CN116245435A - Material distribution service scheduling management system based on unmanned aerial vehicle and vehicle cooperation - Google Patents
Material distribution service scheduling management system based on unmanned aerial vehicle and vehicle cooperation Download PDFInfo
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Abstract
The invention discloses a material distribution service dispatch management system based on unmanned aerial vehicle and vehicle cooperation, which relates to the technical field of material distribution and comprises the following components: the system comprises a material management module, an algorithm running module, an algorithm performance comparison module, an algorithm comparison visualization module and a distribution management module, wherein the material management module is used for managing materials; the algorithm operation module is used for processing and analyzing the selected logistics data, combining with the actual traffic topology to obtain the coordinated transportation route information of the unmanned aerial vehicle and the vehicle, and displaying the route diagram under the condition of different user numbers; the algorithm performance comparison module is used for performing performance comparison on other algorithms; the algorithm comparison visualization module is used for displaying the comparison between different traffic environments and different acquisition points and drawing a line visual comparison chart; the distribution management module is used for selecting distribution materials, acquiring distribution sites and distribution logistics information in real time and performing visual display in a chart form.
Description
Technical Field
The invention relates to the technical field of material distribution service scheduling management systems, in particular to a material distribution service scheduling management system for cooperation of an unmanned aerial vehicle and a vehicle.
Background
The continuous aggravation of the modern unmanned trend makes the application of unmanned aerial vehicles in the military field more important, and can bear various tasks such as reconnaissance detection, tracking and positioning, accurate guidance, electromagnetic interference, material delivery and the like. The accurate execution of the unmanned aerial vehicle task depends on a reasonable and efficient management and control mechanism, namely, according to environmental information perceived by the unmanned aerial vehicle, task requirements, task loads on the unmanned aerial vehicle and other constraint conditions, the task elements are comprehensively analyzed, the scheduling and coordination of various resources are optimized, and the unmanned aerial vehicle task perception, network communication, routing transmission and flight path planning strategies are determined, so that the unmanned aerial vehicle can efficiently complete the task in an optimal mode.
With the development of electronic information technology and the improvement of the informatization and intelligence level of unmanned aerial vehicles, the task perception execution environment and modes of unmanned aerial vehicles are deeply changed, and particularly, the wide area high dynamic state of the task execution environment and the complex diversification of task demands are realized. Under the promotion of the targets of 'carbon reaching peak, carbon neutralization' and 'non-contact delivery', unmanned aerial vehicle and vehicle delivery are taken as a novel material delivery mode, and the time surge of compliance with unmanned trend enters the military field of view and receives high attention from the state. The system can support the military general sense calculation integrated cooperative intelligent combat platform and also can support civil logistics distribution and air-land resource cooperation which can support unmanned aerial vehicle and vehicle cooperation.
CN114677087a, a collaborative distribution method for a vehicle combined unmanned aerial vehicle, predicts logistics order prediction information in a period of time in the future through a sales prediction method based on a meta learning framework, and is used for planning a logistics scheduling scheme and a logistics distribution scheme. Aiming at the logistics scheduling scheme, the method and the system judge and select the distribution scheme according to the height difference among different path nodes, and optimize the logistics scheduling scheme by adopting a delay time punishment function. Meanwhile, the invention also adopts the unmanned aerial vehicle path optimization model to optimize the logistics distribution path, and optimizes the unmanned aerial vehicle path optimization model through a linear relaxation optimization algorithm. The scheme is as follows: obtaining logistics order forecast information; planning a logistics scheduling scheme and a logistics distribution path based on logistics order prediction information; optimizing a logistics scheduling scheme and a logistics distribution path; and carrying out logistics distribution according to the optimized logistics scheduling scheme and the logistics distribution path.
The CN114677087a patent focuses on proposing a formula scheme for logistics distribution, only the derivation of the theoretical formula is remained, and the practical value and effectiveness of the scheme are not considered; the present patent focuses on providing a management system for logistics distribution, applying the proposed algorithm to the actual logistics by combining the real traffic topology by using the front-end and back-end technology, and comparing the practical value obtained by the running results of the CMDSS algorithm proposed by the present patent and other related algorithms to show the effectiveness of the algorithm.
