A method for dividing regions of urban logistics instant delivery merchants

Abstract

The invention discloses a method for dividing regions of city logistics instant delivery merchants, comprising the following steps: taking the minimization of the delivery cost of historical orders in a city where a certain logistics platform is located as an objective function, setting node in-degree and out-degree constraints, merchant region constraints, merchant quantity constraints in each region, vehicle quantity constraints, time continuity constraints for vehicles to visit a certain location, time window constraints, and merchant and customer visit sequence constraints, and constructing a merchant region division model, wherein the nodes include a distribution center location, a merchant location, and a customer delivery location; based on the historical order information of the logistics platform, through the merchant region division model, using the existing integer programming model solving software, the division result of the instant delivery merchant region of the platform is obtained; the method generates a merchant region division plan based on the customer historical orders, and forms a plurality of delivery regions by dividing a plurality of merchants into regions, so as to realize the effective management of merchants, vehicles, and riders in the region.

Description

Technical Field

[0001] The invention belongs to the field of Internet technology and relates to a method for dividing regions of urban logistics instant delivery merchants. Background Art

[0002] The rapid development of e-commerce has continuously expanded and extended the scope of online shopping products. In addition to traditional online shopping products such as clothing, shoes, hats, home furnishings, and digital products that can be delivered across cities within multiple days, fast-moving consumer goods such as food and beverage snacks, fresh fruits and vegetables, and supermarkets and department stores that people need immediately after placing an order from merchants in the current city or region have also become the main force of online shopping. This type of urban logistics instant delivery service adopts the model of "online transaction completion and offline instant delivery", which greatly caters to people's urgent needs for fast-paced, high-quality, and convenient life, and provides great convenience for modern life. Therefore, many urban logistics instant delivery platforms such as Meituan and Ele.me have emerged. These platforms gather a large amount of merchant information. Customers can place an order to purchase goods from a certain merchant on the platform, and the platform will then dispatch riders and vehicles to pick up the goods from the merchant and deliver the goods to the customers in a timely manner.

[0003] However, since such logistics platforms need to manage a large number of merchants, in order to facilitate the efficient management of their orders and their delivery resources (riders and vehicles), logistics platforms usually need to divide the entire city into multiple areas, and manage the merchants in each area separately, so as to improve management efficiency. However, how to divide the merchant areas is a relatively complicated issue, and different division methods have completely different delivery costs for vehicles and riders.

[0004] With the rapid development of e-commerce, urban logistics instant delivery plays an increasingly important role in people's lives. Reasonable regional division of merchants will effectively improve delivery efficiency and reduce delivery costs. In the current Chinese invention patent applications, different business district division methods, devices and electronic devices are provided. For example, in some invention patent applications, the area to be divided is pre-divided into multiple sub-areas, the number of orders in each sub-area is adjusted, and the area to be divided is divided into multiple business districts according to the number of orders in each sub-area and the distance between each sub-area and the reverse clustering process. In some invention patent applications, the target area is divided into multiple grids, the flow of people data and the number of merchants in each grid of the multiple grids are obtained, and then the business district in the target area is determined accordingly. In some invention patent applications, multiple merchants in the target area are first determined, and based on the merchant information of multiple merchants, a merchant relationship network of the target area is constructed, and the business districts corresponding to the multiple merchants are determined based on this. The business district boundary of each business district is determined according to the geographic information of the merchants included in each business district.

[0005] In summary, among the regional division patents in the prior art, the inventions mostly consider the division of logistics distribution and geographical networks, and there are relatively few patents on methods for dividing merchant regions; in the methods for dividing and determining business districts, there are relatively few that use mathematical models to solve merchant regional divisions, and there are relatively few patents that consider the characteristics and rules of historical orders. There is still much room for improvement in the existing merchant regional division methods. Summary of the invention

[0006] In order to solve the above problems, the technical solution adopted by the present invention is: a method for dividing the regions of urban logistics instant delivery merchants, comprising the following steps:

[0007] Taking the minimization of the delivery cost of historical orders in a city where a logistics platform is located as the objective function, setting the node in-degree and out-degree constraints, the merchant region constraints, the number of merchants in each region constraints, the number of vehicles constraints, the time continuity constraints of vehicles visiting a certain location, the time window constraints, and the visit order constraints of merchants and customers, a merchant region division model is constructed. The nodes include: distribution center locations, merchant locations, and customer delivery locations;

[0008] Based on the historical order information of the logistics platform, the merchant area division model is adopted and the existing integer programming model solving software is used to obtain the division results of the platform's instant delivery merchant areas.

