CN110544067A - multi-type combined transport system - Google Patents
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Abstract
A multi-type intermodal transportation system obtains transportation schemes meeting customer requirement information through an input interface, a virtual network state diagram storage unit, a Dijkstra algorithm operation module and a DFS algorithm operation module, provides a plurality of transportation schemes meeting requirements for customers to select through an output interface, and then combines a plurality of logistics platforms to reserve the transportation distance of corresponding time periods through a preset interface according to the transportation schemes selected by users. Therefore, the invention can realize the five-in-one transportation scheme planning of the comprehensive sea, land, air, iron and pipeline. The invention can combine the advantages of various transportation modes to form a coherent transportation system, further shorten the freight turnover time, simplify the intermediate procedures, reduce the logistics cost and finally reach the standard of transportation standardization and rationalization.
Description
Technical Field
the invention belongs to the field of transportation path planning, and particularly relates to a multi-type intermodal transportation system.
background
With the increasing social economy, the logistics demand is increasing, and the requirement of a transportation system on the transportation efficiency and the cost cannot be met by a single transportation mode. The development direction of modern logistics enterprises is to carry out high-efficiency combined transportation by integrating five parts of sea, land, air, iron and pipelines. The multimodal transportation can better promote the collaborative development of multidimensional logistics and can also better promote the resource integration. The transportation system can fully gather the respective advantages of various transportation modes, make up for deficiencies of the various transportation modes, form a coherent transportation system, further shorten the freight turnover time, simplify intermediate procedures, reduce logistics cost and finally reach the standard of transportation standardization and rationalization.
The improvement of the transport efficiency and the benefit of the multimodal transportation mode mainly depends on the compilation of the transportation scheme. The programming of the transportation scheme is inseparable from the selection of the path and the mode in the transportation process. In the transportation process of the multi-type intermodal transportation, if a set of reasonable and proper intermodal transportation scheme can be designed, the transportation time, the cost and the fund backlog can be reduced, the satisfaction degree of customers can be improved, and the service quality can be improved. The multimodal transport also can make contributions to the improvement of competitive advantages at home and abroad, the construction of a low-carbon environment-friendly society, the improvement of the air-fuel ratio of a transport means, the energy conservation and the environmental protection.
Disclosure of Invention
aiming at the defects of the prior art, the invention provides a multi-type intermodal transportation system which can traverse all nodes through time estimation and price estimation, screen out various transportation schemes from different user requirements, solve the selection problem of transportation paths and transportation modes in multi-type intermodal transportation, and effectively reduce transportation cost and time by selecting reasonable transportation paths and transportation modes.
In order to solve the technical problem, the invention provides a computing system of a multimodal transportation scheme, which comprises an input interface, a data processing module and a data processing module, wherein the input interface is used for receiving customer requirement information, including the type, the quantity, the start time, the arrival time, the start point S and the destination D of goods to be transported; a virtual network state graph storage unit, configured to establish a virtual network state graph G ═ V, E, W according to the customer demand information, where a transportation mode set V ═ { ViW |1 ≦ i ≦ n,1 ≦ W } represents a set of all transportation modes that the goods can select at a node i, i represents a number of the node, n represents a total number of the nodes, W represents a number of the transportation modes, W represents a total number of the transportation modes, and an edge set E { (ViW, VjW) (ViL, VjK) |1 ≦ i < j ≦ n,1 ≦ W ≠ L ≠ K ≦ W } represents a set of edges that the goods can transport between the node i and the node j, where (ViW, VjW) represents a transport arc and (ViL, VjK) represents a conversion arc, where each edge has a different weight, respectively, and the weight represents a transport time or a transport cost required by the edge; a Dijkstra algorithm operation module, configured to calculate, by using a Dijkstra algorithm, a route with the shortest transportation time and a route with the lowest transportation cost from the departure point S to the destination D in the virtual network state diagram G ═ (V, E, W); a DFS algorithm operation module, configured to calculate, using a DFS algorithm, all reachable paths from the departure point S to the destination D in the virtual network state diagram G ═ V, E, W; the output interface outputs the failure information of the transportation scheme calculation when no reachable path exists; outputting a transportation plan to a customer when an reachable path exists, wherein the transportation plan comprises all the reachable paths, the path with the shortest transportation time and the path with the lowest transportation cost; the system comprises a preset interface, a plurality of logistics platforms and a plurality of control modules, wherein the preset interface is connected with the plurality of logistics platforms and is used for receiving a transportation scheme selected by a customer, respectively reserving the transport distance of a corresponding time period at the logistics platform corresponding to each side in sequence according to a set of sides contained in the transportation scheme, and outputting reservation success information when the transport distances corresponding to all sides are reserved successfully; and when any one of the preset distances fails, removing the edge corresponding to the distance, and triggering the virtual network state diagram storage unit, the Dijkstra algorithm operation module, the DFS algorithm operation module and the output interface to calculate or interact again according to the removed information.