Disclosure of Invention
The present invention is directed to solving the above problems of the prior art. A material distribution service dispatching management system based on unmanned aerial vehicle and vehicle cooperation is provided. The technical scheme of the invention is as follows:
a material distribution service dispatch management system based on unmanned aerial vehicle and vehicle cooperation, comprising: the system comprises a material management module, an algorithm running module, an algorithm performance comparison module, an algorithm comparison visualization module and a distribution management module, wherein the material management module is used for managing materials and comprises the steps of performing adding, deleting and checking operations on material information in real time and visualizing and displaying the material library and historical material data in a chart form; the algorithm operation module is used for processing and analyzing the selected logistics data, combining with the actual traffic topology to obtain the coordinated transportation route information of the unmanned aerial vehicle and the vehicle, and displaying the route diagram under the condition of different user numbers; the algorithm performance comparison module is used for comparing the performance of other algorithms, comparing the performance of other two algorithms based on different user numbers, different loads of the unmanned aerial vehicle and different demands of the user, maximizing the ratio of the flying distance of the unmanned aerial vehicle to the driving distance of the vehicle under the condition of minimum driving distance of the vehicle from the aspect of cost by adopting the material distribution service scheduling (CoordinationofUAVand vehiclematerialdistributionservicescheduling, CMDSS) algorithm based on the cooperation of the unmanned aerial vehicle and the vehicle and drawing a comparison graph of the unmanned aerial vehicle and the vehicle; the algorithm comparison visualization module is used for displaying a quantitative index graph obtained by comparing the algorithm with other algorithms, comparing the quantitative index graph with different acquisition points under different traffic environments, drawing a line visual comparison graph, and comparing the line visual comparison graph with the unmanned aerial vehicle and vehicle collaborative transportation routes obtained by other related algorithms so as to ensure that the unmanned aerial vehicle and the vehicles with the minimum quantity are scheduled and the running time and distance are the shortest; the distribution management module is used for selecting distribution materials, acquiring distribution sites and distribution logistics information in real time and performing visual display in a chart form.
Further, the material management module comprises a real-time display material stock module, a history material data module, a material information adding module, a material information deleting module, a material information modifying module and a material information checking module; wherein,,
the real-time display material stock module is used for visually displaying the existing material stock in a cake-shaped picture form;
the historical material data module is used for dynamically displaying daily historical data including distributed material data and total material quantity in a dragging line diagram mode.
The material adding information module, the material deleting information module, the material modifying information module and the material viewing information module are respectively used for adding, deleting, modifying and viewing the material information in real time.
Further, the algorithm running module comprises an algorithm theory module, a real-time algorithm module and a historical data algorithm module;
the algorithm theory module is used for visually displaying theoretical path diagrams of the deep reinforcement learning algorithm in 20, 30 and 50 candidate route data sets;
the real-time algorithm module is used for selecting a material data set and then running an algorithm in real time, and generating a route result in real time by combining traffic topology;
the historical data algorithm module is used for generating a logistics data set of a corresponding time period after selecting the corresponding date and the time period, and then calling an implementation algorithm to obtain a route scheme;
further, the algorithm performance comparison module comprises a performance comparison module based on different user numbers, a performance comparison module based on different loads of the unmanned aerial vehicle and a performance comparison module based on different requirements of the user; wherein,,
the performance comparison module based on different user numbers is used for drawing a comparison histogram of the total flight distance of the unmanned aerial vehicle and the total travel distance of the vehicle under the condition that the number of clients is 20, 30 and 50 by using an algorithm used by the system and other two comparison algorithms, and drawing a comparison graph of the ratio of the total flight distance of the unmanned aerial vehicle to the total travel distance of the vehicle under the condition that the number of clients is different;
the performance comparison module based on different loads of the unmanned aerial vehicle is used for drawing a comparison line diagram of the total flight distance of the unmanned aerial vehicle and the total travel distance of the vehicle under the condition that the maximum loads of the unmanned aerial vehicle are 8kg, 9kg, 10kg, 11kg and 12kg respectively, and drawing a comparison graph of the total flight distance of the unmanned aerial vehicle and the total travel distance of the vehicle under the condition that the maximum loads of the unmanned aerial vehicle are different;
the performance comparison module based on different requirements of users is used for drawing a comparison line diagram of the total flight distance of the unmanned aerial vehicle and the total travel distance of the vehicle under the condition that the requirements of clients are 1kg, 2kg, 3kg, 4kg and 5kg respectively, and drawing a comparison graph of the ratio of the total flight distance of the unmanned aerial vehicle to the total travel distance of the vehicle under the condition that the requirements of clients are different.
