CN114580741A - Path planning method, device and equipment based on multi-traffic network - Google Patents
Path planning method, device and equipment based on multi-traffic network Download PDFInfo
- Publication number
- CN114580741A CN114580741A CN202210208270.6A CN202210208270A CN114580741A CN 114580741 A CN114580741 A CN 114580741A CN 202210208270 A CN202210208270 A CN 202210208270A CN 114580741 A CN114580741 A CN 114580741A
- Authority
- CN
- China
- Prior art keywords
- transportation
- time
- route
- traffic network
- minimum
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Theoretical Computer Science (AREA)
- Operations Research (AREA)
- Data Mining & Analysis (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Quality & Reliability (AREA)
- General Business, Economics & Management (AREA)
- Pure & Applied Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Mathematical Physics (AREA)
- Mathematical Optimization (AREA)
- Marketing (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Development Economics (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- General Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Software Systems (AREA)
- Databases & Information Systems (AREA)
- Evolutionary Biology (AREA)
- Algebra (AREA)
- Probability & Statistics with Applications (AREA)
- Game Theory and Decision Science (AREA)
- Navigation (AREA)
Abstract
The application relates to a path planning method and device based on a multi-traffic network, computer equipment and a storage medium. The method comprises the following steps: selecting a traffic network, a transportation mode and a transportation batch according to the area of the materials to be transported and the starting point of transporting the materials; setting a constraint condition of a minimum balance time transportation route under a multi-traffic network by utilizing a traffic network, a transportation mode and a transportation batch; setting the sum of the total route time of material transportation, the transfer time of the material transportation and the departure time of the last transportation batch as an objective function of the transportation route with the minimum trade-off time under the multi-traffic network; establishing a solving model of the minimum balance time transportation route under the multi-traffic network according to the constraint condition and the objective function; solving the solving model through an improved Dijkstra algorithm to obtain a transportation route with minimum balance time, and then calculating the total actual transportation time. By adopting the method, the rescue efficiency can be improved.
Description
Technical Field
The present invention relates to the technical field of path planning, and in particular, to a method, an apparatus, a computer device, and a storage medium for path planning based on a multi-traffic network.
Background
Emergency logistics refers to a special logistics activity for emergency protection (including acquisition, transportation, warehousing, loading and unloading, transportation, packaging, distribution, recovery, information processing, and the like) of the requirements of materials, personnel, funds, and the like in order to deal with emergencies (such as natural disasters, public safety incidents, military conflicts, and the like). In case of emergency, such as earthquake, there is a need for rescue personnel and rescue supplies. It is important how to transport rescue personnel and supplies to the designated location as soon as possible.
In the traditional method, the shortest path in the transportation process is solved most frequently, but in the background of emergency physics, the simple and visual scheme has poor practicability, and on one hand, the traditional method can not realize the shortest path search for switching different traffic modes and can not actually recommend an optimal route; on the other hand, in response to public safety events such as sudden natural disasters, the aim of 'armed forces and high speed' is considered, the shortest distance is not always considered primarily, the needs of rescue workers and material transportation under emergency conditions cannot be met, and the rescue efficiency is low.
Disclosure of Invention
In view of the above, it is necessary to provide a method, an apparatus, a computer device and a storage medium for path planning based on a multi-traffic network, which can improve rescue efficiency.
A path planning method based on a multi-traffic network comprises the following steps:
acquiring an area to be transported and a starting point of transporting materials;
selecting a traffic network, a transportation mode and a transportation batch according to the area of the materials to be transported and the starting point of transporting the materials; the traffic network comprises a node set and a directed edge set; the node set comprises a starting node, a terminating node, a vertex and a transfer node;
setting a constraint condition of a minimum balance time transportation route under a multi-traffic network by utilizing a traffic network, a transportation mode and a transportation batch; setting the sum of the total route time of material transportation, the transfer time of the material transportation and the departure time of the last transportation batch as an objective function of the transportation route with the minimum trade-off time under the multi-traffic network;
establishing a solving model of the minimum balance time transportation route under the multi-traffic network according to the constraint condition and the objective function;
solving the solving model by an improved Dijkstra algorithm to obtain a minimum balance time transportation route considering the road passing time, the traffic capacity and the transportation batch number;
and calculating the transportation time of the material area to be transported according to the minimum balanced time transportation route to obtain the actual total transportation time.
In one embodiment, the constraint condition for setting the minimum trade-off time transportation route under the multi-transportation network by using the transportation network, the transportation mode and the transportation batch comprises the following steps:
constructing a first constraint condition that a transportation route with minimum trade-off time is a connected physical route from a starting node to a terminating node according to the transportation network, the transportation mode and the transportation batch;
constructing a second constraint condition that the quantity of the transport batches per day does not exceed the single-day traffic capacity, the starting single-day loading capacity, the ending single-day loading capacity and the single-day loading and unloading capacity of a transfer node of each road section of the selected path according to the transportation network, the transport mode and the transport batches;
and constructing a third constraint condition for enabling connectivity of the transit node and the selected road section according to the transportation network, the transportation mode and the transportation batch.
