CN109284891B - Charging pile maintenance scheduling method based on time-space index - Google Patents
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Abstract
The invention belongs to the technical field of computer application, and provides a charging pile maintenance scheduling method based on a time-space index. According to the method, quick searching of maintenance personnel is completed by establishing a space-time index, then the cost between the detour path and quick response is balanced according to the maintenance time urgency and the maintenance difficulty of each charging pile, and the scheduling of the maintenance personnel is completed by an optimal strategy. Aiming at the fact that the calculation load of the shortest driving distance of maintenance personnel is large, an inertia shortest path calculation method is adopted, the method makes full use of known geographic information, is simple and efficient, and is greatly improved in speed compared with a conventional algorithm. And in the whole scheduling process, quick maintainer search is completed by establishing a space-time index, and then the cost between the detour and quick response is balanced according to the maintenance time urgency and the maintenance difficulty of each charging pile, so that the maintainer scheduling is completed by an optimal strategy. And aiming at the problem that the calculation load of the shortest driving distance of a maintainer is large, an inert shortest path calculation method is adopted, and redundant calculation is reduced.
Description
Technical Field
The invention belongs to the technical field of computer application, and relates to a charging pile maintenance scheduling method based on a time-space index.
Background
Along with the rise of green traffic, the market demand of the charging automobile is gradually increased, and the demand of the charging pile is increased. For charging pile operators, the timely degree of maintenance of the charging pile directly influences the utilization rate of the charging pile and the enterprise service image. However, coordination difficulty of personnel for maintaining the charging pile is high, and personnel scheduling cost is high, which is a very important problem.
The development of the current mobile internet information technology is benefited, and the specific position can be conveniently positioned by the GPS positioning of the smart phone. In the current operation of filling electric pile enterprise, the maintenance person through the electric pile management APP of cell-phone end with the real-time self state information of certain frequency update to dispatch center, the user can be according to the real-time feedback on the in service behavior APP again, if there is the electric pile trouble and needs the maintenance, then sends the maintenance request to the dispatch center, fills electric pile simultaneously and also can upload the status code to the server, report whether the current condition of stake is normal.
However, charging pile faults occur frequently, fault places are scattered, the current position state and the working state of a maintainer are not considered in the existing maintenance scheduling method, and large operation cost is brought to charging pile operation enterprises. Fill electric pile and also need the maintainer to carry out routine maintenance, like the rifle routine maintenance that charges, pile body inspection, the function detection that charges, fill electric pile communication fault detection etc.. How to efficiently schedule a maintainer to respond to a charging pile maintenance request and perform daily maintenance tasks on the same day is very important for charging pile operation enterprises.
Disclosure of Invention
Aiming at the current situation that maintenance scheduling is difficult and high in cost in a charging pile enterprise, the invention provides a charging pile maintenance scheduling method based on a time-space index. And in the whole scheduling process, quick maintainer search is completed by establishing a space-time index, and then the cost between the detour and quick response is balanced according to the maintenance time urgency and the maintenance difficulty of each charging pile, so that the maintainer scheduling is completed by an optimal strategy. And aiming at the problem that the calculation load of the shortest driving distance of a maintainer is large, an inert shortest path calculation method is adopted, and redundant calculation is reduced.
