CN109816315B - Path planning method, path planning device, electronic equipment and readable storage medium - Google Patents
Path planning method, path planning device, electronic equipment and readable storage medium Download PDFInfo
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Abstract
The embodiment of the disclosure discloses a path planning method, a path planning device, electronic equipment and a readable storage medium, wherein the method comprises the following steps: obtaining possible paths for a delivery resource to reach one or more target sites from a start site, and determining accumulated costs of the possible paths, wherein the possible paths are divided into one or more sub-paths by the start site and the one or more target sites, the accumulated costs comprise the sum of the costs of the sub-paths, and the costs of the sub-paths are at least related to any one or more of the transit time, the path length and the delivery resource preference of the sub-paths; and taking the possible path with the lowest accumulated cost as a planning path of the distribution resource. The technical scheme can determine the planned path based on the accumulated cost of the whole path, thereby avoiding the limitation of a greedy algorithm on path planning, ensuring that the path planning result is more reliable, effectively reducing the logistics cost and improving the distribution efficiency.
Description
Technical Field
The disclosure relates to the field of logistics, in particular to a path planning method, a path planning device, electronic equipment and a readable storage medium.
Background
The path planning is an important link in logistics distribution, and the distribution path is reasonably planned, so that the logistics cost can be effectively reduced, and the distribution efficiency is improved. Although there has been some research in the prior art for the problem of route planning for logistics distribution, most of these studies are based on greedy algorithms. When path planning is performed based on a greedy algorithm, usually, a sub-path with low cost is selected as far as possible with the current position as a starting point, and then the next sub-path is planned with the end point of the sub-path as a next starting point, that is, only one sub-path is determined at a time. Thus, even though the cost of each sub-path is currently the smallest, the overall path of multiple sub-paths is not necessarily the lowest cost accumulated in all possible paths. Thus, a new method for path planning is needed.
Disclosure of Invention
To solve the problems in the related art, embodiments of the present disclosure provide a path planning method, apparatus, electronic device, and readable storage medium.
In a first aspect, an embodiment of the present disclosure provides a path planning method, which is characterized in that the method includes:
Obtaining possible paths for a delivery resource to reach one or more target sites from a start site, and determining accumulated costs of the possible paths, wherein the possible paths are divided into one or more sub-paths by the start site and the one or more target sites, the accumulated costs comprise the sum of the costs of the sub-paths, and the costs of the sub-paths are at least related to any one or more of the transit time, the path length and the delivery resource preference of the sub-paths;
and taking the possible path with the lowest accumulated cost as a planning path of the distribution resource.
With reference to the first aspect, in a first implementation manner of the first aspect, the embodiments of the present disclosure:
the one or more target locations correspond to pick-up locations and pick-up locations of the one or more orders;
in the possible paths, the pick-up location of any order is located before the pick-up location of the order.
With reference to the first aspect, in a second implementation manner of the first aspect, in a case that the delivery resource receives a new order when delivering the new order along the planned path, a first target location reached after receiving the new order or a location where the new order is received is taken as an updated starting location.
With reference to the first aspect, in a third implementation manner of the first aspect, the embodiment of the disclosure further includes:
and obtaining the cost of the sub-path by carrying out weighted summation on any one or more of the transit time, the path length and the distribution resource preference of the sub-path.
With reference to the third implementation manner of the first aspect, in a fourth implementation manner of the first aspect, the embodiment of the present disclosure further includes, before determining the cost of the sub-path, determining a corresponding weight of the any one or more of the transit time, the path length, and the distribution resource preference by:
initializing the corresponding weight;
acquiring respective actual initial positions and one or more actual target positions of a plurality of actual historical paths;
for each actual historical path, acquiring possible paths from the actual starting place to the one or more actual target places, dividing the possible paths into one or more sub-paths by the actual starting place and the one or more actual target places, calculating the accumulated cost of the possible paths by using any one or more of the transit time, the path length and the distribution resource preference of each sub-path of the possible paths and the corresponding weight of each sub-path, and selecting the possible path with the lowest accumulated cost as a planning path of the actual historical path;
And adjusting the corresponding weight to maximize the overall contact ratio of the planned path and the corresponding actual historical path.
With reference to the fourth implementation manner of the first aspect, in a fifth implementation manner of the first aspect, the embodiment of the disclosure calculates the overall overlap ratio by any one of the following ways:
calculating the number of sub-paths with the same level in the corresponding planning path and the actual historical paths as a first number for each actual historical path, summing the corresponding first number of the actual historical paths, and dividing the sum by the sum of the sub-paths of the actual historical paths to obtain the overall contact ratio; or alternatively
And calculating the number of sub-paths in the same order in the corresponding planning path and the actual historical path for each actual historical path, dividing the number by the total number of sub-paths in the actual historical path to obtain the coincidence ratio of the corresponding planning path of the actual historical path, adding the coincidence ratios of the corresponding planning paths of the actual historical paths, and dividing the coincidence ratio by the total number of the historical paths to obtain the overall coincidence ratio.
With reference to the first aspect, in a sixth implementation manner of the embodiment of the present disclosure, the preference of the distribution resource includes a residence time and/or a walking distance of the distribution resource at the start location and/or the target location.
With reference to the first aspect, in a seventh implementation manner of the first aspect, the embodiments of the present disclosure further include determining the one or more target sites according to a pick-up site and/or a pick-up site of the pending order of the delivery resource and a processing status of the pending order of the delivery resource.
In a second aspect, an embodiment of the present disclosure provides a path planning apparatus, including:
a computing module configured to obtain a possible path for a delivery resource from a start location to one or more target locations, determine a cumulative cost for the possible path, wherein the possible path is divided by the start location and the one or more target locations into one or more sub-paths, the cumulative cost comprising a sum of costs for each of the sub-paths, the costs of the sub-paths being related to at least any one or more of a transit time, a path length, and the delivery resource preference of the sub-paths;
and the determining module is configured to take the possible path with the lowest accumulated cost as a planning path of the distribution resource.
