CN112241871A - Bus driver intelligent scheduling method based on segmentation and combination optimization - Google Patents

Bus driver intelligent scheduling method based on segmentation and combination optimization Download PDF

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CN112241871A
CN112241871A CN202011086792.0A CN202011086792A CN112241871A CN 112241871 A CN112241871 A CN 112241871A CN 202011086792 A CN202011086792 A CN 202011086792A CN 112241871 A CN112241871 A CN 112241871A
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任子晖
高洪昌
王晓娟
张超
赵玉坤
曹培宋
刘思琦
倪金林
潘宇
闫其筠
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Abstract

The invention discloses a bus driver intelligent scheduling method based on segmentation and combination optimization, which comprises the following steps of: the method comprises the following steps: acquiring a line basic data set, a passenger flow data set and an operation data set through a data acquisition module; step two: the method comprises the steps that a driving plan compiling model module analyzes and predicts the average driving time, the dispatching frequency and the dispatching interval of each peak section of a line under different dates and different weathers according to historical operation and passenger flow data, and then a model is built to generate an initial driving plan table by combining other basic static data in a data acquisition module; step three: and then, on the basis of an initial driving schedule, a combined optimization analysis module is used for carrying out constraint conditions such as standard working time of a driver every day, weight value of the standard working time and the like. The invention improves the balance degree of the work time of the driver shift scheduling plan, meets the standard of the work time of the driver to the maximum extent, and does not cause potential safety hazards such as overlong work, fatigue driving and the like.

Description

Bus driver intelligent scheduling method based on segmentation and combination optimization
Technical Field
The invention relates to the field of scheduling methods, in particular to a bus driver intelligent scheduling method based on segmentation and combination optimization.
Background
In the intelligent bus system, the core is the intelligent bus scheduling system, and the core of the bus scheduling system is the driving plan and the driver scheduling, which relates to the resource allocation optimization in various aspects such as people, vehicles, fields, stations, lines and the like, so the driving plan and the driver scheduling scheme and the result directly influence the management capability and the operation efficiency of the bus enterprise. However, most public transport enterprises in China still stay at the level of compiling a driving plan and scheduling drivers manually according to personal experience, the requirements of increasingly developed intelligent buses cannot be met, a lot of transportation universities and research institutes have extensive researches on the driving plan and the scheduling drivers, but products which can be really applied to the ground are few, so that the method for intelligently compiling the driving plan has important practical significance and economic value.
The existing intelligent scheduling method has the advantages that in the scheduling process, the balance degree of the scheduled shifts is not good enough, fatigue of a driver is easily caused, the scheduling is not intelligent enough, and certain influence is brought to the use of the scheduling method, so that the intelligent scheduling method for the bus driver based on the segmentation combination optimization is provided.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: how to solve the problems that in the existing intelligent scheduling method, the balance degree of the discharged shifts is not good enough in the scheduling process, the fatigue of a driver is easily caused, and the scheduling is not intelligent enough, so that a certain influence is brought to the use of the scheduling method, and the intelligent scheduling method for the bus driver based on the segmentation combination optimization is provided.
The invention solves the technical problems through the following technical scheme, and the invention comprises the following steps:
the method comprises the following steps: acquiring a line basic data set, a passenger flow data set and an operation data set through a data acquisition module;
step two: the method comprises the steps that a driving plan compiling model module analyzes and predicts the average driving time, the dispatching frequency and the dispatching interval of each peak section of a line under different dates and different weathers according to historical operation and passenger flow data, and then a model is built to generate an initial driving plan table by combining other basic static data in a data acquisition module;
step three: then, on the basis of the initial driving schedule, carrying out segmentation, combination and optimization on each guideboard and a train number chain thereof in the initial driving schedule according to the constraint conditions such as standard working time of a driver every day, a weight value and the like by a combination optimization analysis module, and searching out a relatively optimal combination result meeting one guideboard for one person according to a combined weight result value, namely that the working time of each guideboard in the driving schedule after optimization and combination is basically balanced;
step four: and finally, the intelligent driver scheduling module realizes the matching of the guideboard and a specific driver in the driving plan according to the optimally combined driving schedule of one guideboard by one person and the preference information of the driver on-off places and the like, and automatically generates the scheduling result of each driver.
Preferably, the line basic data set in the step one includes basic static data such as line head and end stations, line up-down length, operation time, stop time range of the head and end stations, and the like; and passenger flow, turnover time and other operation dynamic data in different time, station and direction.
Preferably, the content of the driving schedule in the second step includes each departure time point, the travel time, the stop time and the departure interval between the previous and next departure times of each road sign at the first and last stations;
the driving schedule can be regarded as an m × n matrix, m is the maximum number of guideboards, n is the maximum single number, F (i, j) refers to a departure time point F (i, j), an operation duration t (i, j) and a stop time delta (i, j) data set of each guideboard at each primary/secondary station, F (i, j) { F (i, j), t (i, j), delta (i, j) }, i ═ 1,2, …, m; j is 1,2, …, n;
wherein: f (i, j) ≠ phi, which indicates that a data set exists in the row and the column of the i; f (i, j) ═ Φ, which indicates that there is no data set in row i and column j, that is, it is null, and if F (i, j) is null, which indicates that the vehicle is in a stopped operation state, all the data in the data set are null, i ═ 1,2, …, m; j is 1,2, …, n;
according to the actual values in each F (i, j) set, the required operating times c of each guideboard can be calculatediAnd a required operation time tiSet of, wherein, ciIs equal to the sum of the number of all non-empty F (i, j), tiEqual to the sum of the operating time t (i, j) and the station-stopping time delta (i, j) in all non-empty F (i, j), i being 1,2, …, m; j is 1,2, …, n.