In one embodiment, before setting the sum of the total route time of the material transportation, the transfer time of the material transportation and the departure time of the last transportation batch as the objective function of the minimum weighted time transportation route under the multi-transportation network, the method further comprises the following steps: calculating the transportation time of each transportation route in the directed edge set to obtain the total time of material transportation; determining a starting node and a terminating node from the node set according to the area to be transported and the starting point of the transported material; and constructing the transfer time of material transportation according to the loading time of the starting node, the unloading time of the ending node and the loading and unloading time of the transfer node.
In one embodiment, the step of setting the sum of the total route time of the material transportation, the transfer time of the material transportation and the departure time of the last transportation batch as an objective function of the minimum weighted time transportation route under the multi-transportation network comprises the following steps:
setting the sum of the total route time of material transportation, the transfer time of the material transportation and the departure time of the last transportation batch as an objective function of the transportation route with the minimum balance time under the multi-traffic network
min(T+Q+W)
Where T represents the total route time, Q represents the transit time, and W represents the departure time of the last transport lot.
In one embodiment, solving the solution model by using a modified Dijkstra algorithm to obtain a minimum weighted time transportation route includes:
setting a first set and a second set in a multi-traffic network; the first set includes starting points in the multi-traffic network; the second set comprises other vertexes except the starting point in the traffic network and the weighted time from the starting point to each vertex;
traversing the vertex with the minimum weighted time in the multi-traffic network from the second set, and adding the vertex with the minimum weighted time to the first set;
updating the weighted time from the starting point to each vertex in the second set according to the vertex with the minimum weighted time;
judging all vertexes in the first set according to a preset judgment rule, and traversing all vertexes in the updated second set according to a judgment result until an end point is obtained;
and calculating the passing time, the passing capacity and the number of the transportation batches from the starting point to the end point to obtain the transportation route with the minimum balance time.
In one embodiment, the determining all vertices in the first set according to a preset determination rule, and traversing all vertices in the second set according to a determination result until an end point is obtained includes: judging whether all vertexes of the first set contain vertexes with the vertex sequence numbers not smaller than the starting point number, and if so, taking the vertex as an end point; if not, all the vertexes in the second set are traversed until an end point is obtained.
In one embodiment, the calculating the transportation time of the material area to be transported according to the minimum time balancing transportation route to obtain the actual total transportation time includes:
and calculating the transportation time of the material area to be transported according to the minimum balance time transportation route, the transfer time, the total batch number, the starting point loading time, the starting point loading capacity, the end point unloading time and the end point unloading capacity to obtain the actual transportation total time.
A path planning apparatus based on a multi-traffic network, the apparatus comprising:
the system comprises an initialization module, a data processing module and a data processing module, wherein the initialization module is used for acquiring an area of materials to be transported and a starting point of the transported materials; selecting a traffic network, a transportation mode and a transportation batch according to the area of the materials to be transported and the starting point of transporting the materials; the traffic network comprises a node set and a directed edge set; the node set comprises a starting node, a terminating node, a vertex and a transfer node;
the solving model building module is used for setting the constraint conditions of the minimum balance time transportation route under the multi-traffic network by utilizing the traffic network, the transportation mode and the transportation batch; setting the sum of the total route time of material transportation, the transfer time of the material transportation and the departure time of the last transportation batch as an objective function of the transportation route with the minimum trade-off time under the multi-traffic network; establishing a solving model of the transportation route with the minimum balance time under the multi-traffic network according to the constraint conditions and the objective function;
the solving model solving module is used for solving the solving model through an improved Dijkstra algorithm to obtain a minimum balance time transportation route considering the road passing time, the traffic capacity and the transportation batch number;
and the actual total transportation time calculating module is used for calculating the transportation time of the material area to be transported according to the minimum balanced time transportation route to obtain the actual total transportation time.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring an area to be transported and a starting point of transporting materials;
selecting a traffic network, a transportation mode and a transportation batch according to the area of the materials to be transported and the starting point of transporting the materials; the traffic network comprises a node set and a directed edge set; the node set comprises a starting node, a terminating node, a vertex and a transfer node;
setting a constraint condition of a minimum balance time transportation route under a multi-traffic network by utilizing a traffic network, a transportation mode and a transportation batch; setting the sum of the total route time of material transportation, the transfer time of the material transportation and the departure time of the last transportation batch as an objective function of the transportation route with the minimum trade-off time under the multi-traffic network;
establishing a solving model of the transportation route with the minimum balance time under the multi-traffic network according to the constraint conditions and the objective function;
solving the solving model by an improved Dijkstra algorithm to obtain a minimum balance time transportation route considering the road passing time, the traffic capacity and the transportation batch number;
and calculating the transportation time of the material area to be transported according to the minimum balanced time transportation route to obtain the actual total transportation time.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring an area to be transported and a starting point for transporting materials;
selecting a traffic network, a transportation mode and a transportation batch according to the area of the materials to be transported and the starting point of transporting the materials; the traffic network comprises a node set and a directed edge set; the node set comprises a starting node, a terminating node, a vertex and a transfer node;
setting a constraint condition of a minimum balance time transportation route under a multi-traffic network by utilizing a traffic network, a transportation mode and a transportation batch; setting the sum of the total route time of material transportation, the transfer time of the material transportation and the departure time of the last transportation batch as an objective function of the transportation route with the minimum trade-off time under the multi-traffic network;
establishing a solving model of the transportation route with the minimum balance time under the multi-traffic network according to the constraint conditions and the objective function;
solving the solving model by an improved Dijkstra algorithm to obtain a minimum balance time transportation route considering the road passing time, the traffic capacity and the transportation batch number;
and calculating the transportation time of the material area to be transported according to the minimum balanced time transportation route to obtain the actual total transportation time.