Optionally, the computing system for a multimodal transportation scheme further includes a manual interface, which is triggered by the transportation scheme calculation failure information output by the output interface, and is configured to synchronously push the transportation scheme calculation failure information and the customer requirement information to a manual work, and forward manual intervention processing.
optionally, in the above computing system for a multimodal transportation scheme, the Dijkstra algorithm operation module specifically includes the following sub-modules to calculate, by using a Dijkstra algorithm, a route with the shortest transportation time and a route with the lowest transportation cost from the departure point S to the destination D in the virtual network state diagram G ═ V, E, W: the Dijkstra operation initialization submodule is used for establishing an array distTo, and storing the weight of each node in the virtual network state diagram G ═ V, E and W to the edge of the start point S in the array distTo; establishing an index priority queue pq, and storing each node and the minimum weight of the node to the edge of the origin point S in the index priority queue pq; a weight updating submodule, configured to calculate, starting from the origin point S, weights of edges from each adjacent node T adjacent to the origin point S, and store the weights in the array distTo and in the index priority queue pq; a weight comparison submodule, configured to update the weight stored in the submodule according to the weight, and perform the following steps in sequence from each adjacent node T: respectively calculating the weight of an intermediate node O adjacent to the adjacent node T to the origin point S as distTo (S- > O), respectively calculating the weight of the adjacent node T to the origin point S as distTo (T- > O), comparing the distTo (S- > O) with the distTo (T- > O) according to the weight of the edge of the adjacent node T to the intermediate node O, and updating the weight value of the edge from the intermediate node O to the origin point S in the array distTo and the index priority queue pq as distTo (T- > O) if the distTo (S- > O) is larger, so as to ensure that the shortest path from the O point to the S point exists in the array distTo and pq queues; and the Dijkstra operation output submodule is used for outputting the shortest transportation time path from the starting point S to the destination D and the lowest transportation cost path according to the node sequence stored after the last updating in the array distTo after all the adjacent nodes T are traversed by each submodule.
optionally, in the computing system of the multimodal transportation system, the DFS algorithm operation module specifically includes the following sub-modules to calculate all reachable paths from the departure point S to the destination D in the virtual network state diagram G ═ V, E, W by using the DFS algorithm: the DFS operation initialization submodule is used for emptying a stack vertex, and sequentially storing each node contained in a path with the shortest transportation time or the lowest transportation cost from an origin S to a destination D in the stack vertex; emptying another stack line, and sequentially storing each side contained in a path with the shortest transportation time or a path with the lowest transportation cost from the starting point S to the destination D in the stack line; emptying another queue list for storing all reachable paths; a first path searching submodule, configured to sequentially determine, starting from the starting point S, whether the node exists in the stack vertex, and if so, skip to step 405; if not, the node is pressed into the stack vertex, then a node T adjacent to the node is searched, whether the searched node T is the destination D or not is judged, if the searched node T is the destination D, the edge between the searched node T and the node is pressed into the stack line, then all the nodes are sequentially taken out from the stack vertex, the path formed by the nodes is a reachable path from the starting point S to the destination D, and the reachable path is stored in the queue list; if the destination D is not the destination D, pushing the found node T into the stack vertex, and pushing an edge between the found node T and the node into the stack line; a second path searching submodule, configured to repeat the step 402 from the found node T until a node at the end in the path is traversed, and perform a pop operation on the stack vertex and the stack line respectively; traversing the submodule, and repeating the step 403 until all nodes in the virtual network state diagram G ═ V, E, W are traversed; and the DFS operation output submodule is used for sequentially outputting all reachable paths from the starting point S to the destination D from the queue list.