5. The specific processing process of the shift arrangement result in the third step is as follows:
setting the standard working time t of the driverΔWeight value ρ corresponding to 8Δ180, for any one of the divided and combined operating time lengths tγWeight value rho corresponding to its working timeγComprises the following steps:
Figure BDA0002720630740000031
for the bus route, the general maximum operation time is 18 hours, the total operation time of each original guideboard in the initial driving schedule is different, and the following two methods are adopted:
the method comprises the following steps: the total operation time of each original guideboard in the original driving schedule is more than or equal to hours, and then the guideboards are directly segmented according to the standard working time, and the specific processing process is as follows:
s1: starting from the 1 st F (1,1) of the 1 st guideboard in the original driving schedule, firstly selecting F (1,2) and F (1,1) to combine to form the 1 st division, dividing the 1 st guideboard into two segments, wherein F (1,1) and F (1,2) are the 1 st segment, the sum of the corresponding operation time lengths is known and is set as
Figure BDA0002720630740000032
F (1,3), F (1, n) is the 2 nd segment, the sum of the corresponding operating durations is known, set to
Figure BDA0002720630740000033
According to the previous working time length weight value calculation formula, the weight values of the working time lengths in the two sections can be calculated and are respectively set as
Figure BDA0002720630740000034
The result value of the 1 st combination is obtained
Figure BDA0002720630740000035
Then, 1 train number F (1,3) is added and selected to form a 2 nd division, the 1 st guideboard is divided into two sections, F (1,1), F (1,2) and F (1,3) are the 1 st section, the sum of the corresponding operation time lengths is known and is set as
Figure BDA0002720630740000036
F (1,4), F (1, n) is the 2 nd segment, the sum of the corresponding operating durations is known, set to
Figure BDA0002720630740000037
According to preceding working time length weightValue calculation formula, which can calculate the weight value of travel time in each segment, respectively
Figure BDA0002720630740000041
The result value of the 2 nd combination
Figure BDA0002720630740000042
Gradually increasing and selecting 1 non-empty F (1, j) each time, and each division has corresponding combination result value
Figure BDA0002720630740000043
r 1,2, …, n-1, until the last 1 non-empty F (1, j) of the 1 st signpost is selected, j 1,2, …, n; the sum of the operation time lengths corresponding to the 1 st segment after the last division is known and is set as
Figure BDA0002720630740000044
The operation time corresponding to the segmented 2 nd segment is 0, namely:
Figure BDA0002720630740000045
according to the previous working time length weight value calculation formula, the weight value of the running time length in the 1 st section can be calculated to be
Figure BDA0002720630740000046
The result value of the last 1 split combination
Figure BDA0002720630740000047
Selecting the division mode with the maximum combination result value after division for the 1 st guideboard, and preferentially selecting the section 1 with short working time after division when the two combination result values are the same;
s2: the steps are repeated from the 1 st F (i,1) of the ith guideboard in the original driving schedule in sequence, the optimal segmentation corresponding to each guideboard i is selected until the last guideboard is finished, and the segmentation of all the original schedules is completed to obtain the optimal segmentation of each guideboard;
s3: respectively placing all the segments containing the non-null values F (i, j) on the independent guideboards after the optimal segmentation to form a newly combined driving schedule, wherein the operation time of each guideboard in the newly combined driving schedule is relatively balanced;
step two: the total operation time length of the guideboard in the original driving schedule is less than tΔ8 hours, and the total operation time is less than tΔThe 8-hour guideboard has gamma, and gamma is more than or equal to 1 and less than m, then the combination algorithm is divided as follows:
SS 1: the total operation time length is less than tΔSelecting 8-hour gamma guideboards, and setting the selected guideboard as z, in which the 1 st non-null data and last non-null data are respectively F (z, j)0)、F(z,j1)，1≤j0＜j1≤n；
SS 2: considering that departure from the same departure station is required, departure from the jth1+3 starting at a single time, F (k, j) is selected from the other m-1 guideboards respectively1+3) and F (k, j)1+4) two data combined with the data set of the guideboard z to form m-1 combined results, namely m-1 combined working hours, and calculating corresponding weight values according to the combined working hours
Figure BDA0002720630740000051
k is 1,2, …, m-1, when F (k, j)1+3) the corresponding combined weight value when empty
Figure BDA0002720630740000052
F (k, j) is divided for other m-1 guideboards1+3) and F (k, j)1+4) the two pieces of data are divided into a front section and a rear section, each section corresponds to a working time length, if the working time length of any one of the two divided sections is greater than 0, the weight value of the two divided sections is calculated according to the working time lengths corresponding to the two divided sections, and the calculation is respectively as follows:
Figure BDA0002720630740000053
k is 1,2, …, m-1; then: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA0002720630740000054
k＝1,2,…,m-1；
if the working time length of one section in the two divided sections is 0, the weight value of the section with the working time length of 0 is the weight value of the other section and the combined weight value rhozk22The minimum value among, that is to say when: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA0002720630740000055
or
Figure BDA0002720630740000056
k=1,2,…m-1;
SS 3: continue from jth1+3 starting at a single time, F (k, j) is selected from the other m-1 guideboards respectively1+3)、F(k,j1+4)、F(k,j1+5)、F(k,j1+6) four data combined with the data set of the guideboard z to form m-1 combined results, namely m-1 combined working hours, and calculating corresponding weight values according to the combined working hours
Figure BDA0002720630740000057
k is 1,2, …, m-1, when F (k, j)1+3) the corresponding combined weight value when empty
Figure BDA0002720630740000058
F (k, j) is divided for other m-1 guideboards1+3)、F(k,j1+4)、F(k,j1+5)、F(k,j1+6) the four data are divided into a front section and a rear section, each section corresponds to a working time length, if the working time length of any one of the divided two sections is greater than 0, the weight value of the divided two sections is calculated according to the working time lengths corresponding to the divided two sections, and the calculation is respectively as follows:
Figure BDA0002720630740000059
k is 1,2, …, m-1; then: the guideboard z is divided into two from other m-1 guideboardsThe m-1 weight result values after the data are combined are as follows:
Figure BDA00027206307400000510