Further, the algorithm comparison visualization module comprises a comparison visualization module under different traffic environments, a comparison visualization module with different numbers of clients, an operation equipment number comparison module, an operation cost comparison module, an operation distance proportion comparison module and an operation time comparison module;
the comparison visualization module in different traffic environments refers to an algorithm used by the system and a comparison algorithm which are respectively applied to real maps of Hangzhou and Chengdu, and the obtained unmanned aerial vehicle and vehicle cooperative transportation routes are compared by combining a traffic topological graph, and a visual comparison graph is drawn;
the comparison and visualization module of different customer numbers refers to that an algorithm used by the system and a comparison algorithm are applied to real maps with different numbers of acquisition points, and the obtained unmanned aerial vehicle and vehicle collaborative transportation routes are compared by combining a traffic topological graph, and a visual comparison graph is drawn;
the running equipment quantity comparison graph module is used for comparing the quantity of the unmanned aerial vehicle to the quantity of vehicles required to run according to running lines obtained by different algorithms in comparison graphs based on different traffic environments and different customer quantities;
the operation cost comparison module is used for comparing operation costs required in comparison graphs based on different traffic environments and different numbers of clients, the operation cost is calculated to be 1 yuan per kilometer when the vehicle runs, and 0.5 yuan per kilometer when the unmanned aerial vehicle runs;
the running time comparison module refers to the comparison of the running time required by the transportation route obtained by different algorithms in the comparison graphs based on different traffic environments and different numbers of clients.
Further, the distribution management module comprises a historical material selection module, a real-time updating and dispatching station module, a real-time obtaining and distributing material information module, a material distribution station statistics module and a material route visualization module; wherein,,
the material data set selection module is used for selecting the current day data set to run the CMDSS algorithm so as to obtain a real-time route result;
the real-time updating and dispatching site module is used for updating the dispatched site information in real time;
the real-time material information acquisition and delivery module updates the material information being dispatched in real time;
the material distribution site statistics module is used for counting historical material distribution sites and visually displaying the historical material distribution sites by using a frequency scatter diagram; the material route visualization module is used for dynamically visualizing and displaying route results operated by the algorithm.
The invention has the advantages and beneficial effects as follows:
1. the invention has novel function: the scheduling management system provided by the invention not only realizes material management, but also realizes unmanned aerial vehicle and vehicle material scheduling and path planning management, and the management system can support a military general sense calculation integrated cooperative intelligent combat platform, and also can support logistics distribution and air-land resource cooperation of civil unmanned aerial vehicles and vehicles.
2. Scene to accommodate a large number of customers: fig. 7 shows the relationship among the ratio of the total distance travelled by the unmanned aerial vehicle to the total distance travelled by the vehicle, and the total distance travelled by the unmanned aerial vehicle in order from left to right under the condition of different numbers of users. As can be seen in the three comparison pictures, when the number of users is 20, 30 and 50, respectively, the distance ratio of the unmanned plane and the vehicle of the CMDSS algorithm is higher than the distance ratio of the reinforcement learning algorithm, and the vehicle driving distance of the CMDSS algorithm is smaller than the distance of the deep reinforcement learning algorithm and the greedy algorithm, and the two differences are more obvious along with the continuous increase of the number of the users. Therefore, the CMDSS algorithm shows optimal performance under the conditions of large number of clients, small number of vehicles and reasonable flight route of the unmanned aerial vehicle in consideration of cost and other factors, so that the algorithm is more suitable for the scenes of a large number of clients.
3. Maximum load suitable for different unmanned aerial vehicles: fig. 8 shows the relationship among the ratio of the total distance travelled by the unmanned aerial vehicle to the total distance travelled by the vehicle, and the total distance travelled by the unmanned aerial vehicle, in order from left to right, under the condition of different maximum loads of the unmanned aerial vehicle. The ratio of the flight distance of the unmanned aerial vehicle to the vehicle travel distance is close to the ratio of the flight distance of the unmanned aerial vehicle to the vehicle travel distance of the greedy algorithm under the condition that the maximum loads of the unmanned aerial vehicle are different, the ratio is larger than the ratio of the flight distance of the unmanned aerial vehicle to the vehicle travel distance of the deep reinforcement learning algorithm, and the travel distance of the vehicle is slightly lower than the greedy algorithm. The CMDSS algorithm is therefore suitable for the maximum load of various unmanned aerial vehicles.
