values.

Here, the reference range is a value that can be set by a system administrator, and means a predictable and acceptable waiting time for delivery. Here, there is no limitation on the setting method of the reference range or the range of values, and may be set within 3 minutes (0 to 3 minutes), within 5 minutes (0 to 5 minutes), and the like. In the range of FIG. 4, the reference range was set to within 4 minutes (0 to 4 minutes).

Therefore, in displaying the coordinate values displayed on the graph, that is, the waiting time calculated for the order information generated for each specific point in time as the coordinate values, only the coordinate values included within the reference range are identified as the allowable waiting time information, and the allowable waiting time information on the graph To find out the number of coordinate values specified by .

Next, the excess waiting time determining unit 840 is out of the reference range in the corresponding time section, for example, when the reference range is set to within 4 minutes (0 to 4 minutes) as described above, exceeding the reference range The coordinate value indicating the waiting time is identified as the excessive waiting time information, but the number of coordinate values designated as the excessive waiting time information on the graph is determined.

The delay index calculation unit 850 is based on the number of allowable waiting time information identified through the allowable waiting time determining unit 830 and the number of excess waiting time information identified through the excessive waiting time determining unit 840 . to calculate the delay index.

Here, since there is no limitation on the method of calculating the delay index, a value obtained by subtracting the number of allowable waiting time information from the number of excess waiting time information may be calculated as a delay index, or the number of excess waiting time information is allowed A value divided by the number of waiting time information may be calculated as a delay index.

Therefore, the value obtained by comparing and processing the number of excess waiting time information with the number of allowable waiting time information can be the delay index, and it is determined how much the number of excess waiting time information deviated from the number of allowable waiting time information Various formulas that can be applied can be applied to calculate the delay index.

Therefore, when the delay index is calculated in this way, the dispatch module 400 based on the number of order information generated at a specific time and time, the rising and falling trend of the waiting time and waiting time, by further reflecting the delay index here It is possible to differentially adjust the number and dispatch time of the rider 3 .

By reflecting such a delay index, the actual allowable range, that is, how severe the delay is compared to the reference range, is applied to the number of dispatches and dispatch time control, but preferably by using it for dispatch time control, rider (3) It is possible to maintain a faster, slower, or similar speed of delivery according to the creation of order information.

Here, most preferably, the delay index may be calculated through Equation 1 below.

Equation 1.

는 딜레이 지수,

는 초과대기시간정보의 총 개수,

는 허용대기시간정보의 총 개수,

은 그래프 상에 나타난 좌표값의 총 개수를 의미한다.here,

is the delay exponent,

is the total number of excess waiting time information,

is the total number of allowable waiting time information,

is the total number of coordinate values displayed on the graph.

Here, basically, the delay index decreases as the difference between the number of excess waiting time information and the number of allowable waiting time information decreases, and the difference between the number of excess waiting time information and the number of allowable waiting time information decreases as the difference increases. do.

In addition, it is based on the fact that as the number of coordinates shown on the graph, that is, the number of order information increases, the delay index increases. This is reflected because there is a high possibility that it will increase.

Preferably, the total number of excess waiting information time and the total number of allowable waiting time information are based on each being 1 or more. This is because it is basically assumed that there is no case where no time information appears or no allowable waiting time information appears.

Therefore, the delay index calculated here is based on calculation based on when both the excess waiting time information and the allowable waiting time information appear, that is, when the number of both pieces of information is 1 or more.

For example, the total number of coordinate values displayed on the graph, that is, the total number of order information generated in the corresponding time section is 10, the total number of excess waiting time information is 3, and the total number of allowable waiting time information If is 7,

can be calculated as

Such a delay index may basically represent a value exceeding 0, and may increase rapidly as the number of order information increases and the number of excess waiting time information increases.

Therefore, it can be used to adjust the dispatch time based on the delay index calculated in this way. When it is determined that the delay index increases rapidly, that is, the number of excess waiting time information increases rapidly, the dispatch time compared to the order information generation time It is possible to prevent the rider 3 from waiting excessively at the affiliated store 2 by allowing the rider 3 to be allocated more slowly by adjusting the dispatch time for actually performing the .

Furthermore, the above-described statistical analysis module 700 classifies the order information generated for each affiliate store 2 based on at least one of order time, delivery item, order amount, payment method, pickup request time, and waiting time to obtain statistical data. was created and displayed, and further, let the statistical analysis module 700 evaluate the affiliated store 2 where the rider 3 performed the delivery, and analyze the evaluation content of the affiliated store 2 by the rider 3 It is processed so that it can be used for adjusting the number of dispatches and dispatch time for the corresponding affiliate store 2 through the dispatch module 400 based on this. To this end, the statistical analysis module 700 may further include an evaluation sentence input unit 710 and an evaluation value generation unit 720 .