In a third aspect, an embodiment of the disclosure provides an electronic device, including a memory and a processor, where the memory is configured to store one or more computer instructions, and the one or more computer instructions are executed by the processor to implement the steps of:
Obtaining possible paths for a delivery resource to reach one or more target sites from a start site, and determining accumulated costs of the possible paths, wherein the possible paths are divided into one or more sub-paths by the start site and the one or more target sites, the accumulated costs comprise the sum of the costs of the sub-paths, and the costs of the sub-paths are at least related to any one or more of the transit time, the path length and the delivery resource preference of the sub-paths;
and taking the possible path with the lowest accumulated cost as a planning path of the distribution resource.
With reference to the third aspect, in a first implementation manner of the third aspect, an embodiment of the disclosure:
the one or more target locations correspond to pick-up locations and pick-up locations of the one or more orders;
in the possible paths, the pick-up location of any order is located before the pick-up location of the order.
With reference to the third aspect, in a second implementation manner of the third aspect, in a case that the delivery resource receives a new order when delivering the new order along the planned path, the position where the new order is received or the first target location reached after the new order is received is taken as the updated starting location.
With reference to the third aspect, in a third implementation manner of the third aspect, the one or more computer instructions are further executed by the processor to implement the following steps:
and obtaining the cost of the sub-path by carrying out weighted summation on any one or more of the transit time, the path length and the distribution resource preference of the sub-path.
With reference to a third implementation manner of the third aspect, in a fourth implementation manner of the third aspect, the one or more computer instructions are further executed by the processor to implement the following steps:
before determining the cost of the sub-path, determining the corresponding weights for the any one or more of the transit time, path length, and delivery resource preference by:
initializing the corresponding weight;
acquiring respective actual initial positions and one or more actual target positions of a plurality of actual historical paths;
for each actual historical path, acquiring possible paths from the actual starting place to the one or more actual target places, dividing the possible paths into one or more sub-paths by the actual starting place and the one or more actual target places, calculating the accumulated cost of the possible paths by using any one or more of the transit time, the path length and the distribution resource preference of each sub-path of the possible paths and the corresponding weight of each sub-path, and selecting the possible path with the lowest accumulated cost as a planning path of the actual historical path;
And adjusting the corresponding weight to maximize the overall contact ratio of the planned path and the corresponding actual historical path.
With reference to the fourth implementation manner of the third aspect, in a fifth implementation manner of the third aspect, the embodiment of the disclosure calculates the overall overlap ratio by any one of the following ways:
calculating the number of sub-paths with the same level in the corresponding planning path and the actual historical paths as a first number for each actual historical path, summing the corresponding first number of the actual historical paths, and dividing the sum by the sum of the sub-paths of the actual historical paths to obtain the overall contact ratio; or alternatively
And calculating the number of sub-paths in the same order in the corresponding planning path and the actual historical path for each actual historical path, dividing the number by the total number of sub-paths in the actual historical path to obtain the coincidence ratio of the corresponding planning path of the actual historical path, adding the coincidence ratios of the corresponding planning paths of the actual historical paths, and dividing the coincidence ratio by the total number of the historical paths to obtain the overall coincidence ratio.
With reference to the third aspect, in a sixth implementation manner of the third aspect, the distribution resource preference includes a residence time and/or a walking distance of the distribution resource at the start location and/or the target location.
With reference to the third aspect, in a seventh implementation manner of the third aspect, the one or more computer instructions are further executed by the processor to implement the following steps: the one or more target locations are determined based on the pick-up location and/or the pick-up location of the pending order for the delivery resource and the processing status of the pending order for the delivery resource.
In a fourth aspect, in an embodiment of the present disclosure, there is provided a readable storage medium having stored thereon computer instructions that, when executed by a processor, implement a method according to any one of the first aspect, the first implementation manner to the seventh implementation manner.
The technical scheme provided by the embodiment of the disclosure can comprise the following beneficial effects:
the technical scheme includes that the accumulated cost of possible paths from a starting place to one or more target places is determined, and then the possible path with the lowest accumulated cost is used as a planning path. The technical scheme is that the planning path is determined based on the accumulated cost of the whole path and is not limited by the cost of a single sub-path, so that the limitation of a greedy algorithm on path planning is avoided, the path planning result is more reliable, the logistics cost can be effectively reduced, and the distribution efficiency is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
Other features, objects and advantages of the present disclosure will become more apparent from the following detailed description of non-limiting embodiments, taken in conjunction with the accompanying drawings. In the drawings:
FIG. 1 shows a flow chart of a path planning method according to an embodiment of the present disclosure;
FIG. 2A shows a schematic diagram of a starting location and a plurality of target locations;
FIGS. 2B and 2C are schematic diagrams illustrating a path planning method based on a greedy algorithm and embodiments of the present disclosure, respectively;
FIG. 3 illustrates a schematic diagram of calculating the cumulative cost of possible paths according to an embodiment of the present disclosure;
FIG. 4 shows a flow chart of a path planning method according to another embodiment of the present disclosure;
FIG. 5 illustrates a flow chart of determining corresponding weights for any one or more of transit time, path length, delivery resource preferences, according to an embodiment of the present disclosure;
FIG. 6 shows a block diagram of a path planning apparatus according to an embodiment of the present disclosure;
FIG. 7 shows a block diagram of an electronic device according to an embodiment of the present disclosure;
fig. 8 shows a block diagram of a computer system suitable for use in implementing a path planning method according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. In addition, for the sake of clarity, portions irrelevant to description of the exemplary embodiments are omitted in the drawings.