k＝1,2,…,m-1；
if the working time length of one section in the two divided sections is 0, the weight value of the section with the working time length of 0 is the weight value of the other section and the combined weight value
Figure BDA0002720630740000061
The minimum value among, that is to say when: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA0002720630740000062
or
Figure BDA0002720630740000063
k＝1,2,…,m-1；
SS 4: continue from jth1Starting at a single time, respectively selecting e data from other m-1 guideboards on the basis of the steps each time until F (k, n) is selected, ending the division, combining the data set of the guideboard z after each division to form m-1 combined results, namely the working time of m-1 combinations, and calculating corresponding weight values according to the combined working time
Figure BDA0002720630740000064
k is 1,2, …, m-1, when F (k, j)1+3) the corresponding combined weight value when empty
Figure BDA0002720630740000065
After corresponding data of other m-1 guideboards are respectively segmented, the guideboards are segmented into a front section and a rear section, each section corresponds to a working time, if the working time of any one of the two segmented sections is greater than 0, the weighted value of the guideboards is calculated according to the working time corresponding to the two segmented sections, and the weighted value is set as follows:
Figure BDA0002720630740000066
k is 1,2, …, m-1; then: after each division, the guideboard z divides e data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA0002720630740000067
k＝1,2,…,m-1；
if the working time length of one section in the two divided sections is 0, the weight value of the section with the working time length of 0 is the weight value of the other section and the combined weight value
Figure BDA0002720630740000068
The minimum value among, that is to say when: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA0002720630740000069
or
Figure BDA00027206307400000610
k＝1,2,…,m-1；
SS5 from jth1+5 starting at a single time, F (k, j) is selected from the other m-1 guideboards respectively1+5) and F (k, j)1+6) two data combined with the data set of the guideboard z to form m-1 combined results, namely m-1 combined working hours, and calculating corresponding weight values according to the combined working hours
Figure BDA00027206307400000611
k is 1,2, …, m-1, when F (k, j)1+5) the corresponding combined weight value when empty
Figure BDA00027206307400000612
F (k, j) is divided for other m-1 guideboards1+5) and F (k, j)1+6) the two pieces of data are divided into a front section and a rear section, each section corresponds to a working time length, if the working time length of any one of the two divided sections is greater than 0, the weight value of the two divided sections is calculated according to the working time lengths corresponding to the two divided sections, and the weight values are respectively set as follows:
Figure BDA0002720630740000071
k is 1,2, …, m-1; then: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA0002720630740000072
k＝1,2,…,m-1；
if the working time length of one section in the two divided sections is 0, the weight value of the section with the working time length of 0 is the weight value of the other section and the combined weight value
Figure BDA0002720630740000073
The minimum value among, that is to say when: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA0002720630740000074
or
Figure BDA0002720630740000075
k＝1,2,…,m-1；
SS 6: then from j0-3(j0> 4) selecting F (k, j) from the other m-1 guideboards, respectively, starting at a single time0-3) and F (k, j)0-4) combining the two data with the data set of the guideboard z to form m-1 combined results, i.e. m-1 combined working hours, and calculating corresponding weight values according to the combined working hours
Figure BDA0002720630740000076
k is 1,2, …, m-1, when F (k, j)0-3) when empty, corresponding combined weight values
Figure BDA0002720630740000077
F (k, j) is divided for other m-1 guideboards0-3) and F (k, j)0-4) after two data are divided into two sections, each section corresponding to an operating time, if the operating time of any one of the two sections is dividedIf the average value is greater than 0, calculating the weight value according to the working time length corresponding to the two segmented sections, and respectively setting the weight values as follows:
Figure BDA0002720630740000078
Figure BDA0002720630740000079
k is 1,2, …, m-1; then: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA00027206307400000710
k＝1,2,…,m-1；
if the working time length of one section in the two divided sections is 0, the weight value of the section with the working time length of 0 is the weight value of the other section and the combined weight value
Figure BDA00027206307400000711
The minimum value among, that is to say when: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA00027206307400000712
or
Figure BDA00027206307400000713
k＝1,2,…,m-1；
SS 7: repeating the steps for each guideboard z to sequentially obtain a weight result value after each division and combination;
SS 8: and then according to the working time of the guideboard z, calculating a result value of taking the guideboard z as 1 guideboard according to a working time weight value calculation formula, wherein the result value is as follows: omegazz＝ρzz×ρzz×ρzzZ is 1,2, …, γ, and for all the guideboards z, the corresponding combining weight results are
Figure BDA0002720630740000081
Searching out an optimal segmentation combination result from all the weight results to obtain the segmentation combination results of z guideboards;
SS9 that the total operation time length in the original driving schedule is more than or equal to tΔIf the 8-hour guideboard is not divided, the total operation time of each original guideboard in the original driving schedule is greater than or equal to tΔAnd (4) calculating the optimal result value of the guideboard segmentation as the 8-hour step, and obtaining the segmentation result of the guideboard.
Compared with the prior art, the invention has the following advantages: the intelligent bus driver scheduling method based on the segmentation combination optimization is characterized in that the daily working time balance of a driver is used as an index item for the segmentation combination optimization of a driving schedule, a driving schedule segmentation combination optimization model based on the working time balance is constructed, the balance of the working time of the driver scheduling plan is improved to a large extent, the working time standard of the driver is met to the maximum extent, potential safety hazards such as overlong work and fatigue driving are avoided, a multi-objective optimization model is established according to constraint conditions such as the daily standard working time of the driver and a weighted value of the standard working time of the driver, each road plate and a train number chain in an initial driving schedule are segmented, combined and optimized, a driving schedule meeting one road plate for one person is generated, and a feasible scheduling scheme meeting the daily standard working time of each driver to the maximum extent is provided.