The technical scheme of the invention is as follows:
a charging pile maintenance scheduling method based on space-time index comprises the following steps:
define 2 Dispatch plan s ═ v1,v2，…,vn) Is determined by a maintenance scheduling algorithmTemporal list of sequential n repair tasks, vkThe geographical position of the fault charging pile;
defining 3 that a serviceman P ═ (id, p.lat, p.lon, occ, ot, P.s) contains information of a serviceman's current status, where id is a serviceman job number, p.lat and p.lon are information of a current position of the serviceman, occ indicates whether the serviceman is working, ot indicates whether the serviceman can also perform work or complete work according to a maintenance schedule, and P.s indicates the serviceman's current maintenance schedule;
establishing a time-space index according to geographical position information of a charging pile
1.1, carrying out grid division on map data of a city corresponding to the charging piles, wherein the size of a grid is as close as possible to that of a city block; if the grid contains the charging pile, selecting the geographic position of the charging pile as an anchor point of the grid, and if the grid does not contain the charging pile, selecting a grid center point as the anchor point of the grid;
1.2, obtaining the running time and the running road section between a part of anchor points according to the work data of historical maintainers, and estimating the running speed; selecting the overall average running speed between anchor points without historical maintenance data;
1.3, calculating the shortest driving distance among all grid anchor points and establishing a distance matrix D; estimating the running time according to the result in the step 1.2, and establishing a time matrix H for supporting the calculation of the shortest inertia path;
1.4 for each grid GiCreating a temporal index list, a spatial index list, and a grid GiThe corresponding maintainer index table is used for searching by the maintainers;
1.4.1 time index List from respective grid to grid GiSorting the required travel time in an ascending order;
1.4.2 spatial index List from respective grid to grid GiSorting the required driving distances in an ascending order;
1.4.3 in-grid maintainers and upcoming drives into grid G during a particular time periodiIs dynamically changed, each of the maintainers drives out of the grid GiAnd then the water-soluble organic acid is removed,each maintenance person drives into the grid GiTime will be inserted and the time stamp of the serviceman in the grid will also be updated after receiving the updated GPS signal; the ID of each serviceman is time-stamped;
(II) screening serviceable maintainer candidate sets by Fibonacci search based on travel time
First, a candidate set of maintainers is set, ttmpRepresenting the current time, tijRepresenting the travel time required for travel between two grid anchor points, denoted by t(A,B)Represents the travel time required between two places AB, d(A,B)Representing the required driving distance between the two places AB;
2.1 when a maintenance request is placed on grid GiThen, whether maintenance personnel in the grid can meet the time window constraint of maintenance of the charging pile is checked according to the sequence in the time index list, and then grid G is appliediThe corresponding maintainer index table looks up the grid G where the current time isiIf the time window constraint is met, inserting the maintainers meeting the maintenance urgency of the charging pile into the candidate set according to the time sequence;
2.2 if the size of the candidate set of the maintainers is larger than a given upper bound, the candidate set range is too large, the time window constraint of part of the maintainers is too tight, a plurality of maintainers are inserted to fail later, and the overall calculation burden is increased; the size of the upper bound can be determined according to the total number of maintenance personnel and the calculation performance of the maintenance scheduling system in the actual operation process;
determining a searched splitting point by adopting a Fibonacci numerical value closest to the length of the candidate set of the maintainer; finding a number F [ n ] which is equal to or close to the length of the candidate set of the maintainers in the Fibonacci number series, expanding the length of the original candidate set to be F [ n ] (if elements need to be supplemented, the last maintainer element is supplemented and repeated until F [ n ] elements are met), carrying out Fibonacci segmentation after the completion, and taking F [ n-1] elements of the first half part of segmentation to establish a new candidate set of the maintainers;
(III) inserting maintenance request Q into scheduling state of maintainer P using lazy shortest path computation policy
3.1 judging whether the maintainer P in the maintainer candidate set has a subsequent task at present in the scheduling plan, if not, then judging whether the maintainer P has a subsequent taskxAdd to the dispatch status of maintainer P; if there is a subsequent task QyThen the check is made to lie in grid G in the order in the spatio-temporal index listjWhether the serviceman satisfies ttmp+t(P.loc, i)+Qx.f≤Wy.uThe limit of (2);
3.1.1 location on grid G due to computationjThe calculation cost of the shortest distance between the maintainer and the grid anchor point j is obviously less than that of the direct calculation of the shortest distance between the maintainer and the grid anchor point j in the grid GjThe shortest distance between a maintainer and a target maintenance charging pile i is calculated by applying an inert shortest path calculation strategy, the cache data is utilized as much as possible, the calculation cost is reduced as little as possible, and the lower bound of the driving time of the maintainer and the charging pile to be maintained is calculated by a triangle inequality, namely t (P.loc, i) ≥ tij-t (p.loc, j); the feasibility test of the insertion is performed more quickly by the lower limit constraint;
3.1.2 only when the lower bound does not violate the time constraint, the algorithm needs to continuously calculate the shortest time path between the current point of a maintainer and the charging pile to be maintained and complete the limitation judgment of the step 3.2;
3.2 judging whether the detour distance generated by responding to the maintenance request Q meets alpha limit or not; to ensure minimum operational maintenance cost and maximum operational service quality, respond to maintenance requirements with maximum commercial interest, and define the original planned route (direct response Q)yMaintenance request) as a response request QxRatio of the generated travel distances
Greater than a certain ratio, inserting a service request Q into the service status of the serviceman if the limit is satisfied;
3.3 if no maintainer meeting the conditions is found, performing insertion feasibility check according to the steps 3.1 and 3.2 by using the residual persons in the maintainer candidate item which is not optimized in the step (two). If no suitable maintainer is found, the task is dispatched to a spare, spare maintainer.