In this disclosure, it is to be understood that terms such as "comprises" or "comprising," etc., are intended to indicate the presence of a tag, number, step, action, component, section or combination thereof disclosed in this specification, and are not intended to exclude the possibility that one or more other tags, numbers, steps, actions, components, sections or combinations thereof are present or added.
In addition, it should be noted that, without conflict, the embodiments of the present disclosure and the labels in the embodiments may be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
The technical scheme provided by the embodiment of the disclosure determines the accumulated cost of possible paths from a starting place to one or more target places, and takes the possible path with the lowest accumulated cost as a planning path. The technical scheme is that the planning path is determined based on the accumulated cost of the whole path and is not limited by the cost of a single sub-path, so that the limitation of a greedy algorithm on path planning is avoided, the result of path planning is more reliable, the logistics cost can be effectively reduced, and the distribution efficiency is improved.
Fig. 1 shows a flow chart of a path planning method according to an embodiment of the present disclosure.
As shown in fig. 1, the path planning method includes the following steps S101-S102:
in step S101, obtaining possible paths for a delivery resource to reach one or more target sites from a start site, determining a cumulative cost of the possible paths, wherein the possible paths are divided into one or more sub-paths by the start site and the one or more target sites, the cumulative cost including a sum of costs of each of the sub-paths, the costs of the sub-paths being related to at least any one or more of a transit time, a path length, and the delivery resource preference of the sub-paths;
in step S102, the possible path with the lowest cumulative cost is used as the planned path of the distribution resource.
In an alternative embodiment of the present disclosure, the delivery resource may be any one of a delivery person, an unmanned aerial vehicle, an unmanned vehicle, and a delivery robot, for example.
In an alternative embodiment of the present disclosure, the starting location may be, for example, the current location of the delivery resource, or may be the destination to which the delivery resource is going.
In an alternative embodiment of the present disclosure, the one or more target locations may be determined based on the pick-up location and/or pick-up location of the pending order of the delivery resource and the processing status of the pending order of the delivery resource. For example, the ship-to location of the picked and not-delivered order may be determined as the target location and/or the ship-to location and the ship-to location of the not-picked order may be determined as the target location.
In an alternative embodiment of the present disclosure, the one or more target locations correspond to pick-up locations and pick-up locations of one or more orders. In the possible paths, the pick-up location of any order is located before the pick-up location of the order. That is, the delivery resource needs to first pick up the relevant goods of the order at the pick-up location to complete the delivery of the order at the pick-up location.
An example of a path planning method according to one embodiment of the present disclosure is described below with reference to fig. 2A-2C.
Fig. 2A shows a schematic diagram of a starting location and a plurality of target locations. For example, the delivery resource obtains order 1 and order 2 at location O, where order 1 includes pick-up location A1 and pick-up location B1, order 2 includes pick-up location A2 and pick-up location B2, location O is the starting location, and locations A1, B1, A2, B2 are the destination locations.
Fig. 2B and 2C show schematic diagrams of a path planning method based on a greedy algorithm and an embodiment of the present disclosure, respectively, in which, for ease of understanding, the cost of a sub-path is calculated only from the straight-line distance between two end points of the sub-path in this example.
As shown in fig. 2B, according to the greedy algorithm, the linear distance from the location A1 to the location O is smaller than the linear distance from the location A2 to the location O, and the delivery resource is delivered to the target location A1 first for picking. Secondly, the distance from the place B1 to the place A1 is smaller than the distance from the place A2 to the place A1, and then the delivery resource firstly reaches the target place B1 to finish delivery of the order 1, and then sequentially goes to the target place A2 and the target place B2 to finish pickup and delivery of the order 2. Although this method can go to the target site with the shortest straight line distance each time, the sum of the straight line distances of the sub-paths is not necessarily the shortest in all possible paths as a whole, so that the logistics distribution efficiency is lower and the cost is higher.
As shown in fig. 2C, completing the delivery of order 1 and order 2 from site O includes the following six possible paths, according to an embodiment of the present disclosure:
possible path 1: firstly, taking goods from a place A1, then taking goods from a place A2, then delivering the goods from a place B1, and finally delivering the goods from a place B2;
possible path 2: firstly, taking goods from a place A1, then taking goods from a place A2, then delivering the goods from a place B2, and finally delivering the goods from a place B1;
possible path 3: firstly, taking goods from a place A1, then delivering the goods from a place B1, then taking the goods from a place A2, and finally delivering the goods from a place B2, namely the planned path shown in FIG. 4A;
possible path 4: firstly, taking goods from a place A2, then taking goods from a place A1, then delivering the goods from a place B1, and finally delivering the goods from a place B2;
possible path 5: firstly, taking goods from a place A2, then taking goods from a place A1, then delivering the goods from a place B2, and finally delivering the goods from a place B1;
possible path 6: the method comprises the steps of taking goods from a place A2, delivering the goods from the place B2, taking the goods from the place A1, and delivering the goods from the place B1.
For each possible path, calculating the cost of the sub path according to the linear distance of each sub path, and accumulating the cost of each sub path to obtain the accumulated cost of the possible path. The possible path 6 is taken as the planned path because the cumulative cost among the 6 possible paths is the lowest, i.e., the sum of the straight-line distances of the respective sub-paths is the shortest possible path 6.
As can be seen by comparing fig. 2B and fig. 2C, although the cost of a single sub-path in the possible path 6 is not the lowest of the selectable sub-paths, the cumulative cost of the overall path is the lowest of the six possible paths, so that the limitation of path planning based on the greedy algorithm is avoided, the result of path planning is more reliable, the logistic cost can be effectively reduced, and the distribution efficiency is improved.
FIG. 3 illustrates a schematic diagram of calculating the cumulative cost of possible paths according to an embodiment of the present disclosure.
As shown in fig. 3, in an alternative embodiment of the present disclosure, the cumulative cost of the distribution resources completing all possible paths of the current order may be calculated by the following back-pushing method.