According to the path planning method, the path planning device, the computer equipment and the storage medium based on the multi-traffic network, the constraint conditions of the minimum balance time transportation route under the multi-traffic network are set by utilizing the traffic network, the transportation mode and the transportation batch; setting the sum of total route time of material transportation, transfer time of material transportation and departure time of the last transportation batch as an objective function of the minimum balance time transportation route in the multi-traffic network, establishing a solving model of the minimum balance time transportation route in the multi-traffic network according to constraint conditions and the objective function, then improving a Dijkstra algorithm to solve the solving model of the minimum balance time transportation route in the multi-traffic network, calculating total time according to the obtained minimum balance time transportation route, establishing the minimum balance time transportation route solving model, solving the model by using the improved Dijkstra algorithm, carrying out rescue material transportation according to the obtained minimum balance time transportation route, and sending rescue materials to an area to be rescued in the shortest time, so that the rescue efficiency is improved.
Drawings
Fig. 1 is a schematic flow chart of a path planning method based on a multi-traffic network in an embodiment;
FIG. 2 is a block diagram illustrating a path planning apparatus based on a multi-traffic network according to an embodiment;
FIG. 3 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In one embodiment, as shown in fig. 1, a path planning method based on a multi-traffic network is provided, which includes the following steps:
102, acquiring an area to be transported with materials and a starting point for transporting the materials; and selecting a traffic network, a transportation mode and a transportation batch according to the area to be transported with the materials and the starting point of transporting the materials.
The traffic network comprises a node set and a directed edge set; the node set includes a start node, a stop node, a vertex, and a transit node. The traffic network comprises an aviation traffic network, a railway traffic network and a road traffic network; the transportation modes comprise airplanes, high-speed rails, trains, ships, automobiles and the like. The method comprises the steps of selecting a traffic network and a transportation mode according to the regional characteristics of materials to be transported, such as geographic environment, estimating the distance between a region and a starting point of the transported materials, estimating a primary transportation batch according to the traffic network and the transportation mode, setting constraint conditions of a minimum balanced time transportation route under a multi-traffic network according to the conditions, and obtaining the optimal time path estimation.
104, setting a constraint condition of a minimum balance time transportation route in a multi-traffic network by utilizing a traffic network, a transportation mode and a transportation batch; and setting the sum of the total route time of the material transportation, the transfer time of the material transportation and the departure time of the last transportation batch as an objective function of the transportation route with the minimum trade-off time under the multi-traffic network.
And step 106, solving the solved model through an improved Dijkstra algorithm to obtain a minimum balance time transportation route considering the road passing time, the traffic capacity and the transportation batch number.
The Dijkstra algorithm is proposed by Ducktra, a Netherlands computer scientist, and is described as three steps of initializing, marking p and modifying t, and is a shortest path algorithm from one vertex to the rest of the vertices, and the shortest path problem in the weighted graph is solved. The method improves the solving model by utilizing Dijkstra algorithm, namely different traffic networks are combined into an algorithm operable traffic network, and when the different traffic networks are combined into one traffic network, the starting point s needs to be split into s1,s2,s3. And sequentially judging which traffic network node the starting point s is, starting searching from the traffic network with the highest priority existing in the starting point s, and recording as I. Introducing two sets S1And S2，S1The effect of (1) is to record the vertices for which the minimum trade-off time has been found, and S2Then it is the vertex for which the record has not yet found the minimum trade-off time. At the beginning S1Containing only the starting point sI，S2Involving removal of sIOther vertex than S, and2the time C of the middle vertex is "start point sIWeighted time to the top point ". From S2Traverse the vertex with the minimum trade-off time and add the vertex to S1The preparation method comprises the following steps of (1) performing; updating S2The corresponding route of each vertex in the map. And then the process is circulated until the end point e is traversedjNot less than I, andcomparison S2Middle end point ejMinimum value of all times C ≧ I. Finally, the minimum time balancing transportation route is obtained, and then the actual total transportation time is recalculated.
And 108, calculating the transportation time of the material area to be transported according to the minimum balanced time transportation route to obtain the actual total transportation time.
Rescue goods and materials are transported by using the minimum balanced time transportation route, the rescue goods and materials can be sent to the area to be rescued in the shortest time, and the rescue efficiency is improved.
In the path planning method based on the multi-traffic network, the constraint condition of the minimum balance time transportation route in the multi-traffic network is set by utilizing the traffic network, the transportation mode and the transportation batch; setting the sum of total route time of material transportation, transfer time of material transportation and departure time of the last transportation batch as an objective function of the minimum balance time transportation route in the multi-traffic network, establishing a solving model of the minimum balance time transportation route in the multi-traffic network according to constraint conditions and the objective function, then improving a Dijkstra algorithm to solve the solving model of the minimum balance time transportation route in the multi-traffic network, calculating total time according to the obtained minimum balance time transportation route, establishing the minimum balance time transportation route solving model, solving the model by using the improved Dijkstra algorithm, carrying out rescue material transportation according to the obtained minimum balance time transportation route, and sending rescue materials to an area to be rescued in the shortest time, so that the rescue efficiency is improved.