The invention has the beneficial effects that: by the method, the geographical position information and the historical maintenance scheduling records of the maintainers are fully utilized, a space-time index is established for each maintainer in the system to complete quick regional maintainer search, the calculation load in the search process is reduced, and the repeated calculation is reduced by fully utilizing the historical maintenance data and the offline path calculation result by adopting an inert shortest path calculation method. The lower bound of the running time of a maintainer and the charging pile to be maintained is calculated through a triangle inequality, and the running time calculation is simplified. The method fully solves the problems that the frequent maintenance request amount of the charging pile faults is large, the fault places are scattered, the current position state and the working state of a maintainer are not considered in the existing maintenance scheduling method, the load amount, the maintenance detour distance proportion and the service response time are optimized, and the problem that the maintenance scheduling is difficult and the cost is high in a charging pile enterprise is solved.
Drawings
FIG. 1 is a system data flow diagram of the present method.
Fig. 2(a) and (b) are a shortest travel distance matrix D and a time matrix H between respective mesh anchors.
FIG. 3 is a schematic diagram of a candidate maintainer search process based on a spatial index list.
Fig. 4 is a process diagram of calculation according to the lower bound of the travel time of the maintenance personnel and the charging pile to be maintained.
FIG. 5 is a serviceman dispatch example.
FIG. 6 is a diagram of a calculation process for detour distance based on a repair person responding to a newly inserted repair request.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are described in detail and completely with reference to the drawings in the embodiments of the present invention.
The data flow diagram of the whole system is shown in fig. 1, and maintenance request data (including request time, longitude and latitude of the fault charging pile, minimum completion time for fault maintenance, and time urgency of maintenance task) are shown at the lower left.
After maintenance request data are received, maintenance personnel search is carried out according to a maintenance personnel space-time index table (1.4), a map, grid information and a shortest driving distance matrix D between grid anchor points, namely a shortest path cache (1.3), and newly calculated distance information is inserted when path information which is not in the distance matrix D is involved in the search process. And after the candidate set of the maintainers meeting the range is obtained, inserting the maintenance request into the scheduling state of the maintainers by applying an inert shortest path calculation strategy, and updating the state information of the maintainers. The above process is a maintenance request data stream.
When the information of the mobile geographic position of the maintainer is changed, the maintainer in the grid is updated and the maintainer is about to enter G in a specific time periodiA list of maintenance personnel. The above process updates the flow for the maintainer status.
Analyzing OSM map data, dividing city grid information, initializing a distance matrix D, and establishing a time index list and a space index list. The above process is an offline computational flow.