Optionally, the computing system of the multimodal transportation scheme further includes a mongolian line optimization unit, which is connected to the Dijkstra algorithm operation module, the DFS algorithm operation module, and the output interface, and preferentially calculates and outputs each node and each edge corresponding to the mongolian line in the operation process.
advantageous effects
The multi-type intermodal transportation system provided by the invention obtains transportation schemes meeting the information of customer requirements through the input interface, the virtual network state diagram storage unit, the Dijkstra algorithm operation module and the DFS algorithm operation module, provides a plurality of transportation schemes meeting the requirements for customers to select through the output interface, and then combines a plurality of logistics platforms to reserve the transportation distance of corresponding time intervals through the preset interface according to the transportation schemes selected by the users. Therefore, the invention can realize the five-in-one transportation scheme planning of the comprehensive sea, land, air, iron and pipeline. The invention can combine the advantages of various transportation modes to form a coherent transportation system, further shorten the freight turnover time, simplify the intermediate procedures, reduce the logistics cost and finally reach the standard of transportation standardization and rationalization.
particularly, the multimodal transportation scheme provided by the invention can also provide the nodes and edges corresponding to the Mongolian lines for each operation module preferentially through the Mongolian line optimization unit when planning and calculating the transportation scheme, preferentially select the Mongolian lines to plan and optimize and calculate the path, realize optimization and efficiency improvement of the lines, realize the guarantee of the transportation to the time limit, and keep the price unchanged.
Drawings
Fig. 1 is a state diagram of a virtual network corresponding to all paths from a starting point S to a destination D in the present invention;
FIG. 2 is a schematic flow diagram of the operation of the multimodal transport system of the present invention;
FIG. 3 is a schematic illustration of route information output by the multimodal transport system of the present invention;
FIG. 4 is a directed graph corresponding to the route information of FIG. 3;
fig. 5 is a schematic illustration of a transportation scheme output by the multimodal transport system of the present invention.
Detailed Description
In order to make the purpose and technical solution of the embodiments of the present invention clearer, the technical solution of the embodiments of the present invention will be clearly and completely described below with reference to the drawings of the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the invention without any inventive step, are within the scope of protection of the invention.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The meaning of "and/or" in the present invention means that the respective single or both of them exist individually or in combination.
The invention provides a multi-type intermodal transportation system which is used for generating various paths in the planning process of a multi-type intermodal transportation scheme, realizing the reservation of the transportation distance in a one-stop mode according to the path selected by a client, improving the transportation efficiency and facilitating the client.
Based on this, the system mainly needs to be designed to sequentially realize the following 6 stages:
1. ordering by customer (inputting goods information, weight of goods, etc.), selecting initial site and destination site
2. The platform helps the customer to plan the lowest cost line, the shortest time line and all reachable lines according to the order information, the starting station and the destination station and by combining the line data and the transportation capacity of the platform
3. The customer selects a line with the most cost performance by combining the cost and the time condition of the customer.
4. after the customer selects the line, the platform places orders to different logistics platforms respectively, and when all the logistics platforms place orders successfully, the successful order placing is returned to the customer
5. If a certain platform fails to place an order, removing the unusable line data according to the failure reason, and repeating the steps 2-5
6. and if no reachable path exists after the unusable line is removed finally, the ordering fails and manual intervention processing is carried out.