4. Effectiveness of CMDSS algorithm: fig. 9 shows the relationship among the ratio of the total distance of unmanned aerial vehicle flight to the total distance of vehicle, the total distance of vehicle flight and the total distance of unmanned aerial vehicle flight in order from left to right under the condition of customer demand. Because the weight-required packages of the transported materials occupy a larger amount, when the customer demand is 1.0kg to 3.0kg, the descending trend of the total flying distance of the unmanned aerial vehicle and the total traveling distance of the vehicle is faster; the distance travelled by the vehicle is also significantly lower than the distance of the other two algorithms. The effectiveness of the CMDSS algorithm of the unmanned aerial vehicle under the condition of small load is proved.
5. Advantages of the system in real traffic: a, b and c in fig. 13 represent two algorithm comparison graphs of different numbers in different regions, which are respectively a comparison graph of the actual traffic topology of Hangzhou 13 data nodes, 17 data nodes in Hangzhou 25 data nodes. Taking the graph a as an example, the number of vehicles, the number of unmanned aerial vehicles, the total distance travelled by the vehicles and the unmanned aerial vehicles, the sum of driving vehicles and the driving cost are respectively compared from left to right by using two algorithms of CMDSS and DRL. It can be seen from the figure that under the condition of the same node, the CMDSS algorithm is more advantageous than the DRL in the number of input devices, the driving distance, the driving time and the driving cost.
The innovation point of the invention is mainly that the algorithm operation module, the algorithm performance comparison module and the algorithm comparison visualization module are adopted, wherein the CMDSS algorithm used in the algorithm operation module is improved based on a greedy algorithm; comparing the performance of the CMDSS algorithm with that of the DRL algorithm and that of the greedy algorithm through an algorithm performance comparison module so as to show the superiority of the CMDSS algorithm; and the CMDSS algorithm is applied to a material distribution service scheduling system of unmanned aerial vehicle and vehicle cooperation through a front-end and back-end technology, and simulation and quantitative comparison are carried out by combining with a real traffic topology so as to show the practical value of the system in actual traffic.
Drawings
FIG. 1 is a schematic diagram of a system functional module framework in accordance with a preferred embodiment of the present invention
FIG. 2 is a schematic diagram of a material management module according to the present invention
FIG. 3 is a schematic flow chart of a material management module according to the present invention
FIG. 4 is a theoretical operating diagram of 20 data nodes of the present invention
FIG. 5 is a theoretical operation chart of 30 data nodes of the present invention
FIG. 6 is a theoretical operation chart of 50 data nodes of the present invention
FIG. 7 is a bar graph of the present invention based on different user performance
FIG. 8 is a graph showing performance comparisons based on different maximum loads of the unmanned aerial vehicle
FIG. 9 is a graph showing the comparison of performance based on different demands of users according to the present invention
FIG. 10 is a graph comparing actual traffic topology of 13 data nodes in Hangzhou using two algorithms in accordance with the present invention
FIG. 11 is a graph comparing actual traffic topology at 17 nodes in a lump using two algorithms in accordance with the present invention
FIG. 12 is a graph comparing actual traffic topologies at Hangzhou 25 data nodes using two algorithms in accordance with the present invention
FIG. 13 is a quantized histogram of the present invention in comparison with FIGS. 10, 11 and 12
FIG. 14 is a schematic diagram of a distribution management module
FIG. 15 is a flow chart of a distribution management module
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and specifically described below with reference to the drawings in the embodiments of the present invention. The described embodiments are only a few embodiments of the present invention.
