CN110598910B - Automatic delivery system for e-commerce logistics distribution goods - Google Patents

Abstract

The invention discloses an automatic delivery system for logistics delivered goods of electronic commerce, which comprises a server, an automatic delivery device and a user terminal, wherein the server comprises a central processor I and an algorithm module which are connected through signals, and the algorithm module adopts an improved ant colony algorithm to plan a trolley operation route; the automatic warehouse-out device comprises a central processor II, and a gravity sensing module, a scanning module, an execution module, an instruction module, a fault diagnosis module and a wireless transmission module II which are connected with the central processor II in a signal manner; the user terminal comprises an output module, a wireless transmission module III and a mobile phone or a computer; the automatic warehouse-out device comprises a transportation pipeline, a self-adaptive movable trolley, a trolley pause area and an empty trolley return pipeline. When the commodity warehouse-out system is used for commodity warehouse-out, the working of sorting, scanning, spot inspection and the like are not needed, so that the warehouse-out efficiency is greatly improved, the error rate is reduced, and the labor cost is reduced.

Description

An automated outbound delivery system for e-commerce logistics distribution

Technical Field

The present invention relates to the field of e-commerce warehousing logistics and distribution, and more specifically, to an automated outbound delivery system for e-commerce logistics and distribution goods.

Background Art

With the rapid development of e-commerce, online shopping has become a common way of shopping in people's lives. More and more e-commerce platforms (such as Suning.com, JD.com, Dangdang.com, etc.) have turned their attention to the construction of logistics platforms and invested a lot of money to build self-operated warehousing and distribution centers.

At present, some e-commerce warehouses have achieved partial automation, such as automated three-dimensional warehouse equipment, which has achieved rational utilization of high-rise warehouse space, automated storage and retrieval, and simplified operation. However, some links still need to be operated manually, such as the delivery of some goods, which requires manual sorting of packaged and coded goods according to the final destination of the goods to be delivered, and manual scanning of the goods to be loaded and uploading of the delivery information. With the rapid growth of express logistics, people will become the biggest factor restricting warehouses from improving distribution efficiency.

The part of the automated sorting equipment that has been put into use is shown in Figure 1. A is a slider that changes the direction of the goods, B is the main conveyor belt, C is the goods, and D is the branch roller conveyor belt. A barcode scanner is installed at the entrance of the main conveyor belt B to scan the delivery information of the goods C passing by and determine whether the delivery direction of the goods needs to be changed. If it needs to be changed, the slider A is controlled to change the goods to the branch roller conveyor belt D. The goods of this automated sorting equipment are sorted on the main conveyor belt. This automatic sorting equipment saves manpower and is highly efficient. However, once a section of the main conveyor belt has a mechanical failure and stops running, especially when the amount of goods to be delivered is large, it will cause the goods to pile up and reduce the delivery efficiency.

Summary of the invention

In view of the deficiencies in the prior art or the need for improvement, the present invention provides an automated outbound delivery system for e-commerce logistics distribution, comprising a server and an automated outbound delivery device through signal transmission, the server comprising a central processing unit I and an algorithm module connected by signals, the automated outbound delivery device comprising a transport pipeline, and if a trolley equipped with a fault diagnosis module fails while running in the transport pipeline, the central processing unit I determines whether other trolleys have passed through the area where the faulty trolley is located, and if so, the algorithm module re-plans the optimal path for the trolley.

In the above technical scheme, the transport pipeline includes an inverted T-shaped pipeline A connected to one end of the inlet pipeline port and several pipelines parallel to the ground connected to the bottom end of the inverted T-shaped pipeline A. The pipelines parallel to the ground are all connected to one end of the unloading pipeline port, and the other end of the unloading pipeline port is connected to one end of the L-shaped pipeline of the empty vehicle return pipeline. The other end of the L-shaped pipeline is connected to the bottom end of the inverted T-shaped pipeline B, and the top end of the inverted T-shaped pipeline B is connected to the other end of the inlet pipeline port; a trolley temporary storage area is provided in the vertical pipeline of the inverted T-shaped pipeline B.