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Detailed Description
The following examples are given for the detailed implementation and specific operation of the present invention, but the scope of the present invention is not limited to the following examples.
As shown in fig. 1, the present embodiment provides a technical solution: a bus driver intelligent scheduling method based on segmentation and combination optimization comprises the following steps:
the method comprises the following steps: acquiring a line basic data set, a passenger flow data set and an operation data set through a data acquisition module;
step two: the method comprises the steps that a driving plan compiling model module analyzes and predicts the average driving time, the dispatching frequency and the dispatching interval of each peak section of a line under different dates and different weathers according to historical operation and passenger flow data, and then a model is built to generate an initial driving plan table by combining other basic static data in a data acquisition module;
step three: then, on the basis of the initial driving schedule, carrying out segmentation, combination and optimization on each guideboard and a train number chain thereof in the initial driving schedule according to the constraint conditions such as standard working time of a driver every day, a weight value and the like by a combination optimization analysis module, and searching out a relatively optimal combination result meeting one guideboard for one person according to a combined weight result value, namely that the working time of each guideboard in the driving schedule after optimization and combination is basically balanced;
step four: and finally, the intelligent driver scheduling module realizes the matching of the guideboard and a specific driver in the driving plan according to the optimally combined driving schedule of one guideboard by one person and the preference information of the driver on-off places and the like, and automatically generates the scheduling result of each driver.
The line basic data set in the first step comprises basic static data of line head and end stations, line up-down length, operation time, station stop time range of the head and end stations and the like; and passenger flow, turnover time and other operation dynamic data in different time, station and direction.
The contents of the driving schedule in the second step comprise each guideboard at each departure time point, the driving time, the stop time and the departure interval between the front departure train number and the rear departure train number at the first station and the last station;
the initial driving schedule is as follows:
Figure BDA0002720630740000091
Figure BDA0002720630740000101
the driving schedule can be regarded as an m × n matrix, m is the maximum number of guideboards, n is the maximum single number, F (i, j) refers to a departure time point F (i, j), an operation duration t (i, j) and a stop time delta (i, j) data set of each guideboard at each primary/secondary station, F (i, j) { F (i, j), t (i, j), delta (i, j) }, i ═ 1,2, …, m; j is 1,2, …, n;
wherein: f (i, j) ≠ phi, which indicates that a data set exists in the row and the column of the i; f (i, j) ═ Φ, which indicates that there is no data set in row i and column j, that is, it is null, and if F (i, j) is null, which indicates that the vehicle is in a stopped operation state, all the data in the data set are null, i ═ 1,2, …, m; j is 1,2, …, n;
according to the actual values in each F (i, j) set, the required operating times c of each guideboard can be calculatediAnd a required operation time tiSet of, wherein, ciIs equal to the sum of the number of all non-empty F (i, j), tiEqual to the sum of the operating time t (i, j) and the station-stopping time delta (i, j) in all non-empty F (i, j), i being 1,2, …, m; j is 1,2, …, n.
According to the labor method, each driver works for 8 hours every day, the standard working time is the standard working time, the working time generally fluctuates up and down in the standard working time of 8 hours, the working time is unreasonable for the driver, and fatigue driving is easy to cause; if the time is too short, the number of drivers needs to be increased, and the bus operation cost is increased, so that the working time of each driver is unreasonable, the number of the vehicles and the working time of each guideboard in the initial driving plan are divided and combined, and the final combined result value is found out through the weighted value of the combined result, so that the working time of each guideboard in the final plan is relatively balanced, and the standard working time of the drivers can be met to a greater extent.
The specific processing process of the shift arrangement result in the third step is as follows:
setting the standard working time t of the driverΔWeight value ρ corresponding to 8Δ180, for any one of the divided and combined operating time lengths tγWeight value rho corresponding to its working timeγComprises the following steps:
Figure BDA0002720630740000111
for the bus route, the general maximum operation time is 18 hours, the total operation time of each original guideboard in the initial driving schedule is different, and the following two methods are adopted:
the method comprises the following steps: the total operation time of each original guideboard in the original driving schedule is more than or equal to hours, and then the guideboards are directly segmented according to the standard working time, and the specific processing process is as follows:
s1: starting from the 1 st F (1,1) of the 1 st guideboard in the original driving schedule, firstly selecting F (1,2) and F (1,1) to combine to form the 1 st division, dividing the 1 st guideboard into two segments, wherein F (1,1) and F (1,2) are the 1 st segment, the sum of the corresponding operation time lengths is known and is set as
Figure BDA0002720630740000112
F (1,3), F (1, n) is the 2 nd segment, the sum of the corresponding operating durations is known, set to
Figure BDA0002720630740000113
According to the previous working time length weight value calculation formula, the weight values of the working time lengths in the two sections can be calculated and are respectively set as
Figure BDA0002720630740000114
The result value of the 1 st combination is obtained
Figure BDA0002720630740000115
Then, 1 train number F (1,3) is added and selected to form a 2 nd division, the 1 st guideboard is divided into two sections, F (1,1), F (1,2) and F (1,3) are the 1 st section, the sum of the corresponding operation time lengths is known and is set as
Figure BDA0002720630740000116
F (1,4), F (1, n) is the 2 nd segment, the sum of the corresponding operating durations is known, set to
Figure BDA0002720630740000117
According to the previous working duration weighted value calculation formula, the weighted value of the running time in each section can be calculated, namely
Figure BDA0002720630740000118
The result value of the 2 nd combination
Figure BDA0002720630740000119
Gradually increasing and selecting 1 non-empty F (1, j) each time, and each division has corresponding combination result value
Figure BDA00027206307400001110