Specifically, for most users of the Mongolian line, the above-mentioned 6 phases are used for:
firstly, selecting a starting coal yard + to reach a power plant;
secondly, giving the nearest originating station plus destination station (the station means including Monghua self line, special transport line and port);
third, the system automatically gives a scheme similar to "x" + switch site 1+ monhuan transportation + switch site 2+ "&"; wherein ". x" represents a non-montmorillonoid line comprising: state iron, other railway or waterway, "x" can be empty, and "x" is empty to indicate that the Mongolian starts to end; due to the uncertainty of the line, an actual estimated value cannot be given in the step, the transportation products need to be selected below, and different transportation products need different time expenses and transportation cost expenses; after selecting the originating station and the terminating station, generating a preliminary plan according to the originating station and the terminating station, and only showing a schematic diagram of possible lines, wherein the schematic diagram can include the following two information: estimation of transportation time (what the shortest time is, what the longest time is, which can be determined by experience), estimation of transportation cost (what the lowest price is, what the highest price is, which can be determined by experience or past price);
And taking over the preliminary scheme given in the process of the third step, and automatically pushing the Mongolian book line transportation products conforming to the station by the system, such as: if a suitable Mongolian shipping product is available, the shipping product can be directly selected, wherein the shipping product is similar to a quinquel, similar to a passenger car, and needs to be determined: the starting time, the transportation duration, the train number, the price and the loading and unloading place can be guaranteed, so that the time limit of transportation can be guaranteed, and the price is kept unchanged; if the transport products which meet the requirements of customers do not exist, operation line presetting is needed, and the operation line presetting needs to be carried out according to the operation line pushed by the production platform to carry out the line specification; wherein the planning of the operating route comprises the following steps: start time, start station, arrival station, transit length (usually empirical, temporary), and price estimate (empirical, the longer the time the cheaper).
fourthly, the client selects one of the operation lines which is suitable for the transportation requirement of the client by referring to the operation line given by the production platform (5 is taken up, and the second step, the third step and the fourth step are subsequent processes); in the interaction process, the system pushes the preset goods tonnage, starting, ending and starting time required by the customer to a production platform; the production platform arranges vehicles according to the requirements of customers, so that the number of the vehicles and the locomotive number can be given after the vehicles are arranged; therefore, the marketing platform in the system can receive the information of the production platform and update the transportation information for the client. Thus, the system can automatically push the site-compliant transportation products, selecting in & & transportation: the method comprises the following steps of (1) carrying out state railway transportation or waterway transportation, wherein the state railway transportation needs to be in butt joint with a state railway line, and only time and price can be estimated according to experience; waterway transportation, namely a molten iron combined transportation platform which needs to be in butt joint with the launching of a coal storage base;
fifthly, if any one platform fails to place an order, the system needs to remove unusable line data according to the failure reason, and repeats the steps until the sixth step;
and sixthly, if no reachable path exists after the unusable line is removed, the ordering fails, and manual intervention processing is carried out. Otherwise, sending the cargo information and the estimated Mongolian arrival time to a water transportation platform to reserve the shipping resources; wherein, for the shipping platform, the ship is arranged according to the need in this step, therefore the ship number can be given after arranging the ship, the arrival time (estimated value), therefore, the marketing platform receives the shipping platform information, updates the transportation information for the customer.
Finally, after the selection is finished, the time length and the price of a more accurate route can be given, the system automatically compares transportation schemes and gives: the scheme with optimal price and shortest time is used for the client to refer for selection.
in particular, for the above system, it can be set up on the server to implement the method steps described in fig. 2 for the respective modules having:
1) and the input interface is used for receiving the customer requirement information, including the type, the quantity, the shipment starting time, the arrival time, the shipment starting point S and the destination D of the goods to be transported.