The evaluation sentence input unit 710 performs a function of receiving an evaluation sentence from the rider 3 for the affiliate store 2 that has generated the order information of the food delivery in the delivery performed just before. Here, the evaluation sentence is the opinion of the rider (3) about the affiliated store (2), for example, ‘The food is always cooked later than the pickup request time. As a result, waiting times are always on the long side. In addition, the boss is unkind and tends to be somewhat rude to riders, and his attitude towards riders is not good.' At this time, since there is no limitation on the length of the evaluation sentence, the evaluation sentence can be written in the length of 20 characters to 2000 characters as short as possible.

The evaluation value generation unit 720 analyzes and processes the evaluation sentence for the affiliated store 2 input from the rider 3 to generate the evaluation value for the affiliated store 2 . This is to generate a numerical value of the text subjectively input by the rider 3 to the affiliated store 2 based on the analysis of the affiliated store 2 . There is no limitation on the method of calculating the evaluation value of the affiliated store, but preferably, a latent semantic analysis is performed on the evaluation sentence of the affiliated store, and the dimension of the keyword calculated through the latent semantic analysis can be compressed and the affiliated store evaluation value can be generated based on it. . Alternatively, it is also possible to generate a digitized merchant evaluation value through analysis processing of the evaluation sentence in other ways, and there is no separate limitation on this.

Therefore, when the evaluation value for the affiliated store 2, that is, the affiliate store evaluation value is generated in this way, the dispatch module 400 for a specific time and time, based on the number of generated order information, waiting time, statistical data, and Furthermore, it is possible to differentially adjust the number and dispatch time of delivery to the rider 3 at a specific time and specific time zone by reflecting the merchant evaluation value.

For example, looking at the example in which the franchise evaluation value is reflected, the dispatch time can be advanced or the number of dispatches can be increased for the franchisees (2) with a high franchise evaluation value, that is, a positive response, and the franchisee evaluation value is low; That is, it is possible to adjust the number/time of a kind of reward/punitive dispatch, such as delaying the dispatch time or lowering the number of dispatches for the affiliated store 2 that showed a negative reaction.

Here, in the case of the above-described evaluation value generating unit 720, it is said that the affiliate store evaluation value is preferably calculated from the evaluation sentence through latent semantic analysis. Consists of a matrix generation part 722, a transpose matrix generation part 723, a symmetric matrix generation part 724, a diagonal matrix generation part 725, a singular value calculation part 726, and an evaluation value calculation part 727 characterized by being

The target word extraction part 721 performs a function of extracting an analysis target word including an adjective and a verb from the evaluation sentence input from the rider 3 for the affiliated store 2, preferably, the evaluation sentence in a morpheme unit. , and the analysis target word including adjectives and verbs is extracted from a plurality of segmented morphemes. That is, the evaluation sentence is segmented into spaces to generate nodes, and then the function of extracting terms from each node is performed.

For example, as described above, the evaluation sentence is 'It is always cooked later than the pickup request time. As a result, waiting times are always on the long side. In addition, the boss is unkind and has a tendency to be somewhat hostile to riders, and his attitude towards riders is not good.' /will/therefore/according to/waiting time/always/long/sides/besides/the boss/unfriendly/to the rider/somewhat/disrespectful/tends/is/treats/the rider/attitude/good /Not.' is treated as a segmentation.

If we extract the analysis target word including adjectives and verbs from here, it becomes 'late/become/long/have/unkind/disrespectful/are/bad/not good'.

The frequency matrix generation part 722 is based on the exposure frequency, which is the frequency in which each extracted analysis target word appears in a plurality of evaluation sentences, that is, a plurality of evaluation sentences input by several riders 3 for a specific affiliated store 2 to create a frequency matrix. Here, there is no particular limitation on the method of generating the frequency matrix, but preferably, the frequency matrix can be generated through the following Equation (2).

Equation 2,

는 빈도수행렬,

는

번째 분석대상어(

)가 시스템에 입력된

번째 평가문장(

)에 출현한 노출빈도,

은 생성된 분석대상어의 개수,

은 시스템 상에 입력된 특정 가맹점(2)에 대한 평가문장의 개수를 의미한다.)(here,

is the frequency matrix,

Is

The second analysis target word (

) entered into the system

The second evaluation sentence (

), the frequency of exposure

is the number of generated analysis target words,

denotes the number of evaluation sentences for a specific affiliated store (2) entered into the system.)

The number of analysis target words generated here indicates the number of all analysis target words calculated by analyzing the evaluation sentences for a specific affiliate store (2). That is, it means the total number of analysis target words extracted from the analyzed evaluation sentences by analyzing each evaluation sentence input from a plurality of riders 3 for a specific affiliated store (2).

