CN112270438A - Many-to-many path optimization method under dynamic road network environment - Google Patents
Many-to-many path optimization method under dynamic road network environment Download PDFInfo
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Abstract
A many-to-many path optimization method under a dynamic road network environment. Belonging to the field of computer algorithm and management optimization. The method aims to solve the scientific and practical problems that the theoretical optimal path under multiple starting points and multiple end points can be obtained only through one off-line calculation process under the given dynamic road network environment. The method realizes the organic combination of the route searching process and the road network changing process by implanting the road network environment changing model. Meanwhile, the road network accessibility changes constantly along with the dynamic change of the road network environment, and the method effectively reduces the risk of detour by introducing the waiting behavior before the inaccessible node or link. In addition, in the primary calculation process of the method, all the starting points are simultaneously subjected to path optimization, and the corresponding relation between the starting points and the end points is determined by backtracking of the search path which reaches the end point at first, so that the optimality and timeliness of the calculation result are guaranteed. The method can be used for solving the problem of many-to-many path optimization under a real physical network or an abstract virtual network.
Description
The technical field is as follows:
the invention provides a many-to-many path optimization method under a dynamic road network environment, and belongs to the field of computer algorithm and management optimization.
Background art:
the path optimization problem widely exists in real life, and no matter map navigation or material distribution, in order to improve the transportation efficiency, a specific path optimization method is often applied. The most classical path optimization problem is a pair of path optimization problems under a static road network environment, that is, a path planning problem from a single starting point to a single end point under the condition that the road network environment is not changed. However, in reality, there are cases where multiple start points and multiple end points occur simultaneously, for example, the problem of delivery of express from different express points to multiple residential points is that it is necessary to start from multiple start points and reach all end points in a static road network environment. Meanwhile, in order to improve the transportation efficiency, the principle of "near distribution" is usually adopted, that is, a starting point closer to an end point is manually assigned to complete the material distribution. However, considering that dynamic development of disasters such as typhoons, floods, and fires may affect accessibility of a road network environment, a dynamic path optimization method is required. Considering that a plurality of starting points and a plurality of end points may exist in a road network, such as the problem of emergency material distribution in a dynamic disaster environment, the method needs to transport materials from different emergency material storage points to a plurality of residential points, and thus, the method relates to a many-to-many path optimization method in the dynamic road network environment. The many-to-many path planning problem under the dynamic environment has strong application potential in the fields of disaster rescue, transportation and the like. This problem has the following three basic features: (1) the method comprises the steps that in the process of single path search, the road network environment is fixed as the road network environment at the current moment, the essence of the method is the solution of a static problem, and the path optimization problem of the dynamic road network environment is solved through repeated online calculation; (2) because a plurality of starting points and end points exist in a road network, the corresponding relation between the starting points and the end points is often specified in advance in the traditional method, and then a calculation mode of one-to-one problem iterative solution is adopted, so that the high requirement on the calculation capacity is met for large complex problems; (3) due to the dynamic change of the road network environment, the success rate of solving cannot be guaranteed, and the result superiority can be greatly reduced once the behaviors such as detour and the like occur. At present, various algorithms are applied to the problem of many-to-many path optimization in a dynamic road network environment. However, in general, the existing algorithm cannot obtain the theoretical optimal solution of the many-to-many path optimization problem in the dynamic environment through one-time calculation. The solving idea based on the traditional method is as follows: based on the road network environment at the current moment, the problem of many-to-many path optimization under the dynamic road network environment is solved by utilizing iterative solution of a one-to-one problem. That is, the conventional method adopts an online optimization calculation method, considers a single-start point and single-end point problem during single online optimization, calculates an optimal path from a current position to a target position based on a current road network environment, repeatedly performs the above process to obtain an optimal path of a one-to-one problem, and iteratively solves the optimal path of a many-to-many problem. This has the following disadvantages: (1) in a single iteration, starting points and end points need to be specified in advance and correspond to one another, namely fixed starting point and end point pairs, so that real-time adjustment cannot be performed according to a dynamic environment, and once a certain starting point or a peripheral road network of the certain starting point or the peripheral road network is trapped in a trouble due to disaster, all path planning corresponding to the certain starting point will fail; (2) the traditional method can not obtain the theoretical optimal path of many-to-many problems in a dynamic environment through one-time calculation, so that the calculation efficiency and the timeliness of the result are greatly reduced when complex problems are faced, and once one path is planned and trapped in a predicament in single iterative calculation, the execution of subsequent related steps is influenced; (3) most of the traditional methods are static path optimization processes aiming at the road network situation at the current time, and path optimization needs to be carried out again when the road network changes. This not only results in a low efficiency of path optimization, but also has a possibility of detour or turn-back for the dynamic road network problem under a disaster environment, which easily causes the actual path to be inconsistent with the theoretical optimal path. In summary, the conventional method has two fundamental disadvantages as follows: (1) the traditional method cannot obtain the theoretical optimal path of a many-to-many path optimization problem in a dynamic environment through one off-line calculation process, the road network environment in single path optimization is static and unchanged, and the theoretical optimality cannot be guaranteed as a result; (2) the traditional method artificially stipulates the optimal corresponding relation of the starting point and the end point, cannot adapt to the dynamic change of a road network, cannot ensure the theoretical optimality and even can cause the failure of path optimization. The invention patent 'a coevolution path optimization method under a dynamic road network environment' (patent number: 201610021915X) provides a path optimization method from a single starting point to a single terminal point under the dynamic road network environment, which can not effectively solve the dynamic pairing problem between multiple starting points and multiple terminal points in the multiple-to-multiple path optimization problem under the dynamic road network environment; in addition, even if the corresponding relationship between multiple starting points and multiple end points is specified in advance, the invention patent 'method for optimizing a coevolution path in a dynamic road network environment' needs to repeatedly run for many times to find out the optimal path between each starting point and end point pair, so that the calculation efficiency is not high.