2) The virtual network state diagram storage unit, which is shown in fig. 1, describes the customer requirement information obtained by the input interface as: a batch of goods passes through a plurality of cities from a starting city S and is transported to a destination city D, one or more transportation modes can be selected between any two adjacent cities, and the transportation capacity, the transportation cost and the transportation time of different transportation modes are different; if the transportation mode conversion is carried out in the midway node city, certain transportation cost and time can be generated, and the user is required to select and list the transportation scheme with the least transportation cost, the transportation scheme with the shortest transportation time and all the cost and time with the reachable transportation scheme according to the user requirement by integrating information such as the freight rates, the time costs and the like of all parties. The problem may be abstracted to the virtual network state diagram shown in fig. 1.
Where there is a graph G ═ (V, E, W), where the set V ═ { ViW |1 ≦ i ≦ n,1 ≦ W } represents the set of points that selected different transportation means at node i, i represents the node, and W represents the transportation means; wherein the set of edges E { (ViW, VjW) (ViL, VjK) |1 ≦ i < j ≦ n,1 ≦ W ≠ L ≠ K ≦ W } represents an edge formed by any two nodes, (ViL, VjW) represents a traffic arc, (ViL, VjK) represents a conversion arc, and the weight of the edge represents the cost (or time), so the problem becomes: in the directed graph, the problems of S to D point, shortest path (cost or time) and all reachable paths are solved.
3) Dijkstra algorithm operation module is used for solving the shortest path algorithm from one vertex to other vertexes and solving the shortest path in the weighted graph. The method comprises the following specific steps:
step 301, introducing an array distTo, storing the weight of each point to the edge of a source point (S), introducing an index priority queue pq, and storing the minimum weight of each point and the point to the source point;
step 302, starting from a source point, calculating the weight from the adjacent node of the source point to the source point, and storing the weight in distTo and pq;
Step 303, starting from the neighboring node (T), calculating the weight from the neighboring node (O) to the source point (S) of the node, comparing, adding the weight of the edge from T to O to distTo (S- > O) and distTo (T- > O), if the former is larger than the latter, changing the weight value from the previous O point to S point in distTo and pq, and ensuring that the shortest path from O point to S point exists in the array of distTo and pq queues;
Step 304, repeating step 303 until all nodes are calculated;
step 305, finally, the shortest path from each point to the source point (S) is stored in distTo, and corresponding data is taken out to be the shortest path of S- > D according to the position of the target node D in distTo.
4) and a DFS (Depth First Search) algorithm operation module or a BFS (Breadth First Search) algorithm realizes traversal. For the DFS algorithm, the corresponding specific steps in the invention comprise:
Step 401, introducing a stack vertex, storing the vertex into a passing node, introducing a stack to store a passing edge line, and introducing a queue to store all paths list;
step 402, starting from a source point (S), judging whether the node exists in the vertex, and if so, ending; if not, pressing S into a vertex stack, then finding nodes adjacent to S, judging whether the nodes are target nodes D, if so, pressing edges into a line stack, taking out all paths from the stack, namely the reachable paths from S to D, storing the paths in the list, and if not, pressing the node (T) into the vertex stack and pressing the edges into the line stack;
Step 403, repeating step 2 from (T), and when the end node is reached, popping the vertext stack and the line stack;
Step 404, repeating step 403 until all nodes are traversed;
in step 405, all reachable paths are fetched from list.
5) The output interface outputs the failure information of the transportation scheme calculation when no reachable path exists; outputting a transportation plan to a customer when an reachable path exists, wherein the transportation plan comprises all the reachable paths, the path with the shortest transportation time and the path with the lowest transportation cost;
6) the system comprises a preset interface, a plurality of logistics platforms and a plurality of control modules, wherein the preset interface is connected with the plurality of logistics platforms and is used for receiving a transportation scheme selected by a customer, respectively reserving the transport distance of a corresponding time period at the logistics platform corresponding to each side in sequence according to a set of sides contained in the transportation scheme, and outputting reservation success information when the transport distances corresponding to all sides are reserved successfully; and when any one of the preset distances fails, removing the edge corresponding to the distance, and triggering the virtual network state diagram storage unit, the Dijkstra algorithm operation module, the DFS algorithm operation module and the output interface to calculate or interact again according to the removed information.
taking the database shown in fig. 3 as an example, wherein transport _ type represents transportation mode, 1 represents rail transportation, 2 represents water transportation, freight represents transportation fee, here represents cost per ton (first masked mileage parameter), and transport _ time represents transportation time for this distance. The transportation-related information described above is plotted into a directed graph shown in fig. 4. In the directed graph, the lines marked by boxes represent railways, the lines marked by triangles represent waterways, and the middle of the lines represent time or transportation.