In one embodiment, before setting the sum of the total route time of the material transportation, the transfer time of the material transportation and the departure time of the last transportation batch as the objective function of the minimum weighted time transportation route under the multi-transportation network, the method further comprises the following steps: calculating the transportation time of each transportation route in the directed edge set to obtain the total time of material transportation; determining a starting node and a terminating node from the node set according to the area to be transported and the starting point of transporting materials; and constructing the transfer time of material transportation according to the loading time of the starting node, the unloading time of the ending node and the loading and unloading time of the transfer node.
In one embodiment, the step of setting the sum of the total route time of the material transportation, the transfer time of the material transportation and the departure time of the last transportation batch as an objective function of the minimum weighted time transportation route under the multi-transportation network comprises the following steps:
setting the sum of the total route time of material transportation, the transfer time of the material transportation and the departure time of the last transportation batch as an objective function of the transportation route with the minimum balance time under the multi-traffic network
min(T+Q+W)
Wherein T represents the total route time, Q represents the transit time, and W represents the departure time of the last transport lot.
In the problem of the minimum time balancing transportation route under the multi-traffic network, the total transportation time is adopted as an evaluation index of the searched route. According to the decision variable, when the corresponding road section (i, j) under the transportation mode f is selected, the corresponding transportation time is
Considering transit time in general, the objective function can be expressed as
min(T+Q+W) (1)
Where T is the total route time, i.e., the sum of transit times for each route, expressed as
And Q is transit elapsed time including start point load time, end point unload time and transit node load and unload time, expressed as
W is the departure time of the last transport batch, and if u is less than or equal to y, W is 0; if u>y, then
In one embodiment, the constraint condition for setting the minimum trade-off time transportation route under the multi-transportation network by using the transportation network, the transportation mode and the transportation batch comprises the following steps:
constructing a first constraint condition that a transportation route with minimum trade-off time is a connected physical route from a starting node to a terminating node according to the transportation network, the transportation mode and the transportation batch;
constructing a second constraint condition that the quantity of the transport batches per day does not exceed the single-day traffic capacity, the starting single-day loading capacity, the ending single-day loading capacity and the single-day loading and unloading capacity of a transfer node of each road section of the selected path according to the transportation network, the transport mode and the transport batches;
and constructing a third constraint condition for enabling connectivity of the transit node and the selected road section according to the transportation network, the transportation mode and the transportation batch.
In the constraint conditions, the equations (4), (5) and (6) ensure that the selected optimal time path forms a first constraint condition for a communicated physical route from the starting node s to the ending node q, and the equations (7), (8), (9) and (10) ensure that the daily transport batch number does not exceed the single-day traffic capacity of each road section of the selected path, the starting point single-day loading capacity, the ending point single-day loading capacity and the single-day loading and unloading capacity of a transfer node (if a transfer condition occurs, the transportation mode of the node is changed) to form a second constraint condition. Formula (11) ensures from mode of transport f1Turn f2Only once. Equations (12), (13) and (14) ensure that connectivity of transit nodes and selected segments constitutes a third constraint. Wherein N ═ V, E represents the traffic network, V represents the set of nodes, E represents the set of directed edges, i represents the node number i ∈ V, directed edges (i, j) ∈ E if and only if there is at least one transportation mode from i to j, F represents the set of transportation modes, F ∈ F represents the transportation mode number, N represents the transportation mode number, and E represents the set of transportation modesfIndicating that the transport mode f corresponds to a transport subnetwork, s indicates a start node, q indicates a termination node,
representing the single-day loading capacity of node i in mode f of transport,
representing the single-day loading capacity of node i in mode f of transport,
representing the single day traffic capacity of the section (i, j) in the mode of transport f,
represents the transport time of the section (i, j) in the transport mode f, u represents the total number of transport lots, tlRepresents node load time, tnIndicating the node offload time. The decision variables of the minimum trade-off time transport route solution model under the multi-traffic network are shown in table 1.
TABLE 1 decision variable parameter notation and definition
In one embodiment, solving the solution model by using a modified Dijkstra algorithm to obtain a minimum weighted time transportation route includes:
setting a first set and a second set in a multi-traffic network; the first set includes starting points in the multi-traffic network; the second set comprises other vertexes except the starting point in the traffic network and the weighted time from the starting point to each vertex;
traversing the vertex with the minimum weighted time in the multi-traffic network from the second set, and adding the vertex with the minimum weighted time to the first set;
updating the weighted time from the starting point to each vertex in the second set according to the vertex with the minimum weighted time;
judging all vertexes in the first set according to a preset judgment rule, and traversing all vertexes in the updated second set according to a judgment result until an end point is obtained;
and calculating the passing time, the passing capacity and the number of the transportation batches from the starting point to the end point to obtain the transportation route with the minimum balance time.
In one embodiment, the determining all vertices in the first set according to a preset determination rule, and traversing all vertices in the second set according to a determination result until an end point is obtained includes: judging whether all vertexes of the first set contain vertexes with the vertex sequence numbers not smaller than the starting point number, and if so, taking the vertex as an end point; if not, all the vertexes in the second set are traversed until an end point is obtained.