The invention relates to a many-to-many path optimization method in a dynamic environment, which aims to fundamentally solve the problems. When the method of the invention is used for optimizing the path once, the synchronous searching process of all the starting points is realized under the environment of a dynamic road network, and the corresponding relation of the starting points and the end points is completely determined by backtracking the path searching result, thereby ensuring the optimality of the result. Meanwhile, the method of the invention synchronously carries out the change process of the road network in the process of searching the path, thereby effectively solving the defects of the traditional method.
The invention content is as follows:
the invention aims to provide a many-to-many path optimization method under a dynamic road network environment. The method solves the scientific and practical problem that the theoretical optimal path under multiple starting points and multiple end points can be obtained through one calculation process under the given dynamic road network environment.
In order to solve the above problems, the present invention is implemented by the following scheme: in the path optimization calculation process, the road network environment is given by a given dynamic road network environment model and is constantly changed, so all unreachable nodes and links can be properly avoided in the path search process, and the result optimality is ensured; in the primary path optimization calculation process, all starting points can synchronously perform the path searching process until the optimal paths reaching all end points are obtained, so that the calculation timeliness of the result is ensured; the corresponding relation of the starting point and the end point obtained by the method is determined by backtracking the path search result, so that the optimality of the method is ensured; because the route searching process is carried out simultaneously with the road network changing process, the method allows waiting behaviors before nodes or links are temporarily impassable.
The calculation process of the method mainly comprises the following steps: (1) determining a dynamic road network environment description model; (2) initializing a road network and an original starting point, setting the original starting point to be in an active state, and determining a path search speed and unit search time; (3) if the terminal is not reached, going to the step (4), otherwise, going to the step (7); (4) updating the time parameter, and determining the road network environment after the next unit search time according to the dynamic barrier change rule; at the same time, inaccessible nodes and links are allowed to exist; (5) based on the current road network environment, if any node has an inaccessible link connected with the node or the node is inaccessible, the node is set to be in a waiting state; meanwhile, the node for restoring the accessibility is set to be in an active state; (6) calculating all positions which can be reached after one unit of search time starts from the current starting point based on the current road network environment, setting the new positions as new starting points if the new positions are reached before and the number of times of arrival is not more than the number of the original starting points, otherwise, not considering; at the same time, allowing wait behavior before inaccessible nodes and links; then returning to the step (3); (7) and for each terminal, finding out the corresponding starting point and the optimal path through backtracking.
It should be noted that: in the path optimization calculation process of the method, a dynamic road network environment description model is introduced in the step (4), and the organic combination of the path search process and the road network environment change process is realized, so that the road network is not static and is changed in real time in the path search process; since a node or link that is temporarily inaccessible is generated during a dynamic change of the road network environment, the step (5) sets the node or link that is temporarily inaccessible to a standby state and sets the node that recovers accessibility to an active state; searching only the nodes and links in the active state in the step (6), and continuing to perform path optimization after the nodes or links in the waiting state recover the accessibility, which is a waiting behavior in the path searching process, because the temporary waiting can avoid the influence of dynamic obstacles, thereby ensuring the superiority of the result; in step (6), the newly arrived position is considered to be set as a new starting point only if the number of times of arrival of the newly arrived position is not more than the number of the original starting points by convention, and the purpose is to avoid the risk of detour. The steps (4), (5) and (6) are unique to the present invention.