For the transportation situation reflected in fig. 3 and 4, it is assumed that 100 tons of coal are now required to be transported from beijing to nanjing, and it is assumed that the time consumed per ton of coal is 0.02 and the cost consumed per ton of coal is 0.01 when the transportation mode is switched at each site. The method routine described above is performed to produce the results shown in fig. 5.
from the analysis of fig. 5, we can easily find that there are 3 lines from beijing to nanjing,
One is Beijing- > Tianjin- > Jinan- > Nanjing, and the whole is a railway, the time consumption is 6, and the cost is as follows: 6000
One is Beijing- > Shanghai- > Nanjing, which is also a railway, consumes 5 times and costs: 10300
One is beijing- > shanghai- > nanjing, which is a railway for Shanghai- > Shanghai, a waterway for Shanghai- > Nanjing, and the time consumption is 6, and the cost is 4001 (the time consumption is the time number on the line plus the time consumption for converting the transportation mode is 3+100 + 0.02+ 1-6, and the cost is ton per ton plus the cost for converting the transportation mode is 100 + 30+100 + 0.01+100 + 10-4001).
therefore, the customer can select according to the requirement and realize the reservation of the distance through the automatic interaction between the platforms, and the overall transportation efficiency is improved.
The above are merely embodiments of the present invention, which are described in detail and with particularity, and therefore should not be construed as limiting the scope of the invention. It should be noted that, for those skilled in the art, various changes and modifications can be made without departing from the spirit of the present invention, and these changes and modifications are within the scope of the present invention.
Claims (5)
1. A multimodal transport system comprising:
The input interface is used for receiving the customer requirement information, and comprises the type, the quantity, the shipment starting time, the arrival time, the shipment starting point S and the destination D of the goods to be transported;
a virtual network state graph storage unit, configured to establish a virtual network state graph G ═ V, E, W according to the customer demand information, where a transportation mode set V ═ { ViW |1 ≦ i ≦ n,1 ≦ W } represents a set of all transportation modes that the goods can select at a node i, i represents a number of the node, n represents a total number of the nodes, W represents a number of the transportation modes, W represents a total number of the transportation modes, and an edge set E { (ViW, VjW) (ViL, VjK) |1 ≦ i < j ≦ n,1 ≦ W ≠ L ≠ K ≦ W } represents a set of edges that the goods can transport between the node i and the node j, where (ViW, VjW) represents a transport arc and (ViL, VjK) represents a conversion arc, where each edge has a different weight, respectively, and the weight represents a transport time or a transport cost required by the edge;
A Dijkstra algorithm operation module, configured to calculate, by using a Dijkstra algorithm, a route with the shortest transportation time and a route with the lowest transportation cost from the departure point S to the destination D in the virtual network state diagram G ═ (V, E, W);
a DFS algorithm operation module, configured to calculate, using a DFS algorithm, all reachable paths from the departure point S to the destination D in the virtual network state diagram G ═ V, E, W;
The output interface outputs the failure information of the transportation scheme calculation when no reachable path exists; outputting a transportation plan to a customer when an reachable path exists, wherein the transportation plan comprises all the reachable paths, the path with the shortest transportation time and the path with the lowest transportation cost;
the system comprises a preset interface, a plurality of logistics platforms and a plurality of control modules, wherein the preset interface is connected with the plurality of logistics platforms and is used for receiving a transportation scheme selected by a customer, respectively reserving the transport distance of a corresponding time period at the logistics platform corresponding to each side in sequence according to a set of sides contained in the transportation scheme, and outputting reservation success information when the transport distances corresponding to all sides are reserved successfully; and when any one of the preset distances fails, removing the edge corresponding to the distance, and triggering the virtual network state diagram storage unit, the Dijkstra algorithm operation module, the DFS algorithm operation module and the output interface to calculate or interact again according to the removed information.