r 1,2, …, n-1, until the last 1 non-empty F (1, j) of the 1 st signpost is selected, j 1,2, …, n; the sum of the operation time lengths corresponding to the 1 st segment after the last division is known and is set as
Figure BDA00027206307400001111
The operation time corresponding to the segmented 2 nd segment is 0, namely:
Figure BDA00027206307400001112
according to the previous working time length weight value calculation formula, the weight value of the running time length in the 1 st section can be calculated to be
Figure BDA00027206307400001113
The result value of the last 1 split combination
Figure BDA0002720630740000121
Selecting the division mode with the maximum combination result value after division for the 1 st guideboard, and preferentially selecting the section 1 with short working time after division when the two combination result values are the same;
s2: the steps are repeated from the 1 st F (i,1) of the ith guideboard in the original driving schedule in sequence, the optimal segmentation corresponding to each guideboard i is selected until the last guideboard is finished, and the segmentation of all the original schedules is completed to obtain the optimal segmentation of each guideboard;
s3: respectively placing all the segments containing the non-null values F (i, j) on the independent guideboards after the optimal segmentation to form a newly combined driving schedule, wherein the operation time of each guideboard in the newly combined driving schedule is relatively balanced;
step two: the total operation time length of the guideboard in the original driving schedule is less than tΔ8 hours, and the total operation time is less than tΔThe 8-hour guideboard has gamma, and gamma is more than or equal to 1 and less than m, then the combination algorithm is divided as follows:
SS 1: the total operation time length is less than tΔSelecting 8-hour gamma guideboards, and setting the selected guideboard as z, in which the 1 st non-null data and last non-null data are respectively F (z, j)0)、F(z,j1)，1≤j0＜j1≤n；
SS 2: considering that departure from the same departure station is required, departure from the jth1+3 starting at a single time, F (k, j) is selected from the other m-1 guideboards respectively1+3) and F (k, j)1+4) two data combined with the data set of the guideboard z to form m-1 combined results, namely m-1 combined working hours, and calculating corresponding weight values according to the combined working hours
Figure BDA0002720630740000122
k is 1,2, …, m-1, when F (k, j)1+3) the corresponding combined weight value when empty
Figure BDA0002720630740000123
F (k, j) is divided for other m-1 guideboards1+3) and F (k, j)1+4) the two pieces of data are divided into a front section and a rear section, each section corresponds to a working time length, if the working time length of any one of the two divided sections is greater than 0, the weight value of the two divided sections is calculated according to the working time lengths corresponding to the two divided sections, and the calculation is respectively as follows:
Figure BDA0002720630740000124
k is 1,2, …, m-1; then: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA0002720630740000125
k＝1,2,…,m-1；
if the working time length of one section in the two divided sections is 0, the weight value of the section with the working time length of 0 is the weight value of the other section and the combined weight value
Figure BDA0002720630740000131
The minimum value among, that is to say when: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA0002720630740000132
or
Figure BDA0002720630740000133
k＝1,2,…,m-1；
SS 3: continue from jth1+3 starting at a single time, F (k, j) is selected from the other m-1 guideboards respectively1+3)、F(k,j1+4)、F(k,j1+5)、F(k,j1+6) four data combined with the data set of the guideboard z to form m-1 combined results, namely m-1 combined working hours, and calculating corresponding weight values according to the combined working hours
Figure BDA0002720630740000134
k is 1,2, …, m-1, when F (k, j)1+3) the corresponding combined weight value when empty
Figure BDA0002720630740000135
F (k, j) is divided for other m-1 guideboards1+3)、F(k,j1+4)、F(k,j1+5)、F(k,j1+6) the four data are divided into a front section and a rear section, each section corresponds to a working time length, if the working time length of any one of the divided two sections is greater than 0, the weight value of the divided two sections is calculated according to the working time lengths corresponding to the divided two sections, and the calculation is respectively as follows:
Figure BDA0002720630740000136
k is 1,2, …, m-1; then: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA0002720630740000137
k＝1,2,…,m-1；
if the working time length of one section in the two divided sections is 0, the weight value of the section with the working time length of 0 is the weight value of the other section and the combined weight value
Figure BDA0002720630740000138
The minimum value among, that is to say when: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA0002720630740000139
or
Figure BDA00027206307400001310
k＝1,2,…,m-1；
SS 4: continue from jth1Starting at a single time, respectively selecting e data from other m-1 guideboards on the basis of the steps each time until F (k, n) is selected, ending the division, combining the data set of the guideboard z after each division to form m-1 combined results, namely the working time of m-1 combinations, and calculating corresponding weight values according to the combined working time
Figure BDA00027206307400001311
k is 1,2, …, m-1, when F (k, j)1+3) the corresponding combined weight value when empty
Figure BDA0002720630740000141
After corresponding data of other m-1 guideboards are respectively segmented, the guideboards are segmented into a front section and a rear section, each section corresponds to a working time, if the working time of any one of the two segmented sections is greater than 0, the weighted value of the guideboards is calculated according to the working time corresponding to the two segmented sections, and the weighted value is set as follows:
Figure BDA0002720630740000142
k is 1,2, …, m-1; then: after each division, the guideboard z divides e data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA0002720630740000143
k＝1,2,…,m-1；
if the working time length of one section in the two divided sections is 0, the weight value of the section with the working time length of 0 is the weight value of the other section and the combined weight value
Figure BDA0002720630740000144
The minimum value among, that is to say when: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA0002720630740000145
or
Figure BDA0002720630740000146
k＝1,2,…,m-1；
SS5 from jth1+5 starting at a single time, F (k, j) is selected from the other m-1 guideboards respectively1+5) and F (k, j)1+6) two data combined with the data set of the guideboard z to form m-1 combined results, namely m-1 combined working hours, and calculating corresponding weight values according to the combined working hours
Figure BDA0002720630740000147
k is 1,2, …, m-1, when F (k, j)1+5) the corresponding combined weight value when empty
Figure BDA0002720630740000148