In the above technical solution, the unloading pipe opening is provided with a transverse guide rail, a hydraulic push-pull device and a vertical guide rail. The transverse guide rail includes a hollow guide rail and a movable guide rail. The hollow guide rail is fixed in the horizontal transport pipe and one end of the hydraulic push-pull device is installed. The other end of the hydraulic push-pull device is welded to the movable guide rail. The vertical guide rail is installed in the vertical transport pipe.

In the above technical solution, the trolley includes rollers, vertically movable rollers, a horizontally movable mechanism and a body. The roller part is installed in the body, the vertically movable rollers are fixed on the four corners of the body, and the horizontally movable mechanism is embedded in the bottom of the body.

In the above technical solution, the specific process of the algorithm module planning a new optimal path for the car is:

S1: Initialize pipeline environment and algorithm parameters;

S2: The algorithm module receives the car route planning task, and the car receives the path information from the execution module;

S3: Construct a solution for the transportation route of a small vehicle

从可行点集S＝{j∈V|{1,n}∪O}中选取一个节点，O为当前未走过路径T包含的点集，考虑在路径(i,j)的小车排队状况及路径长度，在状态转移概率中加入权重系数w_ij：For each ant starting from node 1, when searching for the k+1th node, according to the probability

Select a node from the feasible point set S = {j∈V|{1,n}∪O}, where O is the point set included in the current untraversed path T. Consider the queue status and path length of the vehicles on the path (i,j), and add the weight coefficient w _ij to the state transition probability:

Where: V = {1, 2, ..., n} is the set of nodes in each transport pipeline (3) in the environment, d _avg is the path average from node i to all next adjacent nodes, t _ij is the time required for a car to pass through path (i, j), Δt represents the time required for a car to wait for another car that needs to pass through path (i, j) to pass through node i when queuing, θ represents the number of cars currently in the queue, τ _ij represents the pheromone intensity of path (i, j), η _ij represents the heuristic factor of path (i, j), α represents the importance coefficient of pheromones accumulated by ants during movement, β represents the importance coefficient of the heuristic factor, and (i, n) represents all possible nodes;

不断迭代选择下一个节点和路径，直至小车到达终点为止，若无法到达终点，则从起始点开始重新进行此过程；By state transition probability

The next node and path are selected iteratively until the car reaches the end point. If the car cannot reach the end point, the process is repeated from the starting point.

S4: Evaluate the current route solution and record the optimal solution;

S5: Update pheromone;

S6: Operation termination judgment

Determine whether the current number of iterations D has reached the preset number of iterations M. If not, return to S4 and replace D with (D+1); if it has, stop the operation, reset the pheromone and transfer probability, output the optimal route as the car's running route, and return to S1.

The beneficial effects achieved by the present invention are:

The present invention provides an automated outbound delivery system for e-commerce logistics distribution goods, which realizes automatic sorting and outbound delivery of logistics distribution goods through the automatic outbound delivery system. The algorithm module in the outbound delivery system adopts an improved ant colony algorithm to plan transportation routes for carts transporting goods, thereby realizing rapid sorting, transportation and entry of outbound delivery information for warehouse order goods, thereby eliminating the links of manual sorting, manual transportation and manual entry of outbound delivery information, greatly saving manpower and improving logistics distribution efficiency; at the same time, when a failure occurs in the system operation, the system intelligently switches to an alternative plan to ensure the normal operation of the outbound delivery process.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings are used to promote further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

FIG1 is a schematic diagram of a partial equipment of a sorting device currently in use;

FIG2 is a schematic diagram of an automatic outbound storage system of the present invention;

FIG3 is a structural diagram of the automated warehouse-out device of the present invention;

FIG4 is a structural diagram of a turning portion of the automated outbound device of the present invention;

5 is a southeast isometric view of the adaptive mobile trolley used in the automated outbound storage device of the present invention;

6 is a bottom view of the adaptive mobile vehicle used in the automated outbound device of the present invention;

FIG. 7 is an algorithm flow chart of the algorithm module of the present invention.