Multiple traffic network G ═ G1,G2,G3In which G is1Representing an air traffic network, G2Representing a railway traffic network, G3Representing a road traffic network, solving the minimum trade-off time transportation route under the multi-traffic network based on the improved Dijkstra algorithm according to the following steps:
step 1.1 is initialized, the transfer time is set to be Q, and the total batch number is set to be R.
Step 1.2 starts with i '1 and ends with i' 3, and determines whether or not the starting point s is Gi′If the node in (1) is satisfied, the node stops with the value of I, wherein I' represents the serial number of the starting point of the traffic network, and I represents the number of the starting points.
Step 1.3 set first set and second set, first set S1Containing only the starting point sIA second set S2Involving removal of sIThe other vertices outside. S2The time of the middle vertex is "start point sIWeighted time "to the top point, if S2Middle vertex and origin sIIf not adjacent, the trade-off time is ∞, i.e. S1＝{sI}，S2(except for s)IOther vertices than the vertices },
marking of origin sIThe symbol s, the other points are not labeled. (Note that, in order not to forcibly select the transportation mode at the start of transportation, a separation starting point s is setIThe trade-off time to other split starts with sequence numbers greater than I is 0, while the split start sITrade-off time to other starting points of splitting with sequence numbers less than I ∞)
Step 1.4 from S2And selecting a vertex k with the minimum weighted time in the multi-traffic network G, and recording a traffic network sequence number q.
Step 1.5 Add vertex k to S1Simultaneously from S2With vertex k removed, i.e. Ck＝min(Csj) In that respect Wherein C issj＝tsj+R/capsj,tsjActual transit time, c ap, for the section from marker s to point jsjFor the daily traffic capacity of the road section from point s to point j, R/capsjAs a time weight measure (indicating that if the value is smaller, the cap is the smallersjThe larger the probability of selecting the road segment).
Step 1.6 update S2From each vertex to the start point sIThe trade-off time. Therefore, update S2The distance of the middle vertex is determined in the previous step so that k is the vertex for obtaining the shortest path, and the distances of other vertices can be updated by k. If the possibility exists that the path length from the previous vertex to the next vertex v through the k vertex is shorter than the path length from the previous vertex to the next vertex v directly, the shortest distance needs to be updated again, and the distance minimization is taken as the judgment standard. Namely, it is
If S2If the middle vertex is a split vertex of the vertex k and the sequence number is greater than q, then
Otherwise
Step 1.7 marks vertex k as index s.
Step 1.8 judgment S1Whether there is a split vertex e including an end pointj(j.gtoreq.I). If yes, go to step 1.9; if not, go to step 1.4.
Step 1.9 finding the peak e of the reached splitjMinimum trade-off time of (j ≧ I)
Outputting the minimum trade-off time transportation route and recalculating the actual total transportation time.
In one embodiment, the calculating the transportation time of the material area to be transported according to the minimum time balancing transportation route to obtain the actual total transportation time includes:
and calculating the transportation time of the material area to be transported according to the minimum balance time transportation route, the transfer time, the total batch number, the starting point loading time, the starting point loading capacity, the end point unloading time and the end point unloading capacity to obtain the actual transportation total time.
The specific steps of calculating the transportation time of the material area to be transported according to the minimum balance time transportation route, the transfer time, the total batch number, the starting point loading time, the starting point loading capacity, the ending point unloading time and the ending point unloading capacity to obtain the actual transportation total time are as follows:
step 2.1 initializes. According to the minimum balance time, the transportation route p, the transit time Q, the total batch number R and the loading time R of the starting pointlStarting point loading capacity clEnd point unload time rulAnd end point unload capability cul。
Step 2.2 set total transport time to T, let T ═ rl+cl。
Step 2.3, splitting the optimal route p, and setting the optimal route p to be composed of n edges, wherein the transportation time of each edge is ti(i-1, 2, …, n) and a daily maximum capacity of capi(i＝1,2,…,n)。
Step 2.4, let i equal to 1, set the maximum daily traffic capacity of route p as y, and let y equal to min (c)l,cul)。
Step 2.5 let T' ═ T + Ti。
Step 2.6 to determine if y>capiIf yes, let y be capi。
Step 2.7 judges whether or not a transfer occurs. If yes, T ═ T' + Q, and let y ═ min { y, daily capacity of transit nodes, daily capacity of shipping nodes }.
Step 2.8 to judge whether i is<n is used as the index. If yes, i is equal to i +1 and go to step 2.5; if not, then
Wherein
Meaning that the round-down calculation takes several days to transport all batches.
And 2.9, outputting the actual total transportation time T'.
The technical effects of the present invention will be described in the following specific embodiments, where it is known that the city route information table (table 2) includes transportation modes, city at the start of a road segment, city at the end of a road segment, name of a road segment, time consumed for transportation of a road segment, and maximum daily transportation batch number of a road segment, and the city node information table (table 2) includes daily loading and unloading capacities of a railway and daily loading and unloading capacities of a road of a city node (it should be noted that data adopted in the embodiments is not real data, and each road segment in table 2 is a one-way traffic road segment).
TABLE 2 City route information Table
TABLE 3 City node information Table
Taking the emergency assistance task of the medical team as an example, the emergency transportation task is carried out on the medical care personnel by adopting the road network information basic data (mainly used for the topology structure of the traffic network and the traffic capacity of the line). According to related requirements, the transportation mode is unlimited, the medical staff transportation of the same medical team is specified to have continuity, and a specific emergency transportation task list is shown in the table 4 (only valid information is given).