First, assuming that the current order of the delivery resource is orderlize, where the status of each order includes three states, not beginning (0), picked (1) and completed (2), the current order status may be represented by a ternary encoding. For example, ordersize=2, status=10 may be used 3 To indicate that there are 2 orders for the current delivery resource to be completed, wherein the status of order 1 is picked and the status of order 2 is not started.
Reusing two-dimensional array D status ][index]Indicating the current cumulative cost of the delivery resource, wherein index indicates the order status of the delivery resource that has recently updated the order index (the array counts from 1, and 0 indicates that order 1 and order 2 have not been processed). For example, D [21 ] 3 ][2]Representing the cumulative cost of the delivery resource in completing the delivery of order 1 and the pick of order 2, and most recently completing the pick of order 2. And c (index) is used to represent the slave more distributed resourceThe cost spent in updating the order index state from the new order preIndex state, which is the previously processed order of the order index. For example, if the delivery resource delivers order 2 after delivering order 1, then order 1 is the order preIndex if order 2 is the order index.
Thus, according to the logic of the access sequence of the delivery resource, the current accumulated cost D [ status ] [ index ] of the delivery resource can be calculated by the following equation:
D[status][index]
＝Min(D[preStatus][preIndex])+c(preIndex,index))
for example, when ordersize=2,
D[21 3 ][1]＝Min(D[11 3 ][2]+c(2,1),D[11 3 ][1]+c(1,1))。
the above formula is understood to mean that the cumulative cost of the delivery resource at the time of the order state S (order 1 has been completed, order 2 has been picked, and order 1 has been updated recently) is calculated from the sum of the cumulative cost at the time of the order state S1 (order 1 has been picked, order 2 has been picked, and order 1 has been completed recently) and the cost at the time of the process C1 (the process from the completion of the picking of order 1 to the delivery of order 1), and the cumulative cost at the time of the order state S2 (order 1 has been picked, order 2 has been picked, and order 2 has been completed recently) and the cost at the time of the process C2 (the process from the completion of the picking of order 2 to the delivery of order 1).
Since status > preStatus, each iteration in the scheme is based on the sub-problem of the previous iteration, and the ineffectiveness of dynamic planning is met.
According to an embodiment of the present disclosure, when the delivery resource order is orderlize=2, the final order status is finalstatus=22 3 (i.e., order 1 has been completed and order 2 has been completed). As shown in FIG. 3, the final status D [22 ] of order 1 and order 2 may be completed by the delivery resource 3 ][1]And D [22 ] 3 ][2]To an initial state D00 3 ][0]The back-pushovers result in various possible paths. For each possibleAnd respectively solving the sub-path cost of the paths, accumulating the sub-path cost to obtain the accumulated cost finalCost of the delivery resource for completing the order 1 and the order 2, and selecting the possible path with the lowest finalCost as the planning path.
In an alternative embodiment of the present disclosure, in the event that the delivery resource receives a new order while delivering along the planned path, the first target location reached at or after receipt of the new order is taken as the updated starting location.
For example, when the delivery resource obtains order 1 at the start location O, and the pick-up location of order 1 is location A1 and the pick-up location is location B1. When the delivery resource is picked up at location A1, order 2 is obtained, and the pick-up location of order 2 is location A2 and the ship-to location is location B2, then the planned path to locations A2, B1 and B2 is updated with location A1 as the updated starting location.
According to the embodiment of the disclosure, when the delivery resource receives a new order while delivering goods along the planned path, the starting location is updated to the location where the new order is received or the first target location reached after the new order is received, so that the path planning method has higher real-time performance, and further the delivery efficiency and reliability are improved.
Fig. 4 shows a flow chart of a path planning method according to another embodiment of the present disclosure.
As shown in fig. 4, in an alternative embodiment of the present disclosure, step S103 is further included before step S101.
In step S103, the cost of the sub-path is obtained by weighted summation of any one or more of the transit time, the path length, and the distribution resource preference of the sub-path.
According to an embodiment of the present disclosure, the distribution resource preference includes at least one of: the residence time of the delivery resource at the start location, the walking distance at the start location, the residence time at the target location, and the walking distance at the target location. In this way, when calculating the cost of the sub-path, any one or more of the passing time, the path length and the distribution resource preference can be selected for weighted summation according to the actual application scene of the method, so that the path planning result is more in line with the actual situation to a certain extent, and the flexibility and the reliability of the path planning method are improved.
Fig. 5 illustrates a flow chart of adjusting respective weights for determining any one or more of a transit time, a path length, and a distribution resource preference, according to an embodiment of the present disclosure.
As shown in fig. 5, in an alternative embodiment of the present disclosure, before determining the cost of the sub-path, further comprising determining the corresponding weight of any one or more of the transit time, the path length, the distribution resource preference by the following steps S201-S204, including:
in step S201, initializing the corresponding weights;
in step S202, acquiring an actual start location and one or more actual target locations of each of a plurality of actual history paths;
in step S203, for each actual historical path, acquiring possible paths from the actual starting location to the one or more actual target locations, the possible paths being divided into one or more sub-paths by the actual starting location and the one or more actual target locations, calculating an accumulated cost of the possible paths using any one or more of a transit time, a path length, a distribution resource preference of each sub-path of the possible paths and their corresponding weights, and selecting a possible path with the lowest accumulated cost as a planning path of the actual historical path;
In step S204, the corresponding weights are adjusted to maximize the overall overlap of the planned path with the corresponding actual historical path.
In an alternative embodiment of the present disclosure, bringing the planned path into close proximity with the respective actual historical path includes maximizing an overall overlap of the planned path of the plurality of actual historical paths with the respective actual historical path.
In an alternative embodiment of the present disclosure, the overall overlap of the planned path of the plurality of actual historical paths with the corresponding actual historical paths may be determined, for example, by any of the following.