[0009] Furthermore: the historical order information includes the time when the order was placed, the location of the merchant from which the goods required for the order came, and the delivery location and time period required by the customer.

[0010] Further: The objective function expression is as follows

[0011]

[0012] in: i, j are distribution centers, route merchants, or customers, d is a delivery day, z is a region, Indicates whether points i and j are visited consecutively by vehicles in this area on this delivery day;

[0013] c ij : represents the delivery cost between points i and j.

[0014] Further: the merchant area division model is as follows:

[0015]

[0016]

[0017]

[0018]

[0019]

[0020]

[0021]

[0022]

[0023] Among them: Constraints (2) to (4) represent y rz Related restrictions, y rz Indicates whether the source merchant r is assigned to the delivery area z;

[0024] Constraint (2) is the node out-degree and in-degree constraint, which means that if a vehicle leaves a point i in region z on a certain day, that is, the out-degree is 1, or enters, that is, the in-degree is 1, then the source merchant of the point must be in region z, otherwise the source merchant of the point is not in region z;

[0025] Constraint (3) is the region constraint of the source merchant, which means that each source merchant must belong to a region;

[0026] Constraint (4) is the quantity constraint of merchants in each region, which gives the quantity range of source merchants contained in each region;

[0027] Constraints (5) to (9) indicate Related restrictions;

[0028] Among them, constraint (5) is the vehicle quantity constraint, which means that the sum of the number of vehicles used in all regions every day cannot exceed the upper limit, that is, the upper limit of the out-degree and in-degree of point o. It is assumed that each vehicle can only be used in one region and cannot be used across regions.

[0029] Constraint (6) is the time continuity constraint of the vehicle visiting the points. This constraint ensures that the time sequence of the vehicle visiting the nodes is continuous. That is, if the vehicle visits point i first and then visits point j, then the time the vehicle visits point j should not be less than the sum of the time the vehicle visits point i and the travel time between points i and j.

[0030] Constraint (7) indicates that the access time of the distribution center is 0;

[0031] Constraint (8) is a time window constraint, which means that the time when the vehicle arrives at customer i to deliver the goods must be within the delivery time range required by customer i;

[0032] Constraint (9) is the point visit order constraint, which means that the customer point must be visited after the merchant point on its route, that is, the vehicle must first pick up the goods from the merchant before delivering the goods to the customer;

[0033] Where: R: the set of all source merchants, subscripted as r, r∈R;

[0034] D: the set of all delivery days, subscripted as d, d∈D;

[0035] Z: the set of all regions, subscripted as z, z∈Z;

[0036] K: the set of all vehicles;

[0037] C d : the set of all customers on day d;

[0038] R d : The collection of all route merchants on day d;

[0039] N d : The set of all points on day d, including distribution center o, customer point C d , and route merchant point R d ;

[0040] r i :i is a route merchant or customer, i∈∪ d∈D (R d ∪C d ), r i Indicates the source merchant to which i belongs;

[0041] The travel time between points i and j;

[0042] o: indicates distribution center;

[0043] [e i ,l i ]:i is a customer, i∈∪ d∈D C d ,[e i ,l i ] represents the time window of customer i;

[0044] [L,U]: indicates the lower and upper bounds of the number of merchants in each region;

[0045] y rz :r is the source merchant, z is a delivery area, variable y rz Indicates whether the source merchant r is assigned to area z;

[0046] i is the route merchant or customer on day d, i∈∪ d∈D (R d ∪C d ),variable is the visit time of point i; when i is the distribution center o,

[0047] Furthermore: the merchant area division model is used to obtain the division result of the platform's instant delivery merchant area through the existing integer programming model solving software.

[0048] Furthermore: the existing integer linear programming model solving software includes Gurobi, Cplex or Lingo.

[0049] The present invention provides a method for dividing a region for urban logistics instant delivery merchants. A merchant region division plan is generated based on customer historical orders. Multiple merchants are divided into regions to form multiple delivery regions, so as to achieve effective management of merchants, vehicles, and riders in the region. Merchants to which delivery orders with similar spatiotemporal characteristics belong are divided into one region, which is beneficial to improving order execution efficiency and reducing delivery costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0051] Figure 1 is a flow chart of the method;

[0052] Figure 2 It is a location distribution map of merchants and customers;

[0053] Figure 3 is a result graph of the delivery route plan of the embodiment;

[0054] Figure 4 This is the area division result map. DETAILED DESCRIPTION

[0055] In order to make the technical solutions and advantages of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention:

[0056] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0057] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0059] Unless otherwise specifically stated, the relative arrangement, numerical expressions and numerical values ​​of the parts and steps described in these embodiments do not limit the scope of the present invention. At the same time, it should be clear that, for ease of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship. The technology, methods and equipment known to ordinary technicians in the relevant field may not be discussed in detail, but in appropriate cases, the technology, methods and equipment should be regarded as a part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as being merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once a certain item is defined in an accompanying drawing, it does not need to be further discussed in subsequent drawings.