2. The multimodal transportation scheme computing system of claim 1, further comprising a manual interface for synchronously pushing the transportation scheme calculation failure information and the customer requirement information to a manual for manual intervention triggered by the transportation scheme calculation failure information outputted by the output interface.
3. The computing system of multimodal transportation scheme as claimed in claims 1 and 2, wherein the Dijkstra algorithm operation module comprises the following sub-modules to calculate the shortest transportation time path and the lowest transportation cost path from the origin point S to the destination D in the virtual network state diagram G ═ (V, E, W) by using Dijkstra algorithm:
the Dijkstra operation initialization submodule is used for establishing an array distTo, and storing the weight of each node in the virtual network state diagram G ═ V, E and W to the edge of the start point S in the array distTo; establishing an index priority queue pq, and storing each node and the minimum weight of the node to the edge of the origin point S in the index priority queue pq;
A weight updating submodule, configured to calculate, starting from the origin point S, weights of edges from each adjacent node T adjacent to the origin point S, and store the weights in the array distTo and in the index priority queue pq;
a weight comparison submodule, configured to update the weight stored in the submodule according to the weight, and perform the following steps in sequence from each adjacent node T: respectively calculating the weight of an intermediate node O adjacent to the adjacent node T to the origin point S as distTo (S- > O), respectively calculating the weight of the adjacent node T to the origin point S as distTo (T- > O), comparing the distTo (S- > O) with the distTo (T- > O) according to the weight of the edge of the adjacent node T to the intermediate node O, and updating the weight value of the edge from the intermediate node O to the origin point S in the array distTo and the index priority queue pq as distTo (T- > O) if the distTo (S- > O) is larger, so as to ensure that the shortest path from the O point to the S point exists in the array distTo and pq queues;
And the Dijkstra operation output submodule is used for outputting the shortest transportation time path from the starting point S to the destination D and the lowest transportation cost path according to the node sequence stored after the last updating in the array distTo after all the adjacent nodes T are traversed by each submodule.
4. The computing system of multimodal transportation scheme as claimed in claims 1-3, wherein the DFS algorithm operation module comprises the following sub-modules to calculate all reachable paths from the origin S to the destination D in the virtual net state diagram G ═ (V, E, W) using DFS algorithm:
the DFS operation initialization submodule is used for emptying a stack vertex, and sequentially storing each node contained in a path with the shortest transportation time or the lowest transportation cost from an origin S to a destination D in the stack vertex; emptying another stack line, and sequentially storing each side contained in a path with the shortest transportation time or a path with the lowest transportation cost from the starting point S to the destination D in the stack line; emptying another queue list for storing all reachable paths;
a first path searching submodule, configured to sequentially determine, starting from the starting point S, whether the node exists in the stack vertex, and if so, skip to step 405; if not, the node is pressed into the stack vertex, then a node T adjacent to the node is searched, whether the searched node T is the destination D or not is judged, if the searched node T is the destination D, the edge between the searched node T and the node is pressed into the stack line, then all the nodes are sequentially taken out from the stack vertex, the path formed by the nodes is a reachable path from the starting point S to the destination D, and the reachable path is stored in the queue list; if the destination D is not the destination D, pushing the found node T into the stack vertex, and pushing an edge between the found node T and the node into the stack line;
A second path searching submodule, configured to repeat the step 402 from the found node T until a node at the end in the path is traversed, and perform a pop operation on the stack vertex and the stack line respectively;
Traversing the submodule, and repeating the step 403 until all nodes in the virtual network state diagram G ═ V, E, W are traversed;
And the DFS operation output submodule is used for sequentially outputting all reachable paths from the starting point S to the destination D from the queue list.