In the accompanying drawings, 1-conveyor belt, 2-pipeline opening, 3-transportation pipeline, 4-unloading pipeline opening, 5-trolley temporary storage area, 6-empty vehicle return pipeline, 7-auxiliary circle, 41-hydraulic push-pull device, 42-adaptive mobile trolley, 43-lateral guide rail, 44-vertical track, 421-roller, 422-vertical moving roller, 423-horizontal moving mechanism, 424-carriage, 100-server, 101-identification module, 102-central processing unit I, 103-algorithm module, 104-wireless transmission module I, 200-automatic warehouse delivery device, 201-central processing unit II, 202-scanning module, 203-gravity sensing module, 204-execution module, 205-command module, 206-wireless transmission module II, 207-fault diagnosis module, 300-user terminal, 301-output module, 302-wireless transmission module III, 303-mobile phone or computer terminal.

DETAILED DESCRIPTION

The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. The preferred embodiments described herein are only used to illustrate and explain the present invention. Those skilled in the art may conceive of other obvious variations, and the present invention is not limited thereto.

As shown in Figure 2, an automatic outbound delivery system for e-commerce logistics distribution of the present invention includes a server 100, an automated outbound delivery device 200 and a user terminal 300. The server 100 includes a central processing unit I 102 and an identification module 101, an algorithm module 103, and a wireless transmission module I 104 connected to the central processing unit I 102 by signal; the automated outbound delivery device 200 is provided with a central processing unit II 201 and a gravity sensing module 203, a scanning module 202, an execution module 204, an instruction module 205, a wireless transmission module II 206, and a fault diagnosis module 207 connected to the central processing unit II 201 by signal, and the gravity sensing module 203 and the fault diagnosis module 207 are both arranged on a trolley for transporting goods; the user terminal 300 includes an output module 301, a wireless transmission module III 302, and a mobile phone or computer terminal 303.

The scanning module 202 is arranged on the conveyor belt through which the goods pass, scans the information of the goods when passing through the pipe port of the automatic outbound storage device 200, and sends it to the central processor II 201. The central processor II 201 sends an adaptive mobile car to pick up the goods through the instruction module 205, and at the same time sends the goods information to the central processor I 102 through the wireless transmission module II 206 and the wireless transmission module I 104. The central processor I 102 identifies the goods information through the identification module 101, and then transmits it to the algorithm module 103 through the central processor I 102. The algorithm module 103 quickly calculates the future moving path of the current running car through the goods information, and transmits the result to the central processor II 201 through the wireless transmission module. The central processor II 201 controls the car to transport the goods through the execution module 204 After the goods are unloaded at the destination, the gravity sensing module 203 on the trolley transmits the unloading signal to the mobile phone or computer terminal 303 through the central processor II 201, the wireless transmission module II 206, the wireless transmission module III 302, and the output module 301, and the trolley returns to the temporary storage area along the set path according to the control of the execution module 204; during the operation of the trolley, the fault diagnosis module 207 monitors the operation status of the trolley in real time. Once the trolley fails, the fault diagnosis module 207 issues a fault prompt and uploads the fault information to the central processor I 102. The central processor I 102 determines whether the current starting trolley will pass through the faulty trolley area. If it passes, the algorithm module 103 updates the ant colony algorithm initialization environment, lists the node where the faulty trolley is located as an infeasible node, and re-plans the optimal path for the starting trolley.

Both the CPU I 102 and the CPU II 201 are AMD Ryzen 7 1800X processors, which are ultra-large-scale integrated circuits and are the computing core (Core) and control core of a computer. The gravity sensing module 203 is provided with a gravity sensor, which uses elastic sensitive elements to make a cantilevered displacement device, and uses an energy storage spring made of elastic sensitive elements to drive the electrical contacts to complete the conversion from gravity changes to electrical signals. The wireless transmission module I 104, the wireless transmission module II 206 and the wireless transmission module III 302 are all a communication method that uses the characteristics of electromagnetic wave signals that can propagate in free space to exchange information. The scanning module 202 uses a scanner.