For example, for each of the actual historical paths, the number of sub-paths whose corresponding planned path is at the same level as the actual historical path may be calculated as a first number, the corresponding first numbers of the actual historical paths may be summed, and the sum may be divided by the sum of sub-paths of the actual historical paths to obtain the overall overlap ratio. For example, assuming that the actual history paths are m→n→o→p→q and u→v→w→x→y, and the corresponding planned paths thereof are m→o→n→p→q and u→v→x→w→y, respectively, the sub-paths of the actual history paths m→n→o→p→q in the same rank as those of the corresponding planned paths thereof are p→q, and the sub-paths of the actual history paths u→v→w→x→y in the same rank as those of the corresponding planned paths thereof are u→v. Thus, the first number of the two actual history paths is 1, and the overall overlap ratio is (1+1)/(4+4) =0.25.
Or, for each actual historical path, calculating the number of sub-paths with the same level in the corresponding planning path and the actual historical path, dividing the number by the total number of sub-paths in the actual historical path to obtain the coincidence degree of the corresponding planning path of the actual historical path, adding the coincidence degrees of the corresponding planning paths of the actual historical paths, and dividing the coincidence degree by the total number of the historical paths to obtain the overall coincidence degree. For example, for the above actual history paths m→n→o→p→q and u→v→w→x→y, the overlap ratio is 1/4=0.25, and the overall overlap ratio is (0.25+0.25)/2=0.25. For example, in one alternative embodiment of the present disclosure, cost (i, j, k) may be used to represent the cost of the sub-path of rider k from location i to location j:
cost(i,j,k)＝h0*t(i,j)+h1*d(i,j)+h2*p(k,i)+h3*p(k,j)
where t (i, j) is the transit time from location i to location j, d (i, j) is the transit distance from location i to location j, p (k, i) is the preference feature of the distribution resource k at location i, p (k, j) is the preference feature of the distribution resource k at location j, and h0, h1, h2, and h3 are the transit times, transit distances, and the corresponding weights of the preference features.
In step S201, the respective weights h0, h1, h2, and h3 are initialized, for example, all set to 0.25. It should be noted that the value 0.25 is merely an example, and the present disclosure is not limited thereto.
In step S202, an actual start location and one or more actual target locations of each of a plurality of actual history paths are acquired.
In step S203, a planned path of the plurality of actual historic paths is determined using the data of the plurality of actual historic paths of the delivery resource. Specifically, for each actual historical path, possible paths from an actual starting location to one or more actual target locations thereof are obtained, the cost of sub-paths of each possible path is calculated through costs (i, j, k), the accumulated cost of the possible paths is calculated, and the possible path with the lowest accumulated cost is selected as the planning path of the actual historical path.
Finally, in step S204, the planned path and the actual historical paths are compared, and weights h0, h1, h2 and h3 are adjusted so as to maximize the overall overlap ratio of the planned paths of the actual historical paths and the corresponding actual historical paths.
In this embodiment, the preference feature of the distribution resource k at the location i may be the average residence time or the average walking distance of the distribution resource k at the location i, or the residence time or the walking distance at the location i may be predicted from the preference habit of the distribution resource k. For example, when the delivery resource k delivers in the office building, the delivery resource k prefers to climb stairs when the ship-to site is above the office building, and the delivery resource k prefers to take an elevator when the ship-to site is above the office building, so that the specific mode of delivering the delivery resource k is predicted, and the stay time or walking distance of the delivery resource k at the site i is predicted.
Fig. 6 shows a block diagram of a path planning apparatus according to an embodiment of the present disclosure.
As shown in fig. 6, the path planning apparatus 600 includes a calculation module 610 and a determination module 620. The path planning apparatus 600 and the respective modules thereof may be implemented by computer software or by programmable hardware.
The computing module 610 is configured to obtain a possible path for a delivery resource from a start location to one or more target locations, determine a cumulative cost for the possible path, wherein the possible path is divided by the start location and the one or more target locations into one or more sub-paths, the cumulative cost comprising a sum of costs of the sub-paths, the costs of the sub-paths being related to at least any one or more of a transit time of the sub-path, a path length, and a preference of the delivery resource.
The determination module 620 is configured to take the possible path with the lowest cumulative cost as the planned path for the delivery resource.
In an alternative embodiment of the present disclosure, the path planning apparatus 600 further comprises a cost determination module 630 configured to obtain the cost of the sub-path by weighted summation of any one or more of the transit time, the path length, the distribution resource preference of the sub-path.
In an alternative embodiment of the present disclosure, the path planning apparatus 600 further comprises a weight determination module 640 configured to determine a respective weight of the any one or more of the transit time, path length, and distribution resource preference.
In one possible embodiment of the present disclosure, the weight determination module 640 may include a first module 641, a second module 642, a third module 643, and a fourth module 644.
The first module 641 is configured to initialize the respective weights.
The second module 642 is configured to obtain an actual starting location and one or more actual target locations for each of a plurality of actual historic paths.
The third module 643 is configured to obtain, for each actual historical path, a possible path from the actual start location to the one or more actual target locations, the possible path being divided into one or more sub-paths by the actual start location and the one or more actual target locations, calculate an accumulated cost for the possible path using any one or more of a transit time, a path length, a distribution resource preference of each sub-path of the possible path, and their corresponding weights, and select the possible path with the lowest accumulated cost as a planned path of the actual historical path.
A fourth module 644 is configured to adjust the respective weights to maximize an overall overlap of the planned path with the respective actual historical paths.
In an alternative embodiment of the present disclosure, the path planning apparatus 600 further comprises a location determination module 650 configured to determine the one or more target locations based on the pick-up location and/or the pick-up location of the pending order for the delivery resource and the processing status of the pending order for the delivery resource.
In one embodiment of the present disclosure, the one or more target locations correspond to pick-up locations and pick-up locations of one or more orders. In the possible paths, the pick-up location of any order is located before the pick-up location of the order.