5. The computing system of the multimodal transportation scheme as claimed in claims 1 to 4, further comprising a Mongolian line optimization unit, which is connected to the Dijkstra algorithm operation module, the DFS algorithm operation module, and the output interface, and preferentially calculates and outputs each corresponding node and edge in the Mongolian line during the operation process.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111062531A (en) * | 2019-12-13 | 2020-04-24 | 上海中通吉网络技术有限公司 | Method and device for generating express trunk transportation scheme |
| CN111639887A (en) * | 2020-04-13 | 2020-09-08 | 中国铁道科学研究院集团有限公司电子计算技术研究所 | Multi-type joint transport processing method, system and node based on alliance chain |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120226624A1 (en) * | 2011-03-04 | 2012-09-06 | Byung Jun Song | Optimization system of smart logistics network |
| CN103425753A (en) * | 2013-07-24 | 2013-12-04 | 浙江大学 | Method for searching for heuristic shortest path based on direction optimization |
| US20160048802A1 (en) * | 2014-08-13 | 2016-02-18 | Tianyu Luwang | Transportation planning for a regional logistics network |
| CN105809402A (en) * | 2016-03-11 | 2016-07-27 | 惠龙易通国际物流股份有限公司 | Freight information processing method and system based on BFS algorithm |
| CN105825296A (en) * | 2016-03-11 | 2016-08-03 | 惠龙易通国际物流股份有限公司 | Dijkstra-algorithm-based freight information processing method and system |
| CN106503789A (en) * | 2016-11-08 | 2017-03-15 | 西安电子科技大学宁波信息技术研究院 | Loop-free shortest path searching method based on Di Jiesitela and minimax ant colony |
| CN109858688A (en) * | 2019-01-18 | 2019-06-07 | 东南大学 | A kind of Container Intermodal Transportation hub location method |
-
2019
- 2019-09-11 CN CN201910856893.2A patent/CN110544067B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120226624A1 (en) * | 2011-03-04 | 2012-09-06 | Byung Jun Song | Optimization system of smart logistics network |
| CN103425753A (en) * | 2013-07-24 | 2013-12-04 | 浙江大学 | Method for searching for heuristic shortest path based on direction optimization |
| US20160048802A1 (en) * | 2014-08-13 | 2016-02-18 | Tianyu Luwang | Transportation planning for a regional logistics network |
| CN105809402A (en) * | 2016-03-11 | 2016-07-27 | 惠龙易通国际物流股份有限公司 | Freight information processing method and system based on BFS algorithm |
| CN105825296A (en) * | 2016-03-11 | 2016-08-03 | 惠龙易通国际物流股份有限公司 | Dijkstra-algorithm-based freight information processing method and system |
| CN106503789A (en) * | 2016-11-08 | 2017-03-15 | 西安电子科技大学宁波信息技术研究院 | Loop-free shortest path searching method based on Di Jiesitela and minimax ant colony |
| CN109858688A (en) * | 2019-01-18 | 2019-06-07 | 东南大学 | A kind of Container Intermodal Transportation hub location method |
Non-Patent Citations (2)
| Title |
|---|
| 吴鹏等: "基于dijkstra和深度优先搜索的进路搜索算法研究", 《交通运输工程与信息学报》 * |
| 康文雄等: "节点约束型最短路径的分层dijkstra算法", 《华南理工大学学报（自然科学版）》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111062531A (en) * | 2019-12-13 | 2020-04-24 | 上海中通吉网络技术有限公司 | Method and device for generating express trunk transportation scheme |
| CN111062531B (en) * | 2019-12-13 | 2021-08-27 | 上海中通吉网络技术有限公司 | Method and device for generating express trunk transportation scheme |
| CN111639887A (en) * | 2020-04-13 | 2020-09-08 | 中国铁道科学研究院集团有限公司电子计算技术研究所 | Multi-type joint transport processing method, system and node based on alliance chain |
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