The many-to-many path optimization method under the dynamic road network environment provided by the invention has the following advantages: (1) according to the method, the dynamic road network environment description model is introduced, the motion path optimization and the dynamic road network environment are cooperatively carried out, the theoretical optimal path of many-to-many problems is obtained through one-time off-line calculation, the calculated amount is greatly reduced, the real-time performance of the calculated result is ensured, and meanwhile, the whole dynamic evolution process of the road network environment is considered at the initial time of path optimization, and the theoretical optimality of the calculated result is ensured; (2) the method breaks through the manually agreed starting point and end point corresponding relation of the traditional method, and finds the corresponding starting point for each end point through backtracking, so that the most appropriate corresponding relation can be selected according to the dynamic change of the road network environment, and the superiority of the result is ensured; (3) the method effectively avoids the risk of detour by introducing the waiting behavior, aims at the problem that the local road network environment cannot be reached temporarily due to the influence of dynamic disasters in the problems of typhoons, fires or floods and the like, can continuously carry out path optimization after the disasters cross the border through the waiting behavior, and effectively improves the transportation efficiency.
Description of the drawings:
the attached drawings show a schematic diagram of the many-to-many path optimization method under the dynamic road network environment, which is disclosed by the invention:
FIG. 1: the method mainly comprises the steps of a dynamic road network environment.
FIG. 2: and (3) a schematic diagram of a solving process of the many-to-many path optimization method under the dynamic road network environment.
The specific implementation mode is as follows:
the following will further explain, in combination with the accompanying drawings, a search mode adopted by the method for optimizing many-to-many paths in a dynamic road network environment to solve the scientific and practical problems that the theoretical optimal path under multiple starting points and multiple end points can be obtained only through one calculation process in a predictable dynamic road network environment.
FIG. 1 shows the main computational steps involved in the method of the present invention;
(step one): determining a dynamic road network environment description model;
(step two): initializing a road network and an original starting point, setting the original starting point to be in an active state, and determining a path search speed and unit search time;
(step three): if the terminal is not reached, go to (step four), otherwise, go to (step seven);
(step four): updating the time parameter, and determining the road network environment after the next unit search time according to the dynamic barrier change rule; meanwhile, the road network accessibility is changed due to the change of the road network environment, so that inaccessible nodes and links are allowed to exist;
(step five): based on the current road network environment, if any node has an inaccessible link connected with the node or the node is inaccessible, the node is set to be in a waiting state, meanwhile, the node with the newly recovered accessibility is set to be in an active state, and the dynamic evolution of the road network environment is reflected as the transition of the accessibility in the road network through the state setting of the node and the link;
(step six): calculating all positions which can be reached by advancing one unit of search time along the current road network environment at a given road strength search speed based on the current starting point, setting the positions as new starting points if the new positions are reached before and the number of the reached positions is not more than the number of the original starting points, otherwise, not considering the new positions because the new positions are obtained based on the previous starting points because the detour behavior is generated if the number of the reached positions is more than the number of the original starting points; meanwhile, if an unreachable node or link is encountered in the path searching process, the node or link waits before the node or link until the accessibility is recovered, namely, a waiting action; then returning to the step three;
(step seven): and for each terminal point, finding out a corresponding starting point and an optimal path through backtracking, and ending the path optimization process.
Fig. 2 shows an example of solving the many-to-many path optimization problem in a dynamic road network environment by one calculation according to the method of the present invention. In the solving process shown in fig. 2, the future 3 times are considered, and it should be noted that the road network environment changes from time to time in the path searching process at these three times.
In the solution example shown in fig. 2, nodes 1 and 12 are the original starting points and nodes 6 and 7 are the end points. At time t, since links (1, 5) and (12, 8) are inaccessible, the current time can only reach nodes 2 and 11, and is set as the starting point of the next time path search. Since links (2, 6) and (7, 11) are inaccessible due to changes in the road network environment, nodes 3 and 10 can only be reached starting from nodes 2 and 11 at time t +1, respectively, and are set as the path search starting points at the next time. At the same time, since the links (1, 5) restore accessibility, the node 5 is reached from the node 1, and the node 5 is also set as the next-time path search starting point. Starting from nodes 3 and 10 at time t +2, respectively, the end points 7 and 6 are reached, while node 5 does not search for a new node since none of the links (5, 9) and (5, 6) connected to node 5 are reachable. The optimal paths under the dynamic road network environment can be obtained by backtracking from the end points 6 and 7, and are respectively as follows: 12 → 11 → 10 → 6 and 1 → 2 → 3 → 7. the path optimization process is finished because the end points are all reached, it should be noted that the corresponding relationship between the start point and the end point of the current result is 12 → 6 and 1 → 7.