F (k, j) is divided for other m-1 guideboards1+5) and F (k, j)1+6) two data, it will be divided into two sections, each section corresponds to a working time, if the working time of any one of the two sections is greater than 0, then according to the corresponding working of the two sectionsCalculating the weighted value of the duration, and respectively setting as follows:
Figure BDA0002720630740000149
k is 1,2, …, m-1; then: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA00027206307400001410
k＝1,2,…,m-1；
if the working time length of one section in the two divided sections is 0, the weight value of the section with the working time length of 0 is the weight value of the other section and the combined weight value
Figure BDA00027206307400001411
The minimum value among, that is to say when: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA00027206307400001412
or
Figure BDA00027206307400001413
k＝1,2,…,m-1；
SS 6: then from j0-3(j0> 4) selecting F (k, j) from the other m-1 guideboards, respectively, starting at a single time0-3) and F (k, j)0-4) combining the two data with the data set of the guideboard z to form m-1 combined results, i.e. m-1 combined working hours, and calculating corresponding weight values according to the combined working hours
Figure BDA0002720630740000151
k is 1,2, …, m-1, when F (k, j)0-3) when empty, corresponding combined weight values
Figure BDA0002720630740000152
F (k, j) is divided for other m-1 guideboards0-3) and F (k, j)04) after two data, the data are divided into two sections, each section corresponds to one working time length, if the two sections are not identical, the working time length is not equal to the working time lengthIf the working time of any one of the two segmented sections is greater than 0, calculating the weight value according to the working time corresponding to the two segmented sections, and setting the weights as follows:
Figure BDA0002720630740000153
Figure BDA0002720630740000154
k is 1,2, …, m-1; then: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA0002720630740000155
k＝1,2,…,m-1；
if the working time length of one section in the two divided sections is 0, the weight value of the section with the working time length of 0 is the weight value of the other section and the combined weight value
Figure BDA0002720630740000156
The minimum value among, that is to say when: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure BDA0002720630740000157
or
Figure BDA0002720630740000158
k＝1,2,…,m-1；
SS 7: repeating the steps for each guideboard z to sequentially obtain a weight result value after each division and combination;
SS 8: and then according to the working time of the guideboard z, calculating a result value of taking the guideboard z as 1 guideboard according to a working time weight value calculation formula, wherein the result value is as follows: omegazz＝ρzz×ρzz×ρzzZ is 1,2, …, γ, and for all the guideboards z, the corresponding combining weight results are
Figure BDA0002720630740000159
Searching out optimal segmentation combination knot from all weight resultsObtaining the segmentation combination results of the z guideboards;
SS9 that the total operation time length in the original driving schedule is more than or equal to tΔIf the 8-hour guideboard is not divided, the total operation time of each original guideboard in the original driving schedule is greater than or equal to tΔAnd (4) calculating the optimal result value of the guideboard segmentation as the 8-hour step, and obtaining the segmentation result of the guideboard.
In summary, the information collected by the data collection module of the present invention includes a line basic data set, a passenger flow data set, and an operation data set, the driving schedule compiling model module analyzes and predicts the average driving time, the departure frequency, and the departure interval of each peak section of the line on different dates and different weathers according to the historical operation and passenger flow data, and then establishes a model to generate an initial driving schedule by combining with other basic static data in the data collection module, the combination optimization analysis module generates an initial driving schedule according to the constraint conditions such as the standard working time and the weight value of the driver each day on the basis of the initial driving schedule, carrying out segmentation combination optimization on each guideboard and the train number chain thereof in the initial driving schedule, and searching out a relatively optimal combination result meeting one guideboard for one person according to a combined weight result value, namely that the working time of each guideboard in the driving schedule after the combination is optimized is basically balanced; the intelligent driver scheduling module realizes the matching of the guideboard and a specific driver in the driving plan according to the optimally combined running schedule of one person and one guideboard and the preference information of the driver on-off places and the like, and automatically generates the scheduling result of each driver.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.

Claims (4)

1. A bus driver intelligent scheduling method based on segmentation and combination optimization is characterized by comprising the following steps:
the method comprises the following steps: acquiring a line basic data set, a passenger flow data set and an operation data set through a data acquisition module;
step two: the method comprises the steps that a driving plan compiling model module analyzes and predicts the average driving time, the dispatching frequency and the dispatching interval of each peak section of a line under different dates and different weathers according to historical operation and passenger flow data, and then a model is built to generate an initial driving plan table by combining other basic static data in a data acquisition module;
step three: then, on the basis of the initial driving schedule, carrying out segmentation, combination and optimization on each guideboard and a train number chain thereof in the initial driving schedule according to the constraint conditions such as standard working time of a driver every day, a weight value and the like by a combination optimization analysis module, and searching out a relatively optimal combination result meeting one guideboard for one person according to a combined weight result value, namely that the working time of each guideboard in the driving schedule after optimization and combination is basically balanced;
step four: and finally, the intelligent driver scheduling module realizes the matching of the guideboard and a specific driver in the driving plan according to the optimally combined driving schedule of one guideboard by one person and the preference information of the driver on-off places and the like, and automatically generates the scheduling result of each driver.
2. The intelligent bus driver scheduling method based on segmentation and combination optimization as claimed in claim 1, wherein: the line basic data set in the first step comprises basic static data of line head and end stations, line up-down length, operation time, station stop time range of the head and end stations and the like; and passenger flow, turnover time and other operation dynamic data in different time, station and direction.
3. The intelligent bus driver scheduling method based on segmentation and combination optimization as claimed in claim 1, wherein: the contents of the driving schedule in the second step comprise each guideboard at each departure time point, the driving time, the stop time and the departure interval between the front departure train number and the rear departure train number at the first station and the last station;
the driving schedule can be regarded as an m × n matrix, m is the maximum number of guideboards, n is the maximum single number, F (i, j) refers to a departure time point F (i, j), an operation duration t (i, j) and a stop time delta (i, j) data set of each guideboard at each primary/secondary station, F (i, j) { F (i, j), t (i, j), delta (i, j) }, i ═ 1,2, …, m; j is 1,2, …, n;
wherein: f (i, j) ≠ phi, which indicates that a data set exists in the row and the column of the i; f (i, j) ═ Φ, which indicates that there is no data set in row i and column j, that is, it is null, and if F (i, j) is null, which indicates that the vehicle is in a stopped operation state, all the data in the data set are null, i ═ 1,2, …, m; j is 1,2, …, n;
according to the actual values in each F (i, j) set, the required operating times c of each guideboard can be calculatediAnd a required operation time tiSet of, wherein, ciIs equal to the sum of the number of all non-empty F (i, j), tiEqual to the operation time t (i, j) and the station stop time in all non-empty F (i, j)Δ (i, j), i ═ 1,2, …, m; j is 1,2, …, n.
4. The intelligent bus driver scheduling method based on segmentation and combination optimization as claimed in claim 1, wherein: the specific processing process of the shift arrangement result in the third step is as follows:
setting the standard working time t of the driverΔWeight value ρ corresponding to 8Δ180, for any one of the divided and combined operating time lengths tγWeight value rho corresponding to its working timeγComprises the following steps:
Figure FDA0002720630730000021
for the bus route, the general maximum operation time is 18 hours, the total operation time of each original guideboard in the initial driving schedule is different, and the following two methods are adopted:
the method comprises the following steps: the total operation time of each original guideboard in the original driving schedule is more than or equal to hours, and then the guideboards are directly segmented according to the standard working time, and the specific processing process is as follows:
s1: starting from the 1 st F (1,1) of the 1 st guideboard in the original driving schedule, firstly selecting F (1,2) and F (1,1) to combine to form the 1 st division, dividing the 1 st guideboard into two segments, wherein F (1,1) and F (1,2) are the 1 st segment, the sum of the corresponding operation time lengths is known and is set as
Figure FDA0002720630730000022
F (1,3), F (1, n) is the 2 nd segment, the sum of the corresponding operating durations is known, set to
Figure FDA0002720630730000023
According to the previous working time length weight value calculation formula, the weight values of the working time lengths in the two sections can be calculated and are respectively set as
Figure FDA0002720630730000031
The result of the 1 st combination is obtainedValue of
Figure FDA0002720630730000032
Then, 1 train number F (1,3) is added and selected to form a 2 nd division, the 1 st guideboard is divided into two sections, F (1,1), F (1,2) and F (1,3) are the 1 st section, the sum of the corresponding operation time lengths is known and is set as
Figure FDA0002720630730000033
F (1,4), F (1, n) is the 2 nd segment, the sum of the corresponding operating durations is known, set to
Figure FDA0002720630730000034
According to the previous working duration weighted value calculation formula, the weighted value of the running time in each section can be calculated, namely
Figure FDA0002720630730000035
The result value of the 2 nd combination
Figure FDA0002720630730000036
Gradually increasing and selecting 1 non-empty F (1, j) each time, and each division has corresponding combination result value
Figure FDA0002720630730000037
Until the last 1 non-empty F (1, j) of the 1 st guideboard is selected, j is 1,2, …, n; the sum of the operation time lengths corresponding to the 1 st segment after the last division is known and is set as
Figure FDA0002720630730000038
The operation time corresponding to the segmented 2 nd segment is 0, namely:
Figure FDA0002720630730000039
according to the previous working time length weight value calculation formula, the weight value of the running time length in the 1 st section can be calculated to be
Figure FDA00027206307300000310
The result value of the last 1 split combination
Figure FDA00027206307300000311
Selecting the division mode with the maximum combination result value after division for the 1 st guideboard, and preferentially selecting the section 1 with short working time after division when the two combination result values are the same;
s2: the steps are repeated from the 1 st F (i,1) of the ith guideboard in the original driving schedule in sequence, the optimal segmentation corresponding to each guideboard i is selected until the last guideboard is finished, and the segmentation of all the original schedules is completed to obtain the optimal segmentation of each guideboard;
s3: respectively placing all the segments containing the non-null values F (i, j) on the independent guideboards after the optimal segmentation to form a newly combined driving schedule, wherein the operation time of each guideboard in the newly combined driving schedule is relatively balanced;
step two: the total operation time length of the guideboard in the original driving schedule is less than tΔ8 hours, and the total operation time is less than tΔThe 8-hour guideboard has gamma, and gamma is more than or equal to 1 and less than m, then the combination algorithm is divided as follows:
SS 1: the total operation time length is less than tΔSelecting 8-hour gamma guideboards, and setting the selected guideboard as z, in which the 1 st non-null data and last non-null data are respectively F (z, j)0)、F(z,j1)，1≤j0＜j1≤n；
SS 2: considering that departure from the same departure station is required, departure from the jth1+3 starting at a single time, F (k, j) is selected from the other m-1 guideboards respectively1+3) and F (k, j)1+4) two data combined with the data set of the guideboard z to form m-1 combined results, namely m-1 combined working hours, and calculating corresponding weight values according to the combined working hours
Figure FDA0002720630730000041
When F (k, j)1+3) the corresponding combined weight value when empty
Figure FDA0002720630730000042
F (k, j) is divided for other m-1 guideboards1+3) and F (k, j)1+4) the two pieces of data are divided into a front section and a rear section, each section corresponds to a working time length, if the working time length of any one of the two divided sections is greater than 0, the weight value of the two divided sections is calculated according to the working time lengths corresponding to the two divided sections, and the calculation is respectively as follows:
Figure FDA0002720630730000043
then: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure FDA0002720630730000044
Figure FDA0002720630730000045
if the working time length of one section in the two divided sections is 0, the weight value of the section with the working time length of 0 is the weight value of the other section and the combined weight value