Firstly, establishing a time-space index according to geographical position information of a charging pile
Map data in an xml format of a city corresponding to the charging pile is downloaded in an OpenStreetMap, wherein data primitives comprise Nodes, Ways and relationships, a MongoDB database is selected to store massive geographic information point-line data, and a 2dsphere geographic space index mechanism of the MongoDB is applied to search data of an area near a certain specific point. And storing Point and Arc data in the map data of the corresponding city of the charging pile into a Point set and an Arc set in the MongoDB in a SAX interface self-defined map data analysis mode, creating a 2dsphere geographic space index db, Point, source index ({ ' gis ': 2dsphere ' }), and storing the geographic position data of the charging pile group into a Charge set in the MongoDB. According to the size of the city block, Grid division is carried out on the map data of the city corresponding to the charging pile according to the size of the block, and reference point information obtained after Grid division is stored in a set Grid; if the grid contains the charging pile, selecting the geographic position of the charging pile as an anchor point of the grid, and if the grid does not contain the charging pile, selecting a grid center point as the anchor point of the grid;
obtaining the running time and running road sections among partial anchor points according to the work data of historical maintainers, storing the calculated running road sections into a shortestPath set, estimating the running speed, and selecting the overall average form speed among anchor points without historical maintenance information;
calculating the shortest driving distance between each grid anchor point by adopting a Dijkstra algorithm after priority queue optimization, establishing a distance matrix D, estimating driving time according to the result in 1.2, and establishing a time matrix H, wherein D and H are shown in figure 2 and are used for supporting inert shortest path calculation; for each grid GiEstablishing a time index list, a space index list and a grid maintainer index list for maintainer search, searching a Point nearest to the center Point of a grid through a $ near, and sorting results according to the distance from near to far to db]},"$maxDistance":Grid.size}}})；
Second, a Fibonacci search based on travel time is used to screen a serviceable maintainer candidate set
When a maintenance request is placed on grid GiThen, whether maintainers in the grids can meet the time window constraint of maintenance of the charging pile is checked according to the sequence in the time index list, and the maintainer index table corresponding to the grids in the application range searches for the grid G at which the current time is locatediAnd if the maintenance person who is not in the maintenance state and satisfies the time window constraint is satisfied, the maintenance person who satisfies the charging pile maintenance urgency is inserted into the candidate set p _ candidate in the driving time sequence.
For example, as shown in fig. 3(a), the basic map has been subjected to grid division, and a space-time index has been established according to the geographical location information of the charging pile, and a fault of a charging pile sends out a maintenance request, where the grid where the fault charging pile is located is G5Look up G5Spatial index list of run distances corresponding to grids { G }3，G10，G4，G6，G2G11 and a time index list G created based on travel speed and distance3，G4，G10，G6，G2，G11Because of eachThe road conditions of the geographic positions are different, the corresponding driving speeds of the geographic positions are also different, so that the space index list and the time index list are not completely consistent, whether grids in the space-time index list meet the time window constraint of maintenance of the charging pile or not is judged, and the space index list { G meeting the time window constraint is selected3，G10，G4And a time index list G3，G4，G10And selecting maintainers meeting the time window constraint of the maintenance of the charging pile according to the sequence in the maintainer index table corresponding to the selected three grids, wherein the selection process is as shown in fig. 3(b), and the maintainers meeting the maintenance urgency of the charging pile are inserted into the candidate set according to the time sequence.
If the size p _ candidate of the candidate set of servicers is larger than a given upper bound max _ p _ can, the candidate set is too large and the time window constraints of some servicers are too tight, which may lead to a large number of subsequent servicer insertion failures and increase the overall computational burden. Determining a searched splitting point by adopting a Fibonacci numerical value closest to the length of the candidate set of the maintainer; constructing a Fibonacci array F [ i ] ═ F [ i-1] + F [ i-2], finding a number F [ n equal to or close to the length of the candidate set of the maintainer in the Fibonacci array, expanding the length of the original candidate set to be F [ n ] (if elements need to be supplemented, the last taxi element is supplemented and repeated until the F [ n ] elements are met), carrying out Fibonacci segmentation after the completion, and taking the F [ n-1] elements of the first half of segmentation to establish a new candidate set of the maintainer.