As shown in Figures 3 to 6, the automated outbound device 200 includes a conveyor belt 1, an inbound pipe port 2, a transport pipe 3, an unloading pipe port 4, a trolley temporary storage area 5 and an empty car return pipe 6. The conveyor belt 1 is aligned and fixed with the inbound pipe port 2. The conveyor belt 1 is used to transport goods that need to be outbound. The transport pipe 3 includes an inverted T-shaped pipe A connected to one end of the inbound pipe port 2 and a plurality of pipes parallel to the ground connected to the bottom end of the inverted T-shaped pipe A. The pipes parallel to the ground are all connected to one end of the unloading pipe port 4; the other end of the unloading pipe port 4 is connected to one end of the L-shaped pipe of the empty car return pipe 6, the other end of the L-shaped pipe is connected to the bottom end of the inverted T-shaped pipe B, and the top of the inverted T-shaped pipe B is connected to the other end of the inbound pipe port 2; a trolley temporary storage area 5 is provided in the vertical pipe of the inverted T-shaped pipe B.

The structure of the unloading pipe port 4 is shown in Figure 4, including a transverse guide rail 43, a hydraulic push-pull device 41, and a vertical guide rail 44. The transverse guide rail 43 is divided into two sections. One section is a hollow guide rail installed in the horizontal transport pipe 3. One end of the hydraulic push-pull device 41 is installed inside the hollow guide rail. The other section is a movable guide rail, which is welded to the other end of the hydraulic push-pull device 41 and can be moved horizontally. When the hydraulic push-pull device 41 is not running, the two sections of the guide rail are in a joined state. When the hydraulic push-pull device 41 is started, the movable guide rail extends and retracts with the hydraulic push-pull device 41. The hydraulic push-pull device 41 is controlled by the central processor II 201 through the execution module 204; the vertical guide rail 44 is installed on the vertical transport pipe 3. When the trolley 42 needs to adjust its direction, the CPU II 201 stops the trolley motor through the execution module 204, and starts the hydraulic pusher 41 inside the transverse guide rail 43, pushing the trolley 42 to a set fixed distance, and engaging with the vertical track 44. The hydraulic pusher 41 retracts the extended movable guide rail. After the movable guide rail returns to its original position, the CPU II 201 restarts the trolley motor through the execution module 204 to enter the vertical transport pipe 3. The trolley temporary storage area 5 is a vertical pipe for storing a certain number of trolleys. A telescopic baffle that can hold the stopped trolley 42 is installed inside the pipe according to the parking space of the trolley. The extension and retraction of the baffle is controlled by the CPU II 201 through the execution module 204.

As shown in FIG5 , the adaptive mobile trolley 42 includes a roller 421, a vertical moving roller 422, a horizontal moving mechanism 423 and a square body 424. The body 424 is provided with a motor, a roller driving device and a reducer for driving the trolley. A part of the roller 421 is installed in the body 424, and the vertical moving roller 422 is fixed on the four corners of the body 424. The roller 421 and the vertical moving roller 422 are driven by the roller driving device, and the driving roller 421 can realize unloading; the horizontal moving mechanism 423 drives the trolley to move horizontally, and the part where the horizontal moving mechanism 423 and the body 424 are embedded is provided with a rotating bearing, which is used to rotate the horizontal moving mechanism 423 when the trolley moves in the up and down directions (rotates 90 degrees only when the next horizontal moving pipe of the trolley is perpendicular to the previous horizontal moving pipe); the roller driving device and the horizontal moving mechanism 423 are controlled by the central processor II 201 through the execution module 204.

FIG6 is a bottom view of the adaptive moving trolley of the present embodiment of the invention. Circle 7 is an auxiliary circle used to limit the size of the horizontal moving mechanism 423 of the trolley 42 so as not to exceed the rotatable range when changing the angle.