[0060] In the description of the present invention, it is necessary to understand that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "lateral, vertical, perpendicular, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the drawings. They are only for the convenience of describing the present invention and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific direction or be constructed and operated in a specific direction. Therefore, they cannot be understood as limiting the scope of protection of the present invention: the directional words "inside and outside" refer to the inside and outside relative to the contours of each component itself.

[0061] For ease of description, spatially relative terms such as "above", "above", "on the upper surface of", "above", etc. may be used here to describe the spatial positional relationship between a device or feature and other devices or features as shown in the figure. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figure. For example, if the device in the accompanying drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below their position devices or structures". Thus, the exemplary term "above" can include both "above" and "below". The device can also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatially relative descriptions used here are interpreted accordingly.

[0062] In addition, it should be noted that the use of terms such as "first" and "second" to limit components is only for the convenience of distinguishing the corresponding components. If not otherwise stated, the above terms have no special meaning and therefore cannot be understood as limiting the scope of protection of the present invention.

[0063] A method for dividing regions of city logistics instant delivery merchants comprises the following steps:

[0064] S1: Taking the minimization of the delivery cost of historical orders in a city where a logistics platform is located as the objective function, setting the node in-degree and out-degree constraints, the merchant region constraints, the number of merchants in each region constraints, the number of vehicles constraints, the time continuity constraints of vehicles visiting a certain location, the time window constraints, and the visit order constraints of merchants and customers, and constructing a merchant region division model. The nodes include: distribution center locations, merchant locations, and customer delivery locations;

[0065] S2: Based on the historical order information of the logistics platform, through the merchant area division model, the existing integer programming model solving software is used to obtain the division results of the platform's instant delivery merchant areas.

[0066] Steps S1 and S2 are performed sequentially;

[0067] Furthermore, the historical order information includes the time when the order was placed, the location of the merchant from which the goods required for the order came, and the delivery location and time period required by the customer.

[0068] The objective function expression is as follows

[0069]

[0070] in: i, j can be a distribution center (i.e., the starting and ending points of the delivery vehicle), a route merchant (see below for explanation), or a customer, d is a delivery day, z is a region, Indicates whether points i and j are visited before and after in this delivery day and in this area.

[0071] This patent has two concepts: "source merchant" and "route merchant". Each merchant has only one "source merchant", that is, the merchant itself. Each merchant can have multiple "route merchants", which are copied into multiple merchants according to the number of customers. Each "route merchant" corresponds to a customer's pickup store, and each "route merchant" can only be visited once.

[0072] c ij : represents the delivery cost between points i and j.

[0073] Further: the merchant area division model is as follows:

[0074]

[0075]

[0076]

[0077]

[0078]

[0079]

[0080]

[0081]

[0082] Among them: Constraints (2) to (4) represent y rz Related restrictions, y rz Indicates whether the source merchant r is assigned to the distribution area z. Constraint (2) is the node out-degree and in-degree constraint, which means that if a vehicle leaves (i.e., the out-degree is 1) or enters (i.e., the in-degree is 1) a certain point i (i is a route merchant or a customer point) in area z on a certain day, then the source merchant of this point must be in area z, otherwise the source merchant of this point is not in area z. Among them, out-degree and in-degree are concepts in a directed graph, out-degree represents the number of outgoing edges of a certain point, and in-degree represents the number of incoming edges of a certain point. Here, out-degree is equal to in-degree, that is, for a certain point, the number of edges entering the point (the number of times vehicles enter) must be equal to the number of edges leaving the point (the number of times vehicles exit). In addition, if there is an out-degree, it must be 1, and similarly, if there is an in-degree, it must also be 1, because i here is a route merchant or a customer point. If a route merchant or a customer point is visited, it can only be visited once;

[0083] Constraint (3) is the region constraint of the source merchant, which means that each source merchant must belong to a region;

[0084] Constraint (4) is the quantity constraint of merchants in each region, which gives the quantity range of source merchants contained in each region;

[0085] Constraints (5) to (9) indicate Related restrictions;

[0086] Among them, constraint (5) is the vehicle quantity constraint, which means that the sum of the number of vehicles used in all regions every day cannot exceed the upper limit, that is, the upper limit of the out-degree and in-degree of point o (distribution center point). It is assumed that each vehicle can only be used in one region and cannot be used across regions.