Third, insert maintenance request Q into the scheduling state of maintainer P using an lazy shortest path computation policy
Judging whether the maintainer P in the maintainer candidate set has a subsequent task at the present scheduling plan, if not, then the maintainer P will maintain the task QxAdded to the dispatch status P.s of the serviceman P, as shown in part two of FIG. 5, where white dots represent the dispatch tasks of the original dispatch plan and black dots represent the dispatch tasks to be inserted; if there is a subsequent task QyThen check that it is located in grid G in the order in the time index listjWhether the serviceman satisfies ttmp+t(P.loc,i)+Qx.f≤Wy.uIs located in grid GjCan be in accordance with QyArrival at grid G from the current position under time requirement of time urgency of maintenance taskiAnd is in Qx.fComplete Q within a fault minimum completion time ofxThe maintenance task of (1) is as shown in part (r) of FIG. 5;
since the computation is located in grid GjThe calculation cost of the shortest distance between the maintainer and the grid anchor point j is obviously less than that of the direct calculation of the shortest distance between the maintainer and the grid anchor point j in the grid GjThe shortest distance between the maintainer and the target maintenance charging pile i is calculated by applying an inert shortest path calculation strategy, the cache data is utilized as much as possible, the calculation cost is reduced as little as possible, the lower bound of the driving time of the maintainer and the charging pile to be maintained is calculated by a triangle inequality as shown in fig. 4, namely t (p.loc, i) ≧ tij-t (p.loc, j). With the lower bound, the feasibility test of the insertion can be performed more quickly.
Only when the time constraint is not violated by the lower bound, the algorithm needs to continuously calculate the shortest time path between the current point of the maintainer and the charging pile to be maintained and complete the limit judgment of the rest steps.
Determining response maintenance request QxWhether the generated detour distance meets the alpha limit or not; limiting the just completed Q to ensure minimum operational maintenance cost and maximum operational service quality, responding to maintenance requirements with maximum commercial benefitx-1Loc location of repair requestyMaintenance request) as a response request QxRatio of the generated travel distances
Greater than a certain ratio (maintenance request Q)xAnd QyThe corresponding charging pile position is QxAnd QyAnchor points of the charging pile grid), if the limit is met, the maintenance request Q is sentxInserted into the service state of the serviceman; the lower bound of the distance between d (p.loc, Qy) and d (p.loc, Qx) is calculated by the trigonometric inequality in order to reduce the amount of calculation. As shown in FIG. 6, the estimation is performed within the allowable range of the error
And if no maintainer meeting the conditions is found, applying the residual persons in the non-optimized maintainer candidate item set in the second step to carry out insertion feasibility check according to the third step. If no suitable maintainer is found, the task is dispatched to a spare, spare maintainer.
Claims (1)
1. A charging pile maintenance scheduling method based on space-time index is characterized by comprising the following steps:
definition 1 maintenance request Q ═ t (t)q,Q.lat,Q.lon,Qf,Wu) For each fault repair request QxWherein t isx.qIs the request time, Qx.latAnd Qx.lonFill electric pile longitude and latitude for trouble, Qx.fMinimum completion time for each trouble repair, Wx.uA time window constraint for a maintenance task;
define 2 Dispatch plan s ═ v1,v2，…,vn) Is a temporary list of time sequences of n maintenance tasks ordered by a maintenance scheduling algorithm, vkThe geographical position of the fault charging pile;
defining 3 that a serviceman P ═ (id, p.lat, p.lon, occ, ot, P.s) contains information of a serviceman's current status, where id is a serviceman job number, p.lat and p.lon are information of a current position of the serviceman, occ indicates whether the serviceman is working, ot indicates whether the serviceman can also perform work or complete work according to a maintenance schedule, and P.s indicates the serviceman's current maintenance schedule;
establishing a time-space index according to geographical position information of a charging pile
1.1, carrying out grid division on map data of a city corresponding to the charging piles, wherein the size of a grid is as close as possible to that of a city block; if the grid contains the charging pile, selecting the geographic position of the charging pile as an anchor point of the grid, and if the grid does not contain the charging pile, selecting a grid center point as the anchor point of the grid;
1.2, obtaining the running time and the running road section between a part of anchor points according to the work data of historical maintainers, and estimating the running speed; selecting the overall average running speed between anchor points without historical maintenance data;
1.3, calculating the shortest driving distance among all grid anchor points and establishing a distance matrix D; estimating the running time according to the result in the step 1.2, and establishing a time matrix H for supporting the calculation of the shortest inertia path;
1.4 for each grid GiCreating a temporal index list, a spatial index list, and a grid GiThe corresponding maintainer index table is used for searching by the maintainers;
1.4.1 time index List from respective grid to grid GiSorting the required travel time in an ascending order;
1.4.2 spatial index List from respective grid to grid GiSorting the required driving distances in an ascending order;
1.4.3 in-grid maintainers and upcoming drives into grid G during a particular time periodiIs dynamically changed, each of the maintainers drives out of the grid GiIs removed and each maintenance person drives into the grid GiTime will be inserted and the time stamp of the serviceman in the grid will also be updated after receiving the updated GPS signal; the ID of each serviceman is time-stamped;
(II) screening serviceable maintainer candidate sets by Fibonacci search based on travel time
First, a candidate set of maintainers is set, ttmpRepresenting the current time, tijRepresenting the travel time required for travel between two grid anchor points, denoted by t(A,B)Represents the travel time required between two places AB, d(A,B)Representing the required driving distance between the two places AB;
2.1 when a maintenance request is placed on grid GiThen, whether maintenance personnel in the grid can meet the time window constraint of maintenance of the charging pile is checked according to the sequence in the time index list, and then grid G is appliediThe corresponding maintainer index table looks up the grid G where the current time isiIf the time window constraint is met, inserting the maintainers meeting the maintenance urgency of the charging pile into the candidate set according to the time sequence;
2.2 if the size of the candidate set of the maintainers is larger than a given upper bound, the candidate set range is too large, the time window constraint of part of the maintainers is too tight, and then a plurality of maintainers insert failures, so that the overall calculation burden is increased; the size of the upper bound is determined according to the total number of maintenance personnel and the calculation performance of the maintenance scheduling system in the actual operation process;
determining a searched splitting point by adopting a Fibonacci numerical value closest to the length of the candidate set of the maintainer; finding a number F [ n ] which is equal to or close to the length of the candidate set of the maintainers in the Fibonacci number series, expanding the length of the original candidate set to be F [ n ], if elements need to be supplemented, supplementing and repeating the last element of the maintainers until the F [ n ] elements are met, carrying out Fibonacci segmentation after the F [ n ] elements are completed, and taking F [ n-1] elements of the first half part of segmentation to establish a new candidate set of the maintainers;
(III) inserting maintenance request Q into scheduling state of maintainer P using lazy shortest path computation policy
3.1 judging whether the maintainer P in the maintainer candidate set has a subsequent task at present in the scheduling plan, if not, then judging whether the maintainer P has a subsequent taskxAdd to the dispatch status of maintainer P; if there is a subsequent task QyThen the check is made to lie in grid G in the order in the spatio-temporal index listjWhether the serviceman satisfies ttmp+t(P.loc,i)+Qx.f≤Wy.uThe limit of (2);
3.1.1 location on grid G due to computationjThe calculation cost of the shortest distance between the maintainer and the grid anchor point j is obviously less than that of the direct calculation of the shortest distance between the maintainer and the grid anchor point j in the grid GjThe shortest distance between a maintainer and a target maintenance charging pile i is calculated by applying an inert shortest path calculation strategy to utilize cache data as much as possible and reduce calculation overhead as little as possible, and the rows of the maintainer and the charging pile to be maintained are calculated by a triangle inequalityLower bound of driving time, i.e. t (P.loc, i) ≥ tij-t (p.loc, j); the feasibility test of the insertion is performed more quickly by the lower limit constraint;
3.1.2 only when the lower bound does not violate the time constraint, the algorithm needs to continuously calculate the shortest time path between the current point of a maintainer and the charging pile to be maintained and complete the limitation judgment of the step 3.2;
3.2 judging whether the detour distance generated by responding to the maintenance request Q meets alpha limit or not; to ensure minimum operational maintenance cost and maximum operational service quality, respond to maintenance requirements with maximum commercial interest, and define the original planned route (direct response Q)yMaintenance request) as a response request QxRatio of the generated travel distances
Greater than a certain ratio, inserting a service request Q into the service status of the serviceman if the limit is satisfied;
3.3 if no maintainer meeting the conditions is found, performing insertion feasibility check according to the steps 3.1 and 3.2 by using the residual staff in the non-optimized maintainer candidate item set in the step (II); if no suitable maintainer is found, the task is dispatched to a spare, spare maintainer.
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