TABLE 4 Emergency transportation task List
| Name (R) | Traffic mode | Number of batches | Starting city | To a city | Type of person | Whether to carry materials or not |
| Medical team 1 | Railway/highway | 6 | City A | City H | Medical staff | Is that |
| Medical team 2 | Railway/highway | 10 | City A | City J | Medical staff | Is that |
The method for planning the transportation route with the minimum balance time under the multi-traffic network respectively designs the recommended delivery routes of the two medical teams, and the influence of the time of each road section, the transportation capacity, the loading and unloading capacity of the transportation point and the transportation time on the completion time of the emergency transportation task is comprehensively considered in the optimization process. Here, it is assumed that the loading time and the unloading time are both 2 hours, and the results are shown in table 5.
TABLE 5 medical team haul route and total task time
The following description is required:
for the medical team 1, the optimized transportation route has the maximum transportation batch number of 8 batches per day, the single-pass line takes 21.35h (without considering the loading and unloading), the transfer loading and unloading time is 2+ 2-4 h, the start and end loading and unloading time is 2+ 2-4 h, and the total time is
For the medical team 2, the optimized transportation route has the maximum daily transportation batch number of 9 batches, the one-way route consumes 42.41h (no loading and unloading is considered), the transportation is generated by the non-transportation mode conversion, the loading and unloading time 2+2 at the starting point and the ending point is 4h, and the total time is 9 batches
It should be understood that, although the steps in the flowchart of fig. 1 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in fig. 1 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 2, there is provided a path planning apparatus based on a multi-traffic network, including: an initialization module 202, a solution model construction module 204, a solution model solution module 206 and an actual total transportation time calculation module, wherein:
the initialization module 202 is used for acquiring an area where goods and materials are to be transported and a starting point of transporting the goods and materials; selecting a traffic network, a transportation mode and a transportation batch according to the area of the materials to be transported and the starting point of transporting the materials; the traffic network comprises a node set and a directed edge set; the node set comprises a starting node, a terminating node, a vertex and a transfer node;
the solution model construction module 204 is used for setting the constraint conditions of the minimum balance time transportation route in the multi-traffic network by utilizing the traffic network, the transportation mode and the transportation batch; setting the sum of the total route time of material transportation, the transfer time of the material transportation and the departure time of the last transportation batch as an objective function of the transportation route with the minimum trade-off time under the multi-traffic network;
a solving model solving module 206, configured to solve the solving model through Dijkstra algorithm to obtain a minimum trade-off time transportation route in which the road passing time, the traffic capacity, and the number of transportation batches are considered;
and the actual total transportation time calculating module 208 is configured to calculate transportation time of the to-be-transported material area according to the minimum trade-off time transportation route, so as to obtain actual total transportation time.
In one embodiment, the solution model building module 204 is further configured to set constraints of the minimum weighted time transportation route in the multi-transportation network by using the transportation network, the transportation mode and the transportation batch, including:
constructing a first constraint condition that a transportation route with minimum trade-off time is a connected physical route from a starting node to a terminating node according to the transportation network, the transportation mode and the transportation batch;
constructing a second constraint condition that the quantity of the transport batches per day does not exceed the single-day traffic capacity, the starting single-day loading capacity, the ending single-day loading capacity and the single-day loading and unloading capacity of a transfer node of each road section of the selected path according to the transportation network, the transport mode and the transport batches;
and constructing a third constraint condition for enabling connectivity of the transit node and the selected road section according to the transportation network, the transportation mode and the transportation batch.
In one embodiment, before the solving the sum of the total route time of the material transportation, the transit time of the material transportation, and the departure time of the last transportation batch is set as the objective function of the transportation route with the minimum trade-off time in the multi-transportation network, the solving the model building module 204 further includes: calculating the transportation time of each transportation route in the directed edge set to obtain the total time of material transportation; determining a starting node and a terminating node from the node set according to the area to be transported and the starting point of the transported material; and constructing the transfer time of material transportation according to the loading time of the starting node, the unloading time of the ending node and the loading and unloading time of the transfer node.
In one embodiment, the solution model building module 204 is further configured to set a sum of a total route time of the material transportation, a transfer time of the material transportation, and a departure time of the last transportation lot as an objective function of the minimum trade-off time transportation route in the multi-transportation network, including:
setting the sum of the total route time of material transportation, the transfer time of material transportation and the departure time of the last transportation batch as an objective function of the transportation route with the minimum balance time under the multi-traffic network as
min(T+Q+W)
Wherein T represents the total route time, Q represents the transit time, and W represents the departure time of the last transport lot.
In one embodiment, the solution model solving module 206 is further configured to solve the solution model by using a modified Dijkstra algorithm to obtain a minimum weighted time transportation route, including:
setting a first set and a second set in a multi-traffic network; the first set includes starting points in the multi-traffic network; the second set comprises other vertexes except the starting point in the traffic network and the weighted time from the starting point to each vertex;
traversing the vertex with the minimum weighted time in the multi-traffic network from the second set, and adding the vertex with the minimum weighted time to the first set;
updating the weighted time from the starting point to each vertex in the second set according to the vertex with the minimum weighted time;
judging all vertexes in the first set according to a preset judgment rule, and traversing all vertexes in the updated second set according to a judgment result until an end point is obtained;
and calculating the passing time, the passing capacity and the number of the transportation batches from the starting point to the end point to obtain the transportation route with the minimum balance time.