In one embodiment of the present disclosure, in the event that the delivery resource receives a new order while delivering the new order along the planned path, the location at which the new order was received or the first target location reached after the new order was received is taken as the updated starting location.
In one embodiment of the present disclosure, the overall overlap ratio is calculated by any of the following means:
calculating the number of sub-paths with the same level in the corresponding planning path and the actual historical paths as a first number for each actual historical path, summing the corresponding first number of the actual historical paths, and dividing the sum by the sum of the sub-paths of the actual historical paths to obtain the overall contact ratio; or alternatively
And calculating the number of sub-paths in the same order in the corresponding planning path and the actual historical path for each actual historical path, dividing the number by the total number of sub-paths in the actual historical path to obtain the coincidence ratio of the corresponding planning path of the actual historical path, adding the coincidence ratios of the corresponding planning paths of the actual historical paths, and dividing the coincidence ratio by the total number of the historical paths to obtain the overall coincidence ratio.
In one embodiment of the present disclosure, the delivery resource preference includes a residence time and/or walking distance of the delivery resource at the starting location and/or the target location.
Fig. 7 shows a block diagram of an electronic device according to an embodiment of the present disclosure.
As shown in fig. 7, the electronic device 700 may include a processor 701 and a memory 702. The memory 702 is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor 701 to perform the steps of:
obtaining possible paths for a delivery resource to reach one or more target sites from a start site, and determining accumulated costs of the possible paths, wherein the possible paths are divided into one or more sub-paths by the start site and the one or more target sites, the accumulated costs comprise the sum of the costs of the sub-paths, and the costs of the sub-paths are at least related to any one or more of the transit time, the path length and the delivery resource preference of the sub-paths;
The possible path with the lowest accumulated cost is taken as the planning path of the distribution resource.
In one embodiment of the present disclosure, the one or more target locations correspond to a pick-up location and a pick-up location of one or more orders, the pick-up location of any one order being located before the pick-up location of the order in the possible path.
In one embodiment of the present disclosure, in the event that the delivery resource receives a new order while delivering the new order along the planned path, the location at which the new order was received or the first target location reached after the new order was received is taken as the updated starting location.
In one embodiment of the present disclosure, the one or more computer instructions are further executable by the processor 701 to perform the steps of:
the cost of the sub-path is obtained by weighted summation of any one or more of the transit time, the path length and the distribution resource preference of the sub-path.
In one embodiment of the present disclosure, the delivery resource preference includes a residence time and/or walking distance of the delivery resource at the starting location and/or the target location.
In one embodiment of the present disclosure, the one or more computer instructions are further executable by the processor 701 to perform the steps of: before determining the cost of the sub-path, determining the corresponding weights for the any one or more of the transit time, path length, and delivery resource preference by:
Initializing the corresponding weight;
acquiring respective actual initial positions and one or more actual target positions of a plurality of actual historical paths;
for each actual historical path, acquiring possible paths from the actual starting place to the one or more actual target places, dividing the possible paths into one or more sub-paths by the actual starting place and the one or more actual target places, calculating the accumulated cost of the possible paths by using any one or more of the transit time, the path length and the distribution resource preference of each sub-path of the possible paths and the corresponding weight of each sub-path, and selecting the possible path with the lowest accumulated cost as a planning path of the actual historical path;
and adjusting the corresponding weight to maximize the overall contact ratio of the planned path and the corresponding actual historical path.
In one embodiment of the present disclosure, the overall overlap ratio is calculated by any of the following means:
calculating the number of sub-paths with the same level in the corresponding planning path and the actual historical paths as a first number for each actual historical path, summing the corresponding first number of the actual historical paths, and dividing the sum by the sum of the sub-paths of the actual historical paths to obtain the overall contact ratio; or alternatively
And calculating the number of sub-paths in the same order in the corresponding planning path and the actual historical path for each actual historical path, dividing the number by the total number of sub-paths in the actual historical path to obtain the coincidence ratio of the corresponding planning path of the actual historical path, adding the coincidence ratios of the corresponding planning paths of the actual historical paths, and dividing the coincidence ratio by the total number of the historical paths to obtain the overall coincidence ratio.
In one embodiment of the present disclosure, the one or more computer instructions are further executable by the processor 701 to perform the steps of:
the one or more target locations are determined based on the pick-up location and/or the pick-up location of the pending order for the delivery resource and the processing status of the pending order for the delivery resource.
Fig. 8 shows a block diagram of a computer system suitable for use in implementing a path planning method according to an embodiment of the present disclosure.
As shown in fig. 8, the computer system 800 includes a Central Processing Unit (CPU) 801 that can execute the above-described method according to a program stored in a Read Only Memory (ROM) 802 or a program loaded from a storage section 808 into a Random Access Memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the system 800 are also stored. The CPU 801, ROM 802, and RAM 803 are connected to each other by a bus 804. An input/output (I/O) interface 805 is also connected to the bus 804.
The following components are connected to the I/O interface 805: an input portion 806 including a keyboard, mouse, etc.; an output portion 807 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and a speaker; a storage section 808 including a hard disk or the like; and a communication section 809 including a network interface card such as a LAN card, a modem, or the like. The communication section 809 performs communication processing via a network such as the internet. The drive 810 is also connected to the I/O interface 805 as needed. A removable medium 811 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 810 as needed so that a computer program read out therefrom is mounted into the storage section 808 as needed.
In particular, according to embodiments of the present disclosure, the methods described above may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a medium readable thereby, the computer program comprising program code for performing the method described above. In such an embodiment, the computer program may be downloaded and installed from a network via the communication section 809, and/or installed from the removable media 811.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules referred to in the embodiments of the present disclosure may be implemented in software or in programmable hardware. The units or modules described may also be provided in a processor, the names of which in some cases do not constitute a limitation of the unit or module itself.