The algorithm module 103 uses an improved ant colony algorithm to plan the vehicle's running route, as shown in FIG7 , including the following steps:

S1: Initialize environment and algorithm parameters

Initialize the environment: Give the point set (including the cargo tray interface, pipeline turning point and exit) and edge set of the three nodes of the transportation pipeline. Specifically, define G = (V, E) as the environment graph of the automated outbound device 200, where V = {1, 2, ..., n} is the set of three nodes of each transportation pipeline in the environment, i.e., the point set; E = {(i, j) | i, j∈V, i≠j} is the set of feasible routes between each positioning point, i.e., the edge set; the distance between any two nodes i and j is d _ij ;

Initialize algorithm parameters: define the number of ants as N, the maximum number of iterations as M, the current number of iterations as D, initialize the pheromone volatility coefficient ρ∈[0,1], and update the pheromone in subsequent steps; the optimization goal is to find a path starting from node 1 and ending at node n so that the obtained path is the shortest.

S2: The algorithm module 103 receives the car route planning task, and the car receives the route information from the execution module 204.

S3: Construct a solution for the transportation route of a small vehicle

从可行点集S＝{j∈V|{1,n}∪O}中选取一个节点，O为当前未走过路径T包含的点集，考虑在路径(i,j)的小车排队状况及路径长度，在状态转移概率中加入权重系数w_ij，加快算法收敛速度，如下：For each ant starting from node 1, when searching for the k+1th node, according to the probability

Select a node from the feasible point set S = {j∈V|{1,n}∪O}, where O is the point set included in the current untraveled path T. Consider the queue status and path length of the vehicles on the path (i,j), and add the weight coefficient w _ij to the state transition probability to speed up the convergence of the algorithm, as follows:

表示路径(i,j)的启发因子，对距离i较近的节点，偏好度较高；α表示蚂蚁在运动过程中所积累的信息素重要性系数，β表示启发因子的重要性系数；(i,n)表示所有可能的节点；w_ij为路径长度因素和小车排队长度因素的综合系数。Where: d _avg is the path average from node i to all next adjacent nodes, t _ij is the time it takes for a car to pass through path (i, j), Δt is the time it takes for a car to wait for another car that needs to pass through path (i, j) to pass through node i when queuing, θ is the number of cars currently in the queue, and τ _ij is the pheromone intensity of path (i, j);

represents the inspiration factor of path (i, j), and the preference for nodes closer to i is higher; α represents the importance coefficient of pheromones accumulated by ants during movement, β represents the importance coefficient of inspiration factor; (i, n) represents all possible nodes; w _ij is the comprehensive coefficient of path length factor and car queue length factor.

不断迭代选择下一个节点和路径，直至小车到达终点为止，若无法到达终点，则从起始点开始重新进行此步骤。According to the state transition probability

The next node and path are selected iteratively until the car reaches the end point. If the car cannot reach the end point, repeat this step from the starting point.

S4: Evaluate the current route solution and record the optimal solution: compare the total length of the routes searched by each ant and record the shortest route;

S5: Update pheromone: After all ants have constructed a solution, the pheromones on the lines between nodes are updated according to the following rules:

τ _ij (l+1)＝ρτ _ij (l)+Δτ _ij (l)

If τ _ij (l+1)＜τ _min , then τ _ij (l+1)=τ _min

If τ _ij (l+1)>τ _max , then τ _ij (l+1)=τ _max

否则为0；

When ant k passes through path (i,j) in this cycle,

Otherwise, 0;

中添加权重λ，使得优于当前最优路径的路线信息素增量明显高于劣于当前最优路径的路线，优化信息素浓度更新方式。Where τ _ij (l) is the pheromone on the l-th generation path (i, j), Δτ _ij (l) is the value of the increase in the pheromone concentration of (i, j) in this cycle path, the initial time is 0, L _k is the length of the path taken by the k-th ant in this cycle path, Q is a constant, L _b is the optimal path currently found,

The weight λ is added in the , so that the pheromone increment of the route that is better than the current optimal path is significantly higher than the route that is worse than the current optimal path, and the pheromone concentration update method is optimized.

S6: Operation termination judgment

输出最优路线L_best作为小车运行路线，并重置返回S1。Determine whether the current number of iterations D has reached the preset number of iterations M. If not, return to S4 and replace D with (D+1); if it has, stop the operation and reset the pheromone τ and the transfer probability

Output the optimal route L _best as the vehicle's running route, and reset and return to S1.