[0087] Constraint (6) is the time continuity constraint of the vehicle visiting the points. This constraint ensures that the time sequence of the vehicle visiting the nodes is continuous. That is, if the vehicle visits point i first and then visits point j, then the time the vehicle visits point j should not be less than the sum of the time the vehicle visits point i and the travel time between points i and j.

[0088] Constraint (7) indicates that the access time of the distribution center is 0;

[0089] Constraint (8) is a time window constraint, which means that the time when the vehicle arrives at customer i to deliver the goods must be within the delivery time range required by customer i. The time window constraint is to meet the delivery time range required by the customer when placing an order. For example, if customer i's time window is [10:00,10:30], the vehicle should deliver the goods to the customer within the time range of 10:00-10:30.

[0090] Constraint (9) is the point visit order constraint, which means that the customer point must be visited after the merchant point on its route, that is, the vehicle must first pick up the goods from the merchant before delivering the goods to the customer;

[0091] The above model uses the following symbols, which represent the following meanings:

[0092] R: the set of all source merchants, subscripted as r, r∈R;

[0093] D: the set of all delivery days, subscripted as d, d∈D;

[0094] Z: the set of all regions, subscripted as z, z∈Z;

[0095] K: the set of all vehicles;

[0096] C d : the set of all customers on day d;

[0097] Rd : The collection of all route merchants on day d;

[0098] N d : The set of all points on day d, including distribution center o, customer point C d , and route merchant point R d ;

[0099] r i :i is a route merchant or customer, i∈∪ d∈D (R d ∪C d ), r i Indicates the source merchant to which i belongs;

[0100] The travel time between points i and j;

[0101] o: indicates distribution center;

[0102] [e i ,l i ]:i is a customer, i∈∪ d∈D C d ,[e i ,l i ] represents the time window of customer i;

[0103] [L,U]: indicates the lower and upper bounds of the number of merchants in each region;

[0104] y rz :r is the source merchant, z is a delivery area, variable y rz Indicates whether the source merchant r is assigned to area z;

[0105] i is the route merchant or customer on day d, i∈∪ d∈D , (R d ∪C d ),variable is the visit time of point i; when i is the distribution center o,

[0106] Furthermore: the merchant area division model is used to obtain the division result of the platform's instant delivery merchant area through the existing integer programming model solving software.

[0107] Further: the existing integer linear programming model solving software includes Gurob, Cplex or Lingo, etc.;

[0108] Embodiment 1,

[0109] Step 1: Obtain historical order data, including the order time, the location of the merchant who placed the order, the delivery location requested by the customer, and the delivery time window, i.e., the time period range [e i ,l i ] Duplicate each merchant into multiple copies corresponding to each customer. Each copy is called a "route merchant". Record the customer corresponding to each "route merchant" and the "source merchant" to which it belongs.

[0110] Step 2: Based on historical order data, obtain the travel time t between any two points (i, j) ij , delivery cost ij , set the upper and lower bounds [L,U] of the number of merchants in each area and the vehicle set K;

[0111] Step 3: Set the travel time t between two points (i, j) ij , the source merchant r to which route merchant i belongs i , customer j's delivery time window [e j ,l j ], the upper and lower bounds of the number of merchants [L, U] and other parameters are input into the merchant area division model;

[0112] Step 4: Run the merchant area division model with the help of Gurobi, an integer linear programming model solving software, to obtain the merchant area division plan;

[0113] For example, suppose there are 4 merchants A, B, C, and D, and 8 orders 1, 2, 3, 4, 5, 6, 7, and 8 on a certain day. Now, these 4 merchants are divided into 2 areas. It is known that merchant A’s orders are 1 and 2, merchant B’s orders are 3, merchant C’s orders are 4, 5, and 6, and merchant D’s orders are 7 and 8. Let r1=r2=A, r3=B, r4=r5=r6=C, r7=r8=D. The delivery time windows of each order are as follows. The two numbers in the brackets represent the start and end times of the delivery time period requested by the customer: [0,4], [1,6], [3,7], [2,5], [2,7], [3,9], [0,6], [1,9]; the location distribution of merchants and customers is as follows: Figure 2 .

[0114] Calculate the travel time t between each point from the order data ij and delivery costs ij , assuming that the number of merchants in each area has an upper bound of L = 1, a lower bound of U = 3, and a number of vehicles K = 4. Substitute the above data into the mathematical model and use the Gurobi solver to solve the merchant area division model. The value of the delivery route plan for that day is as follows Figure 3 shown.