As another aspect, the present disclosure also provides a computer-readable storage medium, which may be a computer-readable storage medium included in the apparatus described in the above embodiment; or may be a computer-readable storage medium, alone, that is not assembled into a device. The computer-readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the present disclosure.
The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by those skilled in the art that the scope of the invention referred to in this disclosure is not limited to the specific combination of features described above, but encompasses other embodiments in which any combination of features described above or their equivalents is contemplated without departing from the inventive concepts described. Such as those described above, are mutually substituted with the technical features having similar functions disclosed in the present disclosure (but not limited thereto).
Claims (14)
1. A method of path planning, comprising:
determining one or more target sites according to the pick-up sites and/or the pick-up sites of the to-be-processed orders of the distribution resources and the processing states of the to-be-processed orders of the distribution resources;
Obtaining possible paths of the distribution resources from the starting location to one or more target locations;
calculating, in a back-stepping manner, a cumulative cost for each of the possible paths for the delivery resource to fulfill the pending order, wherein the possible paths are divided by the starting location and the one or more target locations into one or more sub-paths, the cumulative cost comprising a sum of costs for each of the sub-paths, the costs of the sub-paths being related to at least any one or more of transit time, path length, and the delivery resource preference of the sub-paths;
taking the possible path with the lowest accumulated cost as a planning path of the distribution resource;
wherein the obtaining a possible path of the delivery resource from the start location to one or more target locations comprises:
acquiring all possible paths from the starting point to traverse the target points corresponding to the orders according to the mode that the position of the pick-up point of any order in the path is positioned before the pick-up point of the corresponding order;
wherein calculating, in a back-push manner, an accumulated cost for the delivery resource to complete each of the possible paths of the pending order comprises:
And D [ status ] [ index ] is used for representing the accumulated cost of the current state of the distribution resource, wherein status is used for representing the state of an order, index is used for representing the updated order identification of the distribution resource, two-dimensional array [ status ] [ index ] is used for representing the state corresponding to the current node, and the final state corresponding to each possible path is reversely pushed to the initial state to obtain the accumulated cost.
2. The method of claim 1, wherein in the event that the delivery resource receives a new order while delivering along the planned path, the first target location reached at or after receipt of the new order is taken as the updated starting location.
3. The method as recited in claim 1, further comprising:
and obtaining the cost of the sub-path by carrying out weighted summation on any one or more of the transit time, the path length and the distribution resource preference of the sub-path.
4. A method according to claim 3, further comprising, prior to determining the cost of the sub-path, determining the respective weights for the any one or more of the transit time, path length, distribution resource preference by:
Initializing the corresponding weight;
acquiring respective actual initial positions and one or more actual target positions of a plurality of actual historical paths;
for each actual historical path, acquiring possible paths from the actual starting place to the one or more actual target places, dividing the possible paths into one or more sub-paths by the actual starting place and the one or more actual target places, calculating the accumulated cost of the possible paths by using any one or more of the transit time, the path length and the distribution resource preference of each sub-path of the possible paths and the corresponding weight of each sub-path, and selecting the possible path with the lowest accumulated cost as a planning path of the actual historical path;
and adjusting the corresponding weight to maximize the overall contact ratio of the planned path and the corresponding actual historical path.
5. The method of claim 4, wherein the overall overlap ratio is calculated by any of:
calculating the number of sub-paths with the same level in the corresponding planning path and the actual historical paths as a first number for each actual historical path, summing the corresponding first number of the actual historical paths, and dividing the sum by the sum of the sub-paths of the actual historical paths to obtain the overall contact ratio; or alternatively
And calculating the number of sub-paths in the same order in the corresponding planning path and the actual historical path for each actual historical path, dividing the number by the total number of sub-paths in the actual historical path to obtain the coincidence ratio of the corresponding planning path of the actual historical path, adding the coincidence ratios of the corresponding planning paths of the actual historical paths, and dividing the coincidence ratio by the total number of the historical paths to obtain the overall coincidence ratio.
6. The method of claim 1, wherein the delivery resource preferences include a residence time and/or a walking distance of the delivery resource at a starting location and/or a destination location.
7. A path planning apparatus, comprising:
a target location acquisition module configured to determine one or more target locations according to a pick-up location and/or a pick-up location of a to-be-processed order of a delivery resource and a processing status of the to-be-processed order of the delivery resource;
a computing module configured to obtain possible paths for a delivery resource from a start location to one or more target locations, calculate, in a back-stepping manner, a cumulative cost for each of the possible paths for the delivery resource to complete the order to be processed, wherein the possible paths are divided into one or more sub-paths by the start location and the one or more target locations, the cumulative cost comprising a sum of costs for each of the sub-paths, the costs of the sub-paths being related to at least any one or more of transit time, path length, and the delivery resource preference of the sub-paths;
A determination module configured to take the possible path with the lowest accumulated cost as a planned path of the delivery resource;
the computing module is specifically configured to:
acquiring all possible paths from the starting point to traverse the target points corresponding to the orders according to the mode that the position of the pick-up point of any order in the path is positioned before the pick-up point of the corresponding order;
wherein calculating, in a back-push manner, an accumulated cost for the delivery resource to complete each of the possible paths of the pending order comprises:
and D [ status ] [ index ] is used for representing the accumulated cost of the current state of the distribution resource, wherein status is used for representing the state of an order, index is used for representing the updated order identification of the distribution resource, two-dimensional array [ status ] [ index ] is used for representing the state corresponding to the current node, and the final state corresponding to each possible path is reversely pushed to the initial state to obtain the accumulated cost.