The present invention eliminates the need for manual sorting, scanning, and checking of commodities when they are shipped out of the warehouse, thereby greatly improving the efficiency of shipping out of the warehouse, reducing the error rate, and reducing labor costs.

Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims (2)

1. The automatic delivery system for the goods distributed by the e-commerce logistics is characterized by comprising a server and an automatic delivery device, wherein the server is transmitted by signals, the server comprises a central processing unit I and an algorithm module which are connected by signals, the automatic delivery device comprises a transportation pipeline, if a fault occurs when a trolley provided with a fault diagnosis module runs in the transportation pipeline, the central processing unit I judges whether other trolleys pass through the area where the fault trolley is located, and if so, the algorithm module re-plans an optimal path for the trolley;

the transportation pipeline comprises an inverted T-shaped pipeline A communicated with one end of a cargo inlet pipeline opening and a plurality of pipelines parallel to the ground communicated with the bottom end of the inverted T-shaped pipeline A, the pipelines parallel to the ground are communicated with one end of a discharge pipeline opening, the other end of the discharge pipeline opening is communicated with one end of an L-shaped pipeline of an empty car return pipeline, the other end of the L-shaped pipeline is communicated with the bottom end of an inverted T-shaped pipeline B, and the top end of the inverted T-shaped pipeline B is communicated with the other end of the cargo inlet pipeline opening; a trolley temporary storage area is arranged in the pipeline in the vertical direction of the inverted T-shaped pipeline B;

the unloading pipeline opening is provided with a transverse guide rail, a hydraulic push-pull device and a vertical guide rail, the transverse guide rail comprises a hollow guide rail and a movable guide rail, the hollow guide rail is fixed in a horizontal conveying pipeline, one end of the hydraulic push-pull device is arranged, the other end of the hydraulic push-pull device is welded with the movable guide rail, and the vertical guide rail is arranged in the vertical conveying pipeline;

the specific process of the algorithm module for planning the re-optimal path for the trolley is as follows:

s1: initializing pipeline environment and algorithm parameters;

s2: the algorithm module receives a trolley route planning task, and the trolley receives path information from the execution module;

s3: constructing a trolley transportation route solution;

s4: evaluating the current route solution, and recording the optimal solution;

s5: updating the pheromone;

s6: judging operation termination;

judging whether the current iteration number D reaches the preset iteration number M, if not, returning to S4 and replacing D with (D+1); if so, stopping operation, resetting pheromone and transition probability, outputting an optimal route as a trolley operation route, and returning to the step S1;

the construction of the trolley transportation route solution specifically comprises the following steps:

starting from node 1 for each ant, when searching for the (k+1) th node, according to the probability

From the feasible point set SSelecting a node from = { j epsilon V|{1, n } -U O }, wherein O is a point set contained in the current non-walked path T, and adding a weight coefficient w into the state transition probability by considering the queuing condition of the trolley and the path length of the path (i, j) _ij ：

Wherein: v= {1,2,..n } is the set of transport pipe nodes in the environment, d _avg Is the path average, t, from node i to all next neighbor nodes _ij For the time required for the trolley to pass through the path (i, j), deltat represents the time required for the trolley to wait for another trolley needing to pass through the path (i, j) to pass through the node i while queuing, and theta represents the number of currently queued trolleys, tau _ij Pheromone intensity, eta representing path (i, j) _ij Heuristic factors representing paths (i, j), alpha represents pheromone importance coefficients accumulated by ants in the motion process, beta represents importance coefficients of the heuristic factors, and (i, n) represents all possible nodes;

from state transition probabilities

The next node and path are iteratively selected until the trolley reaches the end point, and if the end point cannot be reached, the process is restarted from the start point.

2. The automated delivery system for the e-commerce logistics distribution of goods of claim 1, wherein the trolley comprises rollers, vertical moving rollers, a horizontal moving mechanism and a vehicle body, wherein the rollers are partially installed in the vehicle body, the vertical moving rollers are fixed on four corners of the vehicle body, and the horizontal moving mechanism is embedded in the bottom of the vehicle body.

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