[0115] The merchant area division model will eventually obtain the variable {y rz}, and obtain the following merchant partitioning scheme; 4 merchants are divided into 2 areas, area 1 includes merchants A and B, area 2 includes merchants C and D, and the regional division results are as follows Figure 4 shown.

[0116] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for dividing regions of urban logistics instant delivery merchants, characterized by: The following steps are involved: Taking the minimization of the delivery cost of historical orders in a city where a logistics platform is located as the objective function, setting the node in-degree and out-degree constraints, the merchant region constraints, the number of merchants in each region constraints, the number of vehicles constraints, the time continuity constraints of vehicles visiting a certain location, the time window constraints, and the visit order constraints of merchants and customers, a merchant region division model is constructed. The nodes include: distribution center locations, merchant locations, and customer delivery locations; Based on the historical order information of the logistics platform, the merchant area division model is used to obtain the division results of the platform's instant delivery merchant area using the existing integer programming model solving software; The objective function expression is as follows in: i, j are distribution centers, route merchants, or customers, d is a delivery day, z is a region, Indicates whether points i and j are visited consecutively by vehicles in this area on this delivery day; c ij : represents the delivery cost between points i and j; The merchant area division model is as follows: Among them: Constraints (2) to (4) represent y rz Related restrictions, y rz Indicates whether the source merchant r is assigned to the delivery area z; Constraint (2) is the node out-degree and in-degree constraint, which means that if a vehicle leaves a route merchant or customer point in area z on a certain day, or if a vehicle enters a route merchant or customer point in area z on a certain day, then the source merchant of the point must be in area z, otherwise the source merchant of the point is not in area z; Constraint (3) is the region constraint of the source merchant, which means that each source merchant must belong to a region; Constraint (4) is the quantity constraint of merchants in each region, which gives the quantity range of source merchants contained in each region; Constraints (5) to (9) indicate Related restrictions; Among them, constraint (5) is the vehicle quantity constraint, which means that the sum of the number of vehicles used in all regions every day cannot exceed the upper limit, that is, the upper limit of the out-degree and in-degree of point o. It is assumed that each vehicle can only be used in one region and cannot be used across regions. Constraint (6) is the time continuity constraint of the vehicle visiting the points. This constraint ensures that the time sequence of the vehicle visiting the nodes is continuous. That is, if the vehicle visits point i first and then visits point j, then the time the vehicle visits point j should not be less than the sum of the time the vehicle visits point i and the travel time between points i and j. Constraint (7) indicates that the access time of the distribution center is 0; Constraint (8) is a time window constraint, which means that the time when the vehicle arrives at customer i to deliver the goods must be within the delivery time range required by customer i; Constraint (9) is the point visit order constraint, which means that the customer point must be visited after the merchant point on its route, that is, the vehicle must first pick up the goods from the merchant before delivering the goods to the customer; Where: R: the set of all source merchants, subscripted as r, r∈R; D: the set of all delivery days, subscripted as d, d∈D; Z: the set of all regions, subscripted as z, z∈Z; K: the set of all vehicles; C d : The set of all customers on day d; R d : The collection of all route merchants on day d; N d : The set of all points on day d, including distribution center o, customer point C d , and route merchant point R d ; r i :i is a route merchant or customer, i∈∪ d∈D (R d ∪C d ), r i Indicates the source merchant to which i belongs; The travel time between points i and j; o: indicates distribution center; [e i ,l i ]:i is a customer, i∈∪ d∈D C d ,[e i ,l i ] represents the time window of customer i; [L,U]: indicates the lower and upper bounds of the number of merchants in each region; y rz :r is the source merchant, z is a delivery area, variable y rz Indicates whether the source merchant r is assigned to area z; i is the route merchant or customer on day d, i∈∪ d∈D (R d ∪C d ),variable is the visit time of point i; i can also be the distribution center o, in which case, 2. A method for dividing regions of city logistics instant delivery merchants according to claim 1, characterized in that: The historical order information includes the time when the order was placed, the location of the merchant from which the goods required for the order came, and the delivery location and time period required by the customer.

3. The method for dividing regions of city logistics instant delivery merchants according to claim 1, characterized in that: The merchant area division model is used to obtain the division result of the platform's instant delivery merchant area through the existing integer programming model solving software.

4. The method for dividing regions of city logistics instant delivery merchants according to claim 1, characterized in that: The existing integer linear programming model solving software includes Gurobi, Cplex or Lingo.

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