8. An electronic device comprising a memory and a processor, the memory for storing one or more computer instructions, the one or more computer instructions being executable by the processor to perform the steps of:
Determining one or more target sites according to the pick-up sites and/or the pick-up sites of the to-be-processed orders of the distribution resources and the processing states of the to-be-processed orders of the distribution resources;
obtaining possible paths of the distribution resources from the starting location to one or more target locations;
calculating, in a back-stepping manner, a cumulative cost for each of the possible paths for the delivery resource to fulfill the pending order, wherein the possible paths are divided by the starting location and the one or more target locations into one or more sub-paths, the cumulative cost comprising a sum of costs for each of the sub-paths, the costs of the sub-paths being related to at least any one or more of transit time, path length, and the delivery resource preference of the sub-paths;
taking the possible path with the lowest accumulated cost as a planning path of the distribution resource;
wherein the obtaining a possible path of the delivery resource from the start location to one or more target locations comprises:
acquiring all possible paths from the starting point to traverse the target points corresponding to the orders according to the mode that the position of the pick-up point of any order in the path is positioned before the pick-up point of the corresponding order;
Wherein calculating, in a back-push manner, an accumulated cost for the delivery resource to complete each of the possible paths of the pending order comprises:
and D [ status ] [ index ] is used for representing the accumulated cost of the current state of the distribution resource, wherein status is used for representing the state of an order, index is used for representing the updated order identification of the distribution resource, two-dimensional array [ status ] [ index ] is used for representing the state corresponding to the current node, and the final state corresponding to each possible path is reversely pushed to the initial state to obtain the accumulated cost.
9. The electronic device of claim 8, wherein in the event that the delivery resource receives a new order while delivering along the planned path, the first target location reached at or after receipt of the new order is taken as the updated starting location.
10. The electronic device of claim 8, wherein the one or more computer instructions are further executable by the processor to perform the steps of:
and obtaining the cost of the sub-path by carrying out weighted summation on any one or more of the transit time, the path length and the distribution resource preference of the sub-path.
11. The electronic device of claim 10, wherein the one or more computer instructions are further executable by the processor to perform the steps of:
before determining the cost of the sub-path, determining the corresponding weights for the any one or more of the transit time, path length, and delivery resource preference by:
initializing the corresponding weight;
acquiring respective actual initial positions and one or more actual target positions of a plurality of actual historical paths;
for each actual historical path, acquiring possible paths from the actual starting place to the one or more actual target places, dividing the possible paths into one or more sub-paths by the actual starting place and the one or more actual target places, calculating the accumulated cost of the possible paths by using any one or more of the transit time, the path length and the distribution resource preference of each sub-path of the possible paths and the corresponding weight of each sub-path, and selecting the possible path with the lowest accumulated cost as a planning path of the actual historical path;
and adjusting the corresponding weight to maximize the overall contact ratio of the planned path and the corresponding actual historical path.
12. The electronic device of claim 11, wherein the overall overlap ratio is calculated by any of:
calculating the number of sub-paths with the same level in the corresponding planning path and the actual historical paths as a first number for each actual historical path, summing the corresponding first number of the actual historical paths, and dividing the sum by the sum of the sub-paths of the actual historical paths to obtain the overall contact ratio; or alternatively
And calculating the number of sub-paths in the same order in the corresponding planning path and the actual historical path for each actual historical path, dividing the number by the total number of sub-paths in the actual historical path to obtain the coincidence ratio of the corresponding planning path of the actual historical path, adding the coincidence ratios of the corresponding planning paths of the actual historical paths, and dividing the coincidence ratio by the total number of the historical paths to obtain the overall coincidence ratio.
13. The electronic device of claim 8, wherein the distribution resource preference comprises a residence time and/or a walking distance of the distribution resource at a start location and/or a target location.
14. A readable storage medium having stored thereon computer instructions which, when executed by a processor, implement the method of any of claims 1-6.
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| CN110426052A (en) * | 2019-07-05 | 2019-11-08 | 中国平安财产保险股份有限公司 | Method for obtaining path, system, equipment and computer readable storage medium |
| CN110610333B (en) * | 2019-08-21 | 2022-01-04 | 深圳易马达科技有限公司 | Method and terminal for planning path |
| CN110851755B (en) * | 2019-09-29 | 2022-11-11 | 口碑(上海)信息技术有限公司 | Method and device for acquiring delivery path information and electronic equipment |
| CN112580843B (en) * | 2019-09-30 | 2022-11-04 | 明创能源股份有限公司 | Reconfigurable distributed real-time transmission and distribution system and real-time transmission and distribution method |
| CN110909859B (en) * | 2019-11-29 | 2023-03-24 | 中国科学院自动化研究所 | Bionic robot fish motion control method and system based on antagonistic structured control |
| CN111080214A (en) * | 2020-01-02 | 2020-04-28 | 汉口北进出口服务有限公司 | Logistics distribution path determining method and device and storage medium |
| CN111325502B (en) * | 2020-02-07 | 2022-02-15 | 北京三快在线科技有限公司 | Line calculation method and device, electronic equipment and readable storage medium |
| CN111429058A (en) * | 2020-03-20 | 2020-07-17 | 上海中通吉网络技术有限公司 | Delivery path recommendation method, device, equipment and storage medium |
| CN111754051B (en) * | 2020-07-23 | 2021-01-08 | 拉扎斯网络科技（上海）有限公司 | Traffic duration prediction processing method and device |
| CN112801748A (en) * | 2021-02-03 | 2021-05-14 | 拉扎斯网络科技（上海）有限公司 | Distribution path data obtaining method and device and electronic equipment |
| CN112801592A (en) * | 2021-02-09 | 2021-05-14 | 北京橙心无限科技发展有限公司 | Method and device for planning distribution path |
| CN113379077A (en) * | 2021-06-15 | 2021-09-10 | 上海市信息网络有限公司 | Maintenance path planning method, system, device and medium |
| CN115164914B (en) * | 2022-07-11 | 2023-10-03 | 北京中航世科电子技术有限公司 | Navigation method, system, electronic equipment and medium for individual combat |
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