If the above problem is solved using the conventional method, the calculation result will be quite different from the method of the present invention. The traditional method adopts a one-to-one iterative calculation mode, such as path optimization of the end point 6 is considered firstly. Since the end point 6 is closest to the start point 1, the start point 1 is assigned to complete the path search for the end point 6. It should be noted that, in the conventional method, the road network is static and unchanged in a path optimization calculation process, that is, the conventional method calculates an optimal path from the current position to the target position according to the current time, advances by one unit of search time to reach the position, and continuously iterates until the end point is reached. Therefore, according to the case shown in fig. 2, at time t, since the link (1, 5) is inaccessible, the optimal path from the starting point 1 to the end point 6 at the current time is 1 → 2 → 6, and proceeds to the node 2. At time t +1, since the link (2, 6) is inaccessible, the optimal paths at the current time are 2 → 1 → 5 → 6 and 2 → 3 → 7 → 6, and it is clear that the optimality of the result cannot be guaranteed regardless of which path is selected. Similarly, at time t, since the link (12, 8) is inaccessible, the optimal path from the starting point 12 to the end point 7 at the current time is 12 → 11 → 7, and proceeds to the node 11. By analogy, the path of the conventional method is 12 → 11 → 10 → 6 → 7. It can be seen that, on the premise of ensuring safe arrival at the end point, if the starting points are all started at the same time, the travel time of the calculation result of the traditional method is increased by 33% compared with the method of the invention. In consideration of time consumption of calculation, compared with the traditional method, the method has better result superiority and timeliness.
Claims (7)
1. A many-to-many path optimization method under dynamic road network environment is used for realizing organic combination of a dynamic road network change process and a path search process under a predictable dynamic road network environment, and obtaining optimal paths under multiple starting points and multiple end points through one off-line calculation, and is characterized in that: in the path searching process, the road network environment is not static and is in dynamic change all the time; the road network environment has multiple starting points and multiple end points, and the total time consumption for pursuing transportation is shortest on the premise of ensuring that all the end points are reached; because of the existence of multiple starting points and multiple end points in the road network environment, the optimal corresponding relation between the starting points and the end points changes along with the dynamic change of the road network environment, and therefore, the optimal corresponding relation is determined by backtracking the path search result which reaches the end point firstly: in the process of one-time calculation, all the starting points start to search paths at the same time, so that the theoretical optimal path of many-to-many problems can be obtained through one-time off-line calculation; because the accessibility of nodes and links changes constantly due to the dynamic change of the road network environment, the waiting behavior before the nodes and links which are temporarily impassable is considered in the path optimization process: the shortest transportation time of a path optimization result under a dynamic road network environment and the calculated timeliness are considered; the method comprises the following steps: (1) determining a dynamic road network environment description model; (2) initializing a road network and all original starting points, setting all the original starting points to be in an active state, and determining the path search speed and unit search time; (3) if the terminal is not reached, going to the step (4), otherwise, going to the step (7); (4) updating the time parameter, and determining the road network environment after the next unit search time according to the dynamic barrier change rule; meanwhile, the road network accessibility is changed due to the change of the road network environment, so that inaccessible nodes and links are allowed to exist; (5) based on the current road network environment, if any node has an unreachable link connected with the node or the node is unreachable, the node is set to be in a waiting state; meanwhile, the nodes for restoring the accessibility are set to be in an active state, and the dynamic evolution of the road network environment is reflected as the transition of the accessibility in the road network through the state setting of the nodes and the links; (6) calculating all positions which can be reached after a unit of search time from a current starting point based on the current road network environment, setting the new positions as new starting points if the new positions are reached before and the number of times of arrival is not more than the number of the original starting points, otherwise, not considering the new positions because the new positions are obtained based on the previous starting points because the detour behavior is generated if the number of times of arrival of one position is more than the number of the original starting points; meanwhile, if an unreachable node or link is encountered in the path searching process, the node or link waits before the node or link until the accessibility is recovered, namely, a waiting action; then returning to the step (3); (7) and for each terminal, finding out the corresponding starting point and the optimal path through backtracking.
2. The dynamic road network environment many-to-many path optimization method as claimed in claim 1, wherein: the optimal correspondence between the starting point and the end point in the road network is determined by backtracking the search result of the path which reaches the end point first.
3. The dynamic road network environment many-to-many path optimization method as claimed in claim 1, wherein: if the rule describing the change of the road network environment is fixed and known, the method can solve the problem only through one-time off-line optimization calculation without repeatedly performing real-time on-line optimization calculation.
4. The dynamic road network environment many-to-many path optimization method as claimed in claim 1, wherein: if the rule describing the change of the road network environment also changes along with time, the method only needs to perform one-time path optimization calculation at each time when the change rule of the road network environment changes.
5. The dynamic road network environment many-to-many path optimization method as claimed in claim 1, wherein: the method is applied to the path optimization problem in the real physical network.
6. The dynamic road network environment many-to-many path optimization method as claimed in claim 1, wherein: the method is applied to the path optimization problem in the abstract virtual network.
7. The dynamic road network environment many-to-many path optimization method as claimed in claim 1, wherein: the method described is implemented using a variety of suitable hardware computing devices and software programming techniques.
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Application publication date: 20210126 |