Figure FDA0002720630730000046
The minimum value among, that is to say when: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure FDA0002720630730000047
or
Figure FDA0002720630730000048
SS 3: continue from jth1+3 starting at a single time, F (k, j) is selected from the other m-1 guideboards respectively1+3)、F(k,j1+4)、F(k,j1+5)、F(k,j1+6) four data combined with the data set of the guideboard z to form m-1 combined results, namely m-1 combined working hours, and calculating corresponding weight values according to the combined working hours
Figure FDA0002720630730000049
When F (k, j)1+3) the corresponding combined weight value when empty
Figure FDA00027206307300000410
F (k, j) is divided for other m-1 guideboards1+3)、F(k,j1+4)、F(k,j1+5)、F(k,j1+6) the four data are divided into a front section and a rear section, each section corresponds to a working time length, if the working time length of any one of the divided two sections is greater than 0, the weight value of the divided two sections is calculated according to the working time lengths corresponding to the divided two sections, and the calculation is respectively as follows:
Figure FDA0002720630730000051
then: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure FDA0002720630730000052
if the working time length of one section in the two divided sections is 0, the weight value of the section with the working time length of 0 is the weight value of the other section and the combined weight value
Figure FDA0002720630730000053
The minimum value among, that is to say when: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure FDA0002720630730000054
or
Figure FDA0002720630730000055
SS 4: continue from jth1Starting at a single time, respectively selecting e data from other m-1 guideboards on the basis of the steps each time until F (k, n) is selected, ending the division, combining the data set of the guideboard z after each division to form m-1 combined results, namely the working time of m-1 combinations, and calculating corresponding weight values according to the combined working time
Figure FDA0002720630730000056
When F (k, j)1+3) the corresponding combined weight value when empty
Figure FDA0002720630730000057
After corresponding data of other m-1 guideboards are respectively segmented, the guideboards are segmented into a front section and a rear section, each section corresponds to a working time, if the working time of any one of the two segmented sections is greater than 0, the weighted value of the guideboards is calculated according to the working time corresponding to the two segmented sections, and the weighted value is set as follows:
Figure FDA0002720630730000058
then: after each division, the guideboard z divides e data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure FDA0002720630730000059
Figure FDA00027206307300000510
if the working time length of one section in the two divided sections is 0, the weight value of the section with the working time length of 0 is the weight value of the other section and the combined weight value
Figure FDA00027206307300000511
The minimum value among, that is to say when: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure FDA00027206307300000512
or
Figure FDA00027206307300000513
SS5 from jth1+5 starting at a single time, F (k, j) is selected from the other m-1 guideboards respectively1+5) and F (k, j)1+6) two data combined with the data set of the guideboard z to form m-1 combined results, namely m-1 combined working hours, and calculating corresponding weight values according to the combined working hours
Figure FDA0002720630730000061
Figure FDA0002720630730000062
When F (k, j)1+5) the corresponding combined weight value when empty
Figure FDA0002720630730000063
F (k, j) is divided for other m-1 guideboards1+5) and F (k, j)1+6) the two pieces of data are divided into a front section and a rear section, each section corresponds to a working time length, if the working time length of any one of the two divided sections is greater than 0, the weight value of the two divided sections is calculated according to the working time lengths corresponding to the two divided sections, and the weight values are respectively set as follows:
Figure FDA0002720630730000064
Figure FDA0002720630730000065
then: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure FDA0002720630730000066
if the working time length of one of the two divided segments is 0,the weighted value of the section with the working time length of 0 is selected from the weighted value of the other section and the combined weighted value
Figure FDA0002720630730000067
The minimum value among, that is to say when: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure FDA0002720630730000068
or
Figure FDA0002720630730000069
SS 6: then from j0-3(j0> 4) selecting F (k, j) from the other m-1 guideboards, respectively, starting at a single time0-3) and F (k, j)0-4) combining the two data with the data set of the guideboard z to form m-1 combined results, i.e. m-1 combined working hours, and calculating corresponding weight values according to the combined working hours
Figure FDA00027206307300000610
When F (k, j)0-3) when empty, corresponding combined weight values
Figure FDA00027206307300000611
F (k, j) is divided for other m-1 guideboards0-3) and F (k, j)0-4) after the two pieces of data are divided into a front section and a rear section, each section corresponds to a working time length, if the working time length of any one of the divided two sections is greater than 0, the weight value of each section is calculated according to the working time length corresponding to the divided two sections, and the calculation is respectively as follows:
Figure FDA00027206307300000612
Figure FDA00027206307300000613
then: the guideboard z divides two data from other m-1 guideboards and combines themThe m-1 weight result values of (a) are:
Figure FDA00027206307300000614
if the working time length of one section in the two divided sections is 0, the weight value of the section with the working time length of 0 is the weight value of the other section and the combined weight value
Figure FDA00027206307300000615
The minimum value among, that is to say when: the guideboard z divides two data from other m-1 guideboards respectively, and m-1 weight result values after combination are as follows:
Figure FDA0002720630730000071
or
Figure FDA0002720630730000072
SS 7: repeating the steps for each guideboard z to sequentially obtain a weight result value after each division and combination;
SS 8: and then according to the working time of the guideboard z, calculating a result value of taking the guideboard z as 1 guideboard according to a working time weight value calculation formula, wherein the result value is as follows: omegazz＝ρzz×ρzz×ρzzZ is 1,2, …, γ, and for all the guideboards z, the corresponding combining weight results are
Figure FDA0002720630730000073
Searching out an optimal segmentation combination result from all the weight results to obtain the segmentation combination results of z guideboards;
SS9 that the total operation time length in the original driving schedule is more than or equal to tΔIf the 8-hour guideboard is not divided, the total operation time of each original guideboard in the original driving schedule is greater than or equal to tΔAnd (4) calculating the optimal result value of the guideboard segmentation as the 8-hour step, and obtaining the segmentation result of the guideboard.
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