In one embodiment, the solving the model solving module 206 is further configured to determine all vertices in the first set according to a preset determination rule, and traverse all vertices in the second set according to the determination result until an end point is obtained, including: judging whether all vertexes of the first set contain vertexes with the vertex sequence numbers not smaller than the starting point number, and if so, taking the vertex as an end point; if not, all the vertexes in the second set are traversed until an end point is obtained.
In one embodiment, the actual total transportation time calculating module 208 is further configured to calculate the transportation time of the to-be-transported material area according to the minimum trade-off time transportation route, so as to obtain the actual total transportation time, including:
and calculating the transportation time of the material area to be transported according to the minimum balance time transportation route, the transfer time, the total batch number, the starting point loading time, the starting point loading capacity, the end point unloading time and the end point unloading capacity to obtain the actual transportation total time.
For specific definition of the path planning device based on the multi-traffic network, refer to the above definition of the path planning method based on the multi-traffic network, and are not described herein again. All or part of the modules in the path planning device based on the multi-traffic network can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 3. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a path planning method based on a multi-traffic network. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 3 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In an embodiment, a computer device is provided, comprising a memory storing a computer program and a processor implementing the steps of the method in the above embodiments when the processor executes the computer program.
In an embodiment, a computer storage medium is provided, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method in the above-mentioned embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is specific and detailed, but not to be understood as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A path planning method based on a multi-traffic network is characterized by comprising the following steps:
acquiring an area to be transported and a starting point of transporting materials;
selecting a traffic network, a transportation mode and a transportation batch according to the area of the materials to be transported and the starting point of transporting the materials; the traffic network comprises a node set and a directed edge set; the node set comprises a starting node, a terminating node, a vertex and a transfer node;
setting a constraint condition of a minimum trade-off time transportation route under a multi-traffic network by utilizing the traffic network, the transportation mode and the transportation batch; setting the sum of the total route time of material transportation, the transfer time of material transportation and the departure time of the last transportation batch as an objective function of the transportation route with the minimum balance time under the multi-traffic network;
establishing a solving model of the minimum balance time transportation route under the multi-traffic network according to the constraint condition and the objective function;
solving the solving model through an improved Dijkstra algorithm to obtain a minimum balance time transportation route considering the road passing time, the traffic capacity and the number of transportation batches;
and calculating the transportation time of the material area to be transported according to the minimum balanced time transportation route to obtain the actual total transportation time.
2. The method of claim 1, wherein setting constraints for a minimum trade-off time transportation route under a multi-transportation network by using the transportation network, the transportation mode and the transportation batch comprises:
constructing a first constraint condition which enables a minimum time balancing transportation route to be a connected physical route from a starting node to a terminating node by utilizing the transportation network, the transportation mode and the transportation batch;
constructing a second constraint condition that the quantity of the transport batches per day does not exceed the single-day traffic capacity, the starting single-day loading capacity, the ending single-day loading capacity and the single-day loading and unloading capacity of a transfer node of each road section of the selected path by using the traffic network, the transport mode and the transport batches;
and constructing a third constraint condition for enabling the connectivity of the transit node and the selected road section by using the transportation network, the transportation mode and the transportation batch.
3. The method of claim 2, wherein before setting the sum of the total route time for the material transport, the transit time for the material transport, and the departure time for the last transport batch as the objective function of the minimum trade-off time transport route under the multi-transportation network, further comprising:
calculating the transportation time of each transportation route in the directed edge set to obtain the total time of material transportation;
determining a starting node and a terminating node from the node set according to the area to be transported and the starting point of transporting the materials; and constructing the transfer time of material transportation according to the loading time of the starting node, the unloading time of the ending node and the loading and unloading time of the transfer node.
4. The method of claim 3, wherein setting the sum of the total route time for material transport, the transit time for material transport, and the departure time for the last transport batch as an objective function of the minimum trade-off time transport route under the multi-transportation network comprises:
setting the sum of the total route time of material transportation, the transfer time of the material transportation and the departure time of the last transportation batch as an objective function of the transportation route with the minimum balance time under the multi-traffic network
min(T+Q+W)
Where T represents the total route time, Q represents the diversion time, and W represents the departure time of the last transport lot.
5. The method of claim 4, wherein solving the solution model using a modified Dijkstra algorithm resulting in a minimum trade-off time haul route comprises:
setting a first set and a second set in the multi-traffic network; the first set includes a starting point in the multi-traffic network; the second set comprises other vertexes except the starting point in the traffic network and weighted time from the starting point to each vertex;
traversing the vertex with the minimum weighted time in the multi-traffic network from the second set, and adding the vertex with the minimum weighted time to the first set;
updating the weighted time from the starting point to each vertex in the second set according to the vertex with the minimum weighted time;
judging all vertexes in the first set according to a preset judgment rule, and traversing all vertexes in the updated second set according to a judgment result until an end point is obtained;
and calculating the passing time, the passing capacity and the number of the transportation batches from the starting point to the end point to obtain the transportation route with the minimum balance time.