Therefore, the number of rows of the frequency matrix becomes the number of analysis target words generated as described above, and the number of columns of the frequency matrix becomes the number of evaluation sentences input for a specific affiliate store 2 . That is, when an evaluation sentence is input from the rider 3 every time delivery is completed for a specific affiliated store 2, the number of times delivery is completed through this system for a specific affiliated store 2 is the specific affiliated store (2). Since it is the number of input evaluation sentences, it becomes the number of columns in the frequency matrix.

Here, for example, let's take an example that there are 'slow' and 'unfriendly' as the analysis target words, and suppose that there are a total of two evaluation sentences input for the affiliated store (2). Here, the exposure frequency of the analysis target word 'slow' in the first evaluation sentence is 2 times, the exposure frequency of 'unfriendly' is 3 times, and the exposure frequency of the analysis target word 'slow' in the second evaluation sentence is 1 time, If the exposure frequency of 'unfriendly' is 0,

A frequency matrix can be created in the form of

The transpose matrix generating part 723 serves to transpose the frequency matrix generated in the frequency matrix generating part 722 to generate a transposed matrix. The meaning of transpose here means that rows and columns are exchanged, and when a frequency matrix is created, the transposition matrix can be expressed by inverting the rows and columns to indicate the positions of components belonging to the frequency matrix. Preferably, the transpose matrix can be expressed by the following Equation (3).

Equation 3,

는 전치행렬,

는 전치행렬의

행

열의 값,

은 생성된 분석대상어의 개수,

은 시스템 상에 입력된 특정 가맹점(2)에 대한 평가문장의 개수를 의미한다.)(here,

is the transpose matrix,

is the transpose matrix

line

column value,

is the number of generated analysis target words,

denotes the number of evaluation sentences for a specific affiliated store (2) entered into the system.)

Here, in order to generate the transpose matrix, it is essential that the above-described frequency matrix is generated first, and the transpose matrix is a form in which the components of the frequency matrix are shown inverted in rows and columns.

인 경우,That is, in the above example, the frequency matrix

If ,

의 형태로 산출될 수 있다.transpose matrix

can be calculated in the form of

That is, the rows and columns are the same, that is, the values of row 1, column 2, row 2, column 3, and column 3 are the same, but the remaining values are created in the form of swapping rows and columns.

The symmetric matrix generation part 724 performs a function of generating a symmetric matrix by multiplying the transpose matrix by the frequency matrix. Therefore, in order to generate a symmetric matrix, the aforementioned frequency matrix and transpose matrix must first be created, and preferably, the symmetric matrix can be expressed in the form of Equation 4 below.

Equation 4,

는 대칭행렬,

는 빈도수행렬,

는 전치행렬,

는 대칭행렬의

행

열의 값,

은 생성된 분석대상어의 개수를 의미한다.)(here,

is a symmetric matrix,

is the frequency matrix,

is the transpose matrix,

is the symmetric matrix

line

column value,

means the number of generated analysis target words.)

Here, the frequency matrix is a matrix of q rows and w columns, and the transpose matrix is a matrix of w rows and q columns.

,

라고 가정했을 때,In the above example, the frequency matrix and the transpose matrix are each

,

Assuming that

로 산출된다.

is calculated as

The diagonal components included in the symmetric matrix shown in this way, i.e., the values of row 1, column 2, row 2, and column q and q, indicate how many times the specific analysis target word appeared in the entire evaluation sentence input for the affiliated store (2) (2). exposure frequency), and other values indicate exposure frequencies in which q analysis target words appearing in the matrix appear simultaneously in w evaluation sentences as described above.

The diagonal matrix generation part 725 performs a function of generating a diagonal matrix by performing the diagonalization theorem on the symmetric matrix calculated through the aforementioned symmetric matrix generation part 724 .

Here, for the diagonalization theorem, the transpose matrix is basically multiplied by the frequency matrix, the transpose matrix is multiplied by the frequency matrix, and eigenvalues are calculated from the resulting matrix, and a diagonal matrix is defined as a component.

Such a diagonal matrix can be calculated in the same way as in Equation 5 below.

Equation 5,

는 대각행렬,

는 직교행렬,

는 직교행렬을 전치한 행렬,

는 빈도수행렬,

는 전치행렬,

는 대각행렬의 성분으로서

번째 고유값이다,)(here,

is a diagonal matrix,

is an orthogonal matrix,

is the matrix transposed of the orthogonal matrix,

is the frequency matrix,

is the transpose matrix,

is a component of the diagonal matrix.

is the th eigenvalue,)

Here, an orthogonal matrix refers to an identity matrix in which the magnitude of the vector values of all rows and columns is 1, and is orthogonal to each other, and the same value appears even if the orthogonal matrix is transposed.

In order to obtain the eigenvalues that can be said to be each component of the diagonal matrix, the transposition matrix is multiplied by the frequency matrix as in the above equation, and the eigenvalues of the result matrix expressed by the product of the obtained transposition matrix and the frequency matrix are obtained, and the components of the eigenvalues are calculated. Based on this, a diagonal matrix is calculated. Here, the number of components of the diagonal matrix, ie, the number of eigenvalues, appears as a plurality of eigenvalues. Preferably, as many eigenvalues as the number of evaluation sentences input into the system are calculated.

,

라고 가정했을 때,As an example, the frequency matrix and the transpose matrix are each

,

Assuming that

로 나타나며,

appears as

When calculating the eigenvalues of the calculated matrix,

의 해를 구하면 되므로,

Since we need to find the solution of

That is, if the diagonal matrix is calculated by arranging the calculated eigenvalues in order of size,

will become

The singular value calculation part 726 performs a function of calculating a singular value in the frequency matrix based on the calculated diagonal matrix. Here, preferably, the number of singular values is calculated as much as the number of evaluation sentences for a specific affiliate store 2 input into the system, that is, one singular value for each evaluation sentence is calculated as a numerically representative value.

Such a singular value is preferably calculated through the following Equation (6).

Equation 6,

는 대각행렬의 성분으로서

번째 고유값,

는

번째 특이값의 값을 의미한다.)(here,

is a component of the diagonal matrix.

second eigenvalue,

Is

It means the value of the second singular value.)

인 경우,Therefore, in the above example

If ,

is calculated as

Therefore, through this singular value calculation part 726, a digitized representative value that can represent each evaluation sentence is calculated, which is a standardized, digitized value calculated through analysis of adjectives and verbs for each evaluation sentence. can do.

Finally, the evaluation value calculation part 727 calculates the final evaluation value by obtaining the sum of the calculated singular values. Therefore, by calculating the evaluation value by adding all the singular values calculated according to the number of each evaluation sentence, the evaluation sentence input by the rider 3 for the affiliated store 2 is analyzed to calculate a numerical value, and based on this As a result, a plurality of riders 3 quantify the evaluation result of the affiliated store 2, and based on this, the dispatch module 400 can be reflected in adjusting the dispatch time and number of dispatches.

As described so far, although the configuration and operation of the automatic rider dispatch management system for food delivery according to the present invention are expressed in the above description and drawings, this is only an example and the spirit of the present invention is limited to the description and drawings Of course, various changes and modifications are possible without departing from the technical spirit of the present invention.

1: Orderer 2: Merchant
3: Rider 4: Central control server
100: Rider DB 200: Order input module
300: order counting module 400: dispatch module
500: delivery execution module 600: waiting time identification module
700: statistical analysis module 710: evaluation sentence input unit
720: evaluation value generating unit 721: target word extraction part
722: frequency matrix generation part 723: transpose matrix generation part
724: Symmetric matrix creation part 725: Diagonal matrix creation part
726: singular value calculation part 727: evaluation value calculation part
800: graph generating module 810: graph generating unit
820: fluctuation detection unit 830: allowable waiting time identification unit
840: excess waiting time determination unit 850: delay index calculation unit

Claims (9)

A rider automated dispatch management system for food delivery, comprising:
Rider DB for storing rider information for a plurality of riders performing delivery;
an order input module for receiving order information including a delivery item, a merchant name, a merchant location, a delivery location, and a pickup request time for a delivery item from a merchant;
an order counting module for determining the number of the order information generated during a specific time and time;
a waiting time identification module for determining the waiting time that the rider waits for the pickup of the delivery item for a specific affiliated store in the previously performed delivery;
A graph generating unit that graphs the specific point in time at which the waiting time in the delivery previously performed for each affiliate store is taken as a time section, and a time section to which the time when the order information is generated in the time section is specified for the section A change grasping unit for understanding the rising and falling trend of the waiting time, and the allowable waiting time for identifying the waiting time that is within a reference range in a specific time section as allowable waiting time information, but identifying the number of allowable waiting time information in the graph An identification unit, an excess waiting time identification unit for identifying the waiting time that is out of the reference range in a specific time section as excess waiting time information, but identifying the number of excess waiting time information in the graph; and the number of the allowable waiting time information and a graph generating module including a delay index calculator for calculating a delay index based on the number of the excess waiting time information;
A dispatch module for differentially adjusting the number of dispatches and dispatch times of the riders included in the rider DB by reflecting the rising and falling trends and the delay index of the waiting time at the specific time and time based on the number of order information;
A delivery execution module for transmitting the order information to the rider based on the number of dispatches and the dispatch time. The method of claim 1,
The delay index is
Rider automatic dispatch management system, characterized in that calculated through the following equation (1).
Equation 1.

(here,

is the delay exponent,

is the total number of excess waiting time information,

is the total number of allowable waiting time information,

is the total number of coordinate values displayed on the graph) delete delete delete delete delete delete delete

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