The technical scheme for solving the technical problems is as follows:
the following generally describes functions of a material distribution service dispatch management system based on unmanned aerial vehicle and vehicle cooperation:
as shown in FIG. 1, the material distribution service scheduling management system based on the cooperation of the unmanned aerial vehicle and the vehicle comprises a material management module, an algorithm running module, an algorithm performance comparison module, an algorithm comparison visualization module and a distribution management module. The material management module is used for managing military materials and comprises the steps of performing adding, deleting and checking operations on material information in real time and visually displaying the library materials and historical material data in a chart form; the algorithm running module is used for processing and analyzing the selected logistics data, obtaining the cooperative transportation route information of the unmanned aerial vehicle and the vehicle by combining the actual traffic topology, and displaying a circuit diagram under the condition of different user numbers; the algorithm performance comparison module is used for comparing the performance of other algorithms, comparing the performance of other two algorithms based on different user numbers, different loads of the unmanned aerial vehicle and different demands of the user, and particularly embodying that the ratio of the flight distance of the unmanned aerial vehicle to the vehicle travel distance is maximized under the condition that the vehicle travel distance is minimum from the viewpoint of cost, and drawing a comparison graph of the ratio; the algorithm comparison visualization module is used for displaying a quantitative index graph obtained by comparing the algorithm with other algorithms, comparing the quantitative index graph with different acquisition points under different traffic environments, drawing a line visual comparison graph, and comparing the line visual comparison graph with unmanned aerial vehicles and vehicle cooperative transportation routes obtained by other related algorithms so as to ensure that the number of unmanned aerial vehicles and vehicles with minimum scheduling is ensured and the running time and distance are shortest; the distribution management module is used for selecting distribution materials, acquiring distribution sites and distribution logistics information in real time and carrying out visual display in a chart form.
1. Material management module
1) Real-time showing material and goods storage module: the existing goods and materials are visually displayed in the form of a pie chart.
2) Historical material data module: for dynamically displaying daily history data including delivered material data and total amount of material in the form of a drag line graph.
2. Algorithm running module
1) Algorithm theory module: theoretical path diagrams for visualizing the depth reinforcement learning algorithm at 20, 30 and 50 candidate route datasets;
2) And a real-time algorithm module: the method is used for selecting a material data set and then running an algorithm in real time, and generating a route result in real time by combining traffic topology;
3) Historical data algorithm module: after the corresponding date and the corresponding time period are selected, a logistics data set of the corresponding time period is generated, and then an implementation algorithm is called to obtain a route scheme;
3. the algorithm performance comparison module
1) Performance comparison module based on different numbers of users: the system comprises a comparison histogram for drawing an algorithm used by the system and the other two comparison algorithms, wherein the comparison histogram of the total flight distance of the unmanned aerial vehicle and the total travel distance of the vehicle is shown under the condition that the number of clients is 20, 30 and 50, and a comparison graph of the ratio of the total flight distance of the unmanned aerial vehicle to the total travel distance of the vehicle is shown under the condition that the number of clients is different;
2) Performance comparison module based on different loads of unmanned aerial vehicle: the system comprises an algorithm used by the system and two other comparison algorithms, wherein the algorithm and the two other comparison algorithms are used for drawing a comparison line diagram of the total flight distance of the unmanned aerial vehicle and the total travel distance of the vehicle under the condition that the maximum load of the unmanned aerial vehicle is 8kg, 9kg, 10kg, 11kg and 12kg respectively, and drawing a comparison graph of the ratio of the total flight distance of the unmanned aerial vehicle to the total travel distance of the vehicle under the condition that the maximum loads of the unmanned aerial vehicle are different;
3) The performance comparison based on different numbers of users: the system comprises an algorithm used for drawing a comparison line diagram of the total flight distance of the unmanned aerial vehicle and the total travel distance of the vehicle under the condition that the client requirements are 1kg, 2kg, 3kg, 4kg and 5kg respectively, and a comparison graph of the ratio of the total flight distance of the unmanned aerial vehicle to the total travel distance of the vehicle under the condition that the client requirements are different;
4. the algorithm comparison visualization module
1) And the contrast visualization module is used for comparing under different traffic environments: the method is characterized in that an algorithm used by the system and a comparison algorithm are respectively applied to real maps of Chengdu and Hangzhou, and the obtained unmanned aerial vehicle and vehicle cooperative transportation route are compared by combining a traffic topological graph, and a visual comparison graph is drawn;
2) Different customer count contrast visualization module: the method is characterized in that an algorithm used by the system and a comparison algorithm are respectively applied to real maps of different collection points in Hangzhou, and the obtained unmanned aerial vehicle and vehicle cooperative transportation route are compared by combining a traffic topological graph, and a visual comparison graph is drawn;
3) Running a device quantity comparison graph module: the method is characterized in that the method refers to operation lines obtained by different algorithms in comparison graphs based on different traffic environments and different numbers of clients, and the number of unmanned aerial vehicles and vehicles required to be operated are compared;
4) And an operation cost comparison module: the method is used for comparing the running cost required in the comparison graphs based on different traffic environments and different numbers of clients, and the running cost of the unmanned aerial vehicle is calculated to be 1 yuan per kilometer, and the running cost of the unmanned aerial vehicle is calculated to be 0.5 yuan per kilometer;
5) And a running time comparison module: the method is used for comparing the required running time of the transportation routes based on different traffic environments and different algorithms in the comparison graphs based on different numbers of clients;
6. distribution management module
1) The historical material selection module is used for selecting the data set of the current day to run the algorithm so as to obtain a real-time route result.
2) Updating the dispatch site module in real time: updating the distributed site information in real time;
3) The real-time material distribution information acquisition module is used for acquiring material distribution information in real time: updating the material information being sent in real time;
4) The material distribution site statistics module: for statistics of the current month history material distribution sites and visualized by using a frequency scatter diagram.
5) A material route visualization module: and the method is used for dynamically visualizing the route result run by the algorithm.
The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The above examples should be understood as illustrative only and not limiting the scope of the invention. Various changes and modifications to the present invention may be made by one skilled in the art after reading the teachings herein, and such equivalent changes and modifications are intended to fall within the scope of the invention as defined in the appended claims.
Claims (6)
1. A material distribution service dispatch management system based on unmanned aerial vehicle and vehicle cooperation, characterized by comprising: the system comprises a material management module, an algorithm running module, an algorithm performance comparison module, an algorithm comparison visualization module and a distribution management module, wherein the material management module is used for managing materials and comprises the steps of performing adding, deleting and checking operations on material information in real time and visualizing and displaying the material library and historical material data in a chart form; the algorithm operation module is used for processing and analyzing the selected logistics data, combining with the actual traffic topology to obtain the coordinated transportation route information of the unmanned aerial vehicle and the vehicle, and displaying the route diagram under the condition of different user numbers; the algorithm performance comparison module is used for comparing the performance of other algorithms, comparing the performance of the designed material distribution service scheduling CMDSS algorithm based on the cooperation of the unmanned aerial vehicle and the vehicle with the performance of the deep reinforcement learning algorithm and the greedy algorithm under the conditions of different user numbers, different loads of the unmanned aerial vehicle and different requirements of the user, maximizing the ratio of the flight distance of the unmanned aerial vehicle to the travel distance of the vehicle under the condition of minimum travel distance of the vehicle from the aspect of cost, and drawing a comparison graph of the ratio; the algorithm comparison visualization module is used for displaying a quantitative index graph obtained by comparing the algorithm with other algorithms, comparing the quantitative index graph with different acquisition points under different traffic environments, drawing a line visual comparison graph, and comparing the line visual comparison graph with the unmanned aerial vehicle and vehicle collaborative transportation routes obtained by other related algorithms so as to ensure that the unmanned aerial vehicle and the vehicles with the minimum quantity are scheduled and the running time and distance are the shortest; the distribution management module is used for selecting distribution materials, acquiring distribution sites and distribution logistics information in real time and performing visual display in a chart form.
2. The material distribution service scheduling management system based on the cooperation of the unmanned aerial vehicle and the vehicle according to claim 1, wherein the material management module comprises a real-time display material stock module, a history material data module, an addition material information module, a deletion material information module, a modification material information module and a view material information module; wherein,,
the real-time display material stock module is used for visually displaying the existing material stock in a cake-shaped picture form;
the historical material data module is used for dynamically displaying daily historical data including distributed material data and total material quantity in a dragging line diagram mode.
The material adding information module, the material deleting information module, the material modifying information module and the material viewing information module are respectively used for adding, deleting, modifying and viewing the material information in real time.
3. The material distribution service scheduling management system based on the cooperation of the unmanned aerial vehicle and the vehicle according to claim 1, wherein the algorithm running module comprises an algorithm theory module, a real-time algorithm module and a historical data algorithm module; wherein,,
the algorithm theory module is used for visually displaying theoretical path diagrams of the deep reinforcement learning algorithm in 20, 30 and 50 candidate route data sets;
the real-time algorithm module is used for selecting a material data set and then running an algorithm in real time, and generating a route result in real time by combining traffic topology;
the historical data algorithm module is used for generating a logistics data set of a corresponding time period after selecting the corresponding date and the time period, and then calling an implementation algorithm to obtain a route scheme.
4. The material distribution service scheduling management system based on the cooperation of the unmanned aerial vehicle and the vehicle according to claim 1, wherein the algorithm performance comparison module comprises a performance comparison module based on different user numbers, a performance comparison module based on different loads of the unmanned aerial vehicle and a performance comparison module based on different requirements of the users; wherein,,
the performance comparison module based on different user numbers is used for drawing a comparison histogram of the total flight distance of the unmanned aerial vehicle and the total travel distance of the vehicle under the condition that the number of clients is 20, 30 and 50 by using an algorithm used by the system and other two comparison algorithms, and drawing a comparison graph of the ratio of the total flight distance of the unmanned aerial vehicle to the total travel distance of the vehicle under the condition that the number of clients is different;
the performance comparison module based on different loads of the unmanned aerial vehicle is used for drawing a comparison line diagram of the total flight distance of the unmanned aerial vehicle and the total travel distance of the vehicle under the condition that the maximum loads of the unmanned aerial vehicle are 8kg, 9kg, 10kg, 11kg and 12kg respectively, and drawing a comparison graph of the total flight distance of the unmanned aerial vehicle and the total travel distance of the vehicle under the condition that the maximum loads of the unmanned aerial vehicle are different;
the performance comparison module based on different requirements of users is used for drawing a comparison line diagram of the total flight distance of the unmanned aerial vehicle and the total travel distance of the vehicle under the condition that the requirements of clients are 1kg, 2kg, 3kg, 4kg and 5kg respectively, and drawing a comparison graph of the ratio of the total flight distance of the unmanned aerial vehicle to the total travel distance of the vehicle under the condition that the requirements of clients are different.
5. The material distribution service scheduling management system based on the cooperation of the unmanned aerial vehicle and the vehicle according to claim 1, wherein the algorithm comparison visualization module comprises a comparison visualization module, a different client number comparison visualization module, an operation equipment number comparison module, an operation cost comparison module, an operation distance proportion comparison module and an operation time comparison module under different traffic environments;
the comparison visualization module in different traffic environments refers to an algorithm used by the system and a comparison algorithm which are respectively applied to real maps of Hangzhou and Chengdu, and the obtained unmanned aerial vehicle and vehicle cooperative transportation routes are compared by combining a traffic topological graph, and a visual comparison graph is drawn;
the comparison and visualization module of different customer numbers refers to that an algorithm used by the system and a comparison algorithm are applied to real maps with different numbers of acquisition points, and the obtained unmanned aerial vehicle and vehicle collaborative transportation routes are compared by combining a traffic topological graph, and a visual comparison graph is drawn;
the running equipment quantity comparison graph module is used for comparing the quantity of the unmanned aerial vehicle to the quantity of vehicles required to run according to running lines obtained by different algorithms in comparison graphs based on different traffic environments and different customer quantities;
the operation cost comparison module is used for comparing operation costs required in comparison graphs based on different traffic environments and different numbers of clients, the operation cost is calculated to be 1 yuan per kilometer when the vehicle runs, and 0.5 yuan per kilometer when the unmanned aerial vehicle runs;
the running time comparison module refers to the comparison of the running time required by the transportation route obtained by different algorithms in the comparison graphs based on different traffic environments and different numbers of clients.
6. The material distribution service scheduling management system based on the cooperation of the unmanned aerial vehicle and the vehicle according to claim 1, wherein the distribution management module comprises a historical material selection module, a real-time update dispatch site module, a real-time acquisition distribution material information module, a material distribution site statistics module and a material route visualization module; wherein,,
the material data set selection module is used for selecting the current day data set to run the CMDSS algorithm so as to obtain a real-time route result;
the real-time updating and dispatching site module is used for updating the dispatched site information in real time;
the real-time material information acquisition and delivery module updates the material information being dispatched in real time;
the material distribution site statistics module is used for counting historical material distribution sites and visually displaying the historical material distribution sites by using a frequency scatter diagram; the material route visualization module is used for dynamically visualizing and displaying route results operated by the algorithm.
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