6. The method of claim 5, wherein determining all vertices in the first set according to a preset determination rule, and traversing all vertices in the second set according to a determination result until an end point is obtained comprises:
judging whether all vertexes of the first set contain vertexes with the vertex sequence numbers not smaller than the starting point number, and if so, taking the vertex as an end point; and if not, traversing all the vertexes in the second set until an end point is obtained.
7. The method of claim 6, wherein calculating the transportation time of the material area to be transported according to the minimum trade-off time transportation route to obtain the actual total transportation time comprises:
and calculating the transportation time of the material area to be transported according to the minimum balance time transportation route, the transit time, the total batch number, the starting point loading time, the starting point loading capacity, the end point unloading time and the end point unloading capacity to obtain the actual transportation total time.
8. A path planning device based on multi-traffic network, characterized in that the device comprises:
the system comprises an initialization module, a data processing module and a data processing module, wherein the initialization module is used for acquiring an area of materials to be transported and a starting point of the transported materials; selecting a traffic network, a transportation mode and a transportation batch according to the area of the materials to be transported and the starting point of transporting the materials; the traffic network comprises a node set and a directed edge set; the node set comprises a starting node, a terminating node, a vertex and a transfer node;
the solving model building module is used for setting the constraint conditions of the minimum balance time transportation route under the multi-traffic network by utilizing the traffic network, the transportation mode and the transportation batch; setting the sum of the total route time of material transportation, the transfer time of the material transportation and the departure time of the last transportation batch as an objective function of the transportation route with the minimum trade-off time under the multi-traffic network; according to the constraint conditions and the objective function, a solving model of the minimum weighted time transportation route under the multi-traffic network is established
The solving model solving module is used for solving the solving model through an improved Dijkstra algorithm to obtain a minimum balance time transportation route considering the road passing time, the traffic capacity and the transportation batch number;
and the actual total transportation time calculating module is used for calculating the transportation time of the material area to be transported according to the minimum balanced time transportation route to obtain the actual total transportation time.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210208270.6A CN114580741A (en) | 2022-03-03 | 2022-03-03 | Path planning method, device and equipment based on multi-traffic network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210208270.6A CN114580741A (en) | 2022-03-03 | 2022-03-03 | Path planning method, device and equipment based on multi-traffic network |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114580741A true CN114580741A (en) | 2022-06-03 |
Family
ID=81775614
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210208270.6A Pending CN114580741A (en) | 2022-03-03 | 2022-03-03 | Path planning method, device and equipment based on multi-traffic network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114580741A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115994635A (en) * | 2023-03-23 | 2023-04-21 | 广东鉴面智能科技有限公司 | Belt optimal discharging transportation path detection method, system and medium |
-
2022
- 2022-03-03 CN CN202210208270.6A patent/CN114580741A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115994635A (en) * | 2023-03-23 | 2023-04-21 | 广东鉴面智能科技有限公司 | Belt optimal discharging transportation path detection method, system and medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Hong et al. | A range-restricted recharging station coverage model for drone delivery service planning | |
| Masson et al. | A branch-and-cut-and-price approach for the pickup and delivery problem with shuttle routes | |
| Dhamala et al. | A critical survey on the network optimization algorithms for evacuation planning problems | |
| Newton et al. | Design of school bus routes by computer | |
| Toumazis et al. | Worst-case conditional value-at-risk minimization for hazardous materials transportation | |
| Witt | Trip-based public transit routing | |
| Tarantilis et al. | A flexible adaptive memory-based algorithm for real-life transportation operations: Two case studies from dairy and construction sector | |
| US8682583B2 (en) | Route search system | |
| US20160148136A1 (en) | Multiple sequential planning and allocation of time-divisible resources | |
| Awad-Núñez et al. | How should the sustainability of the location of dry ports be measured? A proposed methodology using Bayesian networks and multi-criteria decision analysis | |
| US20160363455A1 (en) | Route search apparatus, route search method and computer-readable storage medium storing program | |
| CN110222912B (en) | Railway travel route planning method and device based on time dependence model | |
| CN108663047A (en) | A kind of cross-layer paths planning method | |
| CN114580741A (en) | Path planning method, device and equipment based on multi-traffic network | |
| Bae et al. | Finding a risk-constrained shortest path for an unmanned combat vehicle | |
| JP6999519B2 (en) | Transport capacity adjustment device, transport capacity adjustment system and transport capacity adjustment method | |
| CN110895749B (en) | Positioning-path planning method for emergency logistics | |
| US20230274216A1 (en) | Delivery plan generation apparatus, delivery plan generation method, and program | |
| Berhan | Stochastic vehicle routing problems with simultaneous pickup and delivery services | |
| El-Gharably et al. | Optimization using simulation of the vehicle routing problem | |
| CN115081666A (en) | Method, device, computer equipment and storage medium for determining transportation path | |
| JP6794762B2 (en) | Route management device, route management method and program | |
| Murakami | A generalized model and a heuristic algorithm for the large-scale covering tour problem | |
| Ghaderi et al. | A new multimodal multi-criteria route planning model by integrating a fuzzy-AHP weighting method and a simulated annealing algorithm | |
| Bahrehdar et al. | A decision support system for urban journey planning in multimodal public transit network |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |