CN108960539B - Demand response type connection bus route optimization method - Google Patents

Demand response type connection bus route optimization method Download PDF

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CN108960539B
CN108960539B CN201811008237.9A CN201811008237A CN108960539B CN 108960539 B CN108960539 B CN 108960539B CN 201811008237 A CN201811008237 A CN 201811008237A CN 108960539 B CN108960539 B CN 108960539B
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CN108960539A (en
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李文权
卢云雪
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Southeast University
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Abstract

The invention discloses a demand response type connection bus route optimization method, which comprises the following steps: 1) constructing a mutual constraint relation of the passenger trip time parameters; 2) judging passenger compatibility, constructing a corresponding compatibility matrix, and finding out a maximum incompatible passenger set to obtain the number of initially required vehicles and seed passengers of each initial path; 3) determining a path neighborhood of each passenger, searching feasible insertion for each passenger in the path of the passenger in the path neighborhood, determining the optimal insertion of the passenger in the neighborhood path, and realizing the preliminary planning of the path; 4) and repeating the steps 2-3 for passengers who cannot be inserted into the existing path until the number of remaining passengers or the passenger carrying rate of the obtained path is lower than a specified threshold value. The method fully utilizes the mutual constraint relation of the travel time parameters of the passengers in the same train, provides the concept of the path neighborhood to reduce the feasible solution search domain, and improves the algorithm solving efficiency so as to construct the multi-vehicle multi-path driving plan with high efficiency and low cost.

Description

Demand response type connection bus route optimization method
Technical Field
The invention belongs to the field of urban public transport, and particularly relates to a demand response type connection bus route optimization method which is suitable for suburb areas with low demand density and instability.
Background
In the face of increasingly severe traffic congestion, governments have strongly promoted the development of mass transit systems, particularly mass transit systems such as subways, light and ground trams, BRTs and the like. The large-capacity public transport and the conventional public transport have larger passenger carrying capacity, good passenger ride sharing performance and lower running cost, so that passengers in urban central areas with dense population feel good, and certain economic benefit is brought. However, due to the acceleration of the urbanization process and the expansion of cities, the demand of coming and going to the central area and suburbs of the cities is increased, the travel distance is increased, and the travel places are scattered, so that the service range of a public transport hub station (hereinafter referred to as "hub end") at the suburb end is limited, the passenger flow is reduced, and the traffic resources are not reasonably utilized. The travel characteristics of suburb areas determine that the conventional public transport cannot provide good connection service for people to and from public transport hub stations. Demand response type public transit adopts the mode of demand response, for people provide the service of plugging into of door to door, makes the diversified trip demand of passenger obtain good the satisfying, for the service range of large capacity public transportation systems such as extension track traffic in suburb end, improves the passenger carrying rate, alleviates the traffic jam and the difficult problem of suburb website parking of early and late peak at city access & exit and provides an effectual way. However, the current research on demand response type connection bus route planning at home and abroad lacks deep analysis on the mutual constraint relation of passengers in the same bus, and the essential analysis of problems is insufficient; when a vehicle driving path is established, a time window of a passenger at the beginning and the end of the trip is not considered at the same time, the problems of vehicle multipath and the like are not considered, so that the vehicle investment is high, the user satisfaction is low, and the resource waste exists, therefore, the efficiency and the resolving quality of the current method need to be improved, and the connection bus path planning with higher efficiency and lower cost is obtained.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the problems in the prior art, the invention provides a demand response type connection bus route optimization method, which can obtain connection bus route planning with higher efficiency and lower cost.
The technical scheme is as follows: the invention relates to a demand response type connection bus route optimization method, which comprises the following steps:
(1) calculating passenger travel time parameters according to the passenger appointment time and the passenger appointment place, and constructing a mutual constraint relation of the passenger travel time parameters;
(2) judging passenger compatibility based on the passenger travel time parameters, constructing a corresponding compatibility matrix, and finding out a maximum incompatible passenger set to obtain the number of initial required vehicles and seed passengers of each initial path;
(3) determining a path neighborhood of each passenger according to the maximum incompatible passenger set, searching feasible insertion for the path of each passenger in the path neighborhood of each passenger, determining the optimal insertion of the passenger in each neighborhood path of each passenger by calculating the regret value, and realizing the primary planning of the path;
(4) and (5) repeating the steps (2) - (3) for the passengers which cannot be inserted into the existing path until the number of the remaining passengers is lower than a specified threshold or the passenger carrying rate of the obtained path is lower than a specified threshold.
The specific method of the step (1) is as follows:
(11) the passengers are divided into two types according to different directions of coming from and going from the public transport junction station, the passengers going to the junction end from various places are P-type passengers, the passengers going back to the various places from the junction station are D-type passengers, when the passengers reserve the receiving and delivering service, the expected service time and place of each passenger need to be appointed, the P-type passengers are supposed to only pay attention to the time of arriving at the junction end, the D-type passengers pay attention to the time of departing from the junction station, and the P-type passengers i are rememberedkThe latest arrival time at the junction end, i.e. the latest getting-off time is LDTikClass D passenger jrThe earliest departure time from the junction end, namely the earliest boarding time is EPTjr(ii) a The width of the service change time window acceptable by the two types of passengers at the terminal is set as w by the public transport company; the shortest travel time for class P and class D passengers is DRTik、DRTjrThe longest travel time is MRTik、MRTjr；
(12) Calculating the travel time parameter of the passenger:
for class P passengers there are:
Figure BDA0001784466880000021
Figure BDA0001784466880000022
Figure BDA0001784466880000027
wherein, EDTik、LPTik、EPTikRespectively P-class passengers ikThe earliest getting-off time, the latest getting-on time and the earliest getting-on time of the vehicle;
for class D passengers there are:
Figure BDA0001784466880000023
Figure BDA0001784466880000024
Figure BDA0001784466880000025
wherein LPTjr、EDTjr、LDTjrClass D passengers jrThe latest getting-on time, the earliest getting-off time and the latest getting-off time;
(13) constructing a constraint relation of travel time parameters of passengers in the same train:
Figure BDA0001784466880000026
Figure BDA0001784466880000031
then [ EATO g,LATO g]Showing the slave axis of the vehicle gDeparture time window, EAT, for departure evacuation of class D passengers at New stationO gAnd LATO gRespectively earliest departure time and latest departure time; [ EAT ]D m,LATD m]An arrival time window, EAT, representing the arrival of a vehicle at a junction station when m blocks a class P passengerD mAnd LATD mRespectively the earliest arrival time and the latest arrival time; pmAnd PgRepresenting the set of passengers serviced by vehicle m and vehicle g, respectively.
The passenger compatibility judgment in the step (2) comprises the compatibility judgment of the junction end and the compatibility judgment of the non-junction end, and only when the compatibility judgment results of the junction end and the non-junction end of two passengers are compatible, the two passengers are considered to be compatible and can be served by the same vehicle, wherein,
for any two P-class passengers ikAnd irAnd the pivot end compatibility judgment condition is as follows:
Figure BDA0001784466880000032
wherein (EDT)ik，LDTik) And (EDT)ir，LDTir) Are respectively passengers ikAnd irThe earliest getting-off time and the latest getting-off time when arriving at a hub station;
the compatibility determination conditions of the non-pivot terminal are as follows:
first-serve passenger ikRe-service passenger irWhen it is satisfied
Figure BDA0001784466880000033
Or serve passenger i firstrRe-service passenger ikWhen it is satisfied
Figure BDA0001784466880000034
Wherein (EPT)ik，LPTik) And (EPT)ir，LPTir) Are respectively passengers ikAnd irThe earliest time of getting on the bus and the latest time of getting on the bus when arriving at the hub station; t is tkr pFor vehicle slave passenger ikTo passenger irTravel time of department, trk pFor vehicle slave passenger irTo passenger ikTravel time of department, tkr p＝trk p；
For any two class D passengers jkAnd jrAnd the compatibility judgment condition of the pivot end is as follows:
Figure BDA0001784466880000035
wherein (EPT)jk，LPTjk) And (EPT)jr，LPTjr) Are respectively passenger jkAnd passenger jrThe earliest getting-on time and the latest getting-on time from the hub end;
the compatibility determination conditions of the non-pivot terminal are as follows:
when the passenger jkTo passenger jrWhen it is satisfied
Figure BDA0001784466880000036
Or by passenger jrTo passenger jkWhen it is satisfied
Figure BDA0001784466880000037
Wherein (EDT)jk，LDTjk) And (EDT)jr，LDTjr) Are respectively passenger jkAnd jrThe earliest time of alighting from the vehicle and the latest time of alighting from the vehicle, tkr dFor vehicle slave passenger jkTo passenger jrTime of trip between, trk dFor vehicle slave passenger jrTo passenger jkTime of trip between, tkr d＝trk d。
The method for constructing the passenger compatibility matrix in the step (2) is as follows: the passengers are used as rows and columns to construct a matrix, the compatibility judgment result between the passengers is used as a matrix element, when two passengers are compatible, the value of the corresponding element in the matrix is 1, otherwise, the value is 0.
The method of determining the maximum incompatible passenger set is as follows:
2a) selecting a column or a row with the most 0 elements, marking the column or the row and the corresponding row or column, and then dividing the row and the column corresponding to the element with the value of 1 in the column or the row;
2b) repeating the step 2a) until all the columns or rows are marked or scratched, wherein passengers corresponding to the marked columns or rows form incompatible passenger sets;
2c) and sequentially arranging all the columns or rows as initial mark columns or rows, carrying out the steps for multiple times, and taking the maximum number of the elements of the incompatible set as the maximum incompatible set omega. In the step (3), the path neighborhood determination method is as follows: after the maximum incompatible set is determined, each passenger in the set corresponds to one initial path, each initial path is served by one vehicle, the passenger in the service path starts from the junction station, and then returns to the junction station; in the passenger compatibility matrix, except for the seed passenger, a path set formed by initial paths corresponding to the element with the value of 1 in the row corresponding to each passenger is a path neighborhood of the passenger, and any passenger can only find feasible insertion in the path neighborhood and is brought into vehicle service.
In the step (3), finding feasible insertions in the paths of each passenger in the neighborhood of the path comprises the following steps:
(3a) calculating travel parameters of each route in the route neighborhood, wherein the travel parameters comprise the earliest departure time, the latest departure time, the earliest arrival time and the latest arrival time of the vehicle; considering the mutual constraint of the passengers going out in the same train number, and updating the travel time parameters of the passengers in the path;
(3b) and sequentially carrying out feasible insertion judgment on each service sequence position in each neighborhood path, wherein whether the insertion is feasible or not needs to meet the following constraint conditions:
maximum travel time constraint: newly inserted passengers need to meet the constraint of self maximum travel time at the insertion sequence position, and meanwhile, the constraint of the maximum travel time of the original passengers on the path is also influenced and needs to be checked again;
and (3) common time window constraint of the pivot terminal: the new passenger must have a common time window at the terminal with the passenger already engaged in the train service, and the insertion of the new passenger gradually narrows the common time window at the terminal for the train passenger;
non-pivot end time parameter constraint: the service time of the vehicle at the passenger trip non-terminal end must be within the time window acceptable for all passengers.
The method for calculating the regret value in the step (3) comprises the following steps:
(31) calculating the marginal cost delta C of each path inserted into the neighborhood path for each passenger, wherein the calculation formula is as follows:
ΔC＝ΔC1+ΔC2+ΔC3＝(ΔC11+ΔC12)+(ΔC21+ΔC22)+ΔT
wherein, is1The marginal cost for deviation of actual arrival time of a passenger from ideal arrival time is the incremental Δ C of deviation of ideal service time of an existing passenger in the path caused by a new passenger11Deviation Δ C from ideal service time of new passenger12Summing; delta C2For the marginal cost of the deviation of the travel time of the passenger, the deviation of the ideal travel time of the passenger in the current path is increased by deltaC21Deviation Δ C from ideal travel time of new passenger22Summing; delta C3The marginal cost of the travel time of the train number is the increase delta T of the travel time of the train number caused by the new passenger;
for class P passengers there are:
Figure BDA0001784466880000051
Figure BDA0001784466880000052
wherein, Δ WD2 mThe change value of the upper limit of the common time window of all passengers at the public transport hub station caused by the new passenger is obtained; i PmI represents the number of passengers of the class P passenger served by the train number m; z represents the position of feasible insertion on the current path of the new passenger; LDT (laser direct structuring) deviceinewIs a new passenger inewThe latest getting-off time; TA (TA)inew mIs a new passenger inewWhen taking a car for m times, the car gets on the carThe time that the secondary vehicle continues to travel; DRTinewIs a new passenger inewThe shortest riding time;
for class D passengers there are:
Figure BDA0001784466880000053
Figure BDA0001784466880000054
wherein, Delta WO1 gIs a new passenger jnewThe lower limit of the common time window of all passengers at the public transport hub station is caused to change; i PgI represents the number of passengers whose class D passengers are served by the train number g; EPTjnewIs a new passenger jnewThe earliest time of getting on the vehicle; n is the number of passengers in the current path; TBjnew gIs a new passenger jnewThe time of driving by the number g before getting on the bus; DRTjnewIs a new passenger jnewThe shortest riding time;
(32) calculating the marginal cost delta C of the insertion position of each passenger without taking the service as a row and the current driving paths of all the vehicles as a column, and taking the marginal cost delta C as a matrix element to obtain a marginal cost matrix; then, subtracting the minimum value of each row of the matrix and summing the minimum values to obtain the regret value of the passenger, wherein the regret value is inserted preferentially.
Further, the method comprises the step of replacing the passengers who are not served in the neighborhood path of the passengers one by one, specifically, when the number of the passengers is lower than a certain threshold value theta or all newly generated paths can not meet the requirement of the vehicle occupancy rate α, a whole optimization procedure is executed on the current driving plan, the whole optimization means that the new passengers are replaced with the passengers who are served in the neighborhood of the paths, and if the new passengers i are not served, the passengers who are served are replaced in the neighborhood paths of the new passengers inewCan find feasible insertion in the replaced path and the replaced passenger ikA new path meeting the requirement of the passenger carrying rate can be formed by the set of the rest passengers, so that the overall optimization program is successful; otherwise displaced passengerikIt is also necessary to replace other passengers i in the neighborhood of their pathvIf i iskFind feasible insertions in the permuted path and ivAnd forming a new path meeting the passenger carrying rate requirement with the rest passengers, and then successfully replacing.
Has the advantages that:
1. the method further analyzes the conversion relation among the travel time parameters of the passengers, and is helpful for mastering the essence of the demand response type bus driving plan.
2. The method fully utilizes the constraint relation among passengers in the same train, adopts the method of searching the maximum incompatible passenger set to determine the initial vehicle number and the seed passengers of the initial path, and improves the efficiency and the quality of the method.
3. The method provides a concept of 'path neighborhood', greatly reduces the search range of feasible solutions, and greatly improves the efficiency of the method.
4. The method has the advantages of better overall program, adoption of the idea of reducing the satisfaction degree of partial passengers and the total cost of the system, and effective improvement of the quality of the solution.
Drawings
FIG. 1 is a flow chart of a demand response type bus route optimization method;
fig. 2 is a more preferred flow chart of the whole demand response type bus driving route.
Detailed Description
The technical scheme of the invention is further explained by combining the attached drawings.
Referring to fig. 1, a demand response type connection bus route optimization method includes the following steps:
step 1, calculating a passenger travel time parameter according to the passenger appointment time and the passenger appointment place, and constructing a mutual constraint relation of the passenger travel time parameter. The method specifically comprises the following steps:
(11) the passengers are divided into two types according to different directions from public transport hub stations, the passengers from all places to the hub end are P-type passengers, the passengers from the hub station to all places are D-type passengers, and the passengers need to appoint when the passengers reserve to receive and deliver servicesRespective expected service time and place, assuming that P type passengers only pay attention to the time of arriving at the junction end and D type passengers pay attention to the time of departing from the junction station, and recording P type passengers ikThe latest arrival time at the junction end, i.e. the latest getting-off time is LDTikClass D passenger jrThe earliest departure time from the junction end, namely the earliest boarding time is EPTjr(ii) a The width of the service change time window acceptable by the two types of passengers at the terminal is set as w by the public transport company; the shortest travel time for class P and class D passengers is DRTik、DRTjrThe longest travel time is MRTik、MRTjrThe maximum travel time may be a function of the shortest travel time.
(12) Calculating the travel time parameter of the passenger:
for class P passengers there are:
Figure BDA0001784466880000071
Figure BDA0001784466880000072
Figure BDA0001784466880000073
wherein, EDTik、LPTik、EPTikRespectively P-class passengers ikThe earliest getting-off time, the latest getting-on time and the earliest getting-on time of the vehicle;
for class D passengers there are:
Figure BDA0001784466880000074
Figure BDA0001784466880000075
Figure BDA0001784466880000076
wherein LPTjr、EDTjr、LDTjrClass D passengers jrThe latest getting-on time, the earliest getting-off time and the latest getting-off time;
(13) constructing a constraint relation of travel time parameters of passengers in the same train:
Figure BDA0001784466880000077
Figure BDA0001784466880000078
then [ EATO g,LATO g]Departure time window, EAT, representing departure of vehicle g from the junction station for evacuation of class D passengersO gAnd LATO gRespectively earliest departure time and latest departure time; [ EAT ]D m,LATD m]An arrival time window, EAT, representing the arrival of a vehicle at a junction station when m blocks a class P passengerD mAnd LATD mRespectively the earliest arrival time and the latest arrival time; pmAnd PgRepresenting the set of passengers serviced by vehicle m and vehicle g, respectively.
In one embodiment, the data input is set to: class P passenger ikThe latest arrival time at the junction end (i.e. the latest getting-off time) is 9:00, the allowable variation time window width is 15min, and the shortest travel time DRT for passengers to arrive at the junction endik20min, maximum travel time MRTik＝2*DRTik+5min ═ 35 min; class D passenger jrThe earliest leaving time (i.e. the earliest getting-on time) of the terminal is 8:00, the allowable variation time window width is 15min, and the shortest travel time DRT for passengers to arrive at the terminaljr15min, maximum travel time MRTjr＝2*DRTjr+5min＝35min。
Calculating class P passenger i according to the input data set abovekThe travel time parameters are as follows, and are uniformly expressed as decimal for convenient calculation:
Figure BDA0001784466880000081
Figure BDA0001784466880000082
Figure BDA0001784466880000083
Figure BDA0001784466880000084
class D passenger jrThe travel time parameter of (a) is calculated as follows:
Figure BDA0001784466880000085
Figure BDA0001784466880000086
Figure BDA0001784466880000087
Figure BDA0001784466880000088
the basic constraint relationship of the travel time parameters of the passengers in the same train is calculated as follows: suppose a class P passenger i1、i7、i9Passengers of the same train number m; class D passenger j2、j20、j15Passenger of the same train number g, EDTi1、EDTi7、EDTi9The earliest getting-off time, LDT, of three P-class passengersi9、LDTi9、LDTi9Respectively the latest getting-off time of three P-class passengers; EPTj2、EPTj20、EPTj15Respectively, the earliest time of getting on, LPT, of three class D passengersj2、LPTj20、LPTj15Respectively three-seat class D passengersThe latest time of getting on the bus. Then for the train number m:
Figure BDA0001784466880000089
Figure BDA00017844668800000810
Figure BDA00017844668800000811
for class D passengers there are:
Figure BDA00017844668800000812
Figure BDA00017844668800000813
Figure BDA00017844668800000814
and 2, judging passenger compatibility based on the passenger travel time parameters, constructing a corresponding compatibility matrix, and finding out a maximum incompatible passenger set to obtain the number of initial required vehicles and the seed passengers of each initial path.
(21) Determining passenger compatibility
Passenger compatibility refers to whether the service of the same vehicle can be brought in, and the compatibility among the passengers depends on two conditions, namely whether a common time window exists at a hub end or not, and whether the travel time parameter of a non-hub end meets a constraint condition or not, namely whether the travel time parameter of the non-hub end of the passenger can be met or not under the condition that only two passengers exist in the current train number. The non-hub end refers to the end of the passenger, which is not located at the hub station, at the starting and ending point. The compatibility determination result is true only if both conditions are satisfied.
When P-type passengers are taken as an object set:
and (3) judging the compatibility of the pivot end:hypothesis (EDT)ik，LDTik) And (EDT)ir，LDTir) Are respectively passengers ikAnd irThe earliest time of getting off and the latest time of getting off when arriving at the junction station, if the inequality is satisfied:
Figure BDA0001784466880000091
then the compatibility condition one is satisfied.
And (3) judging the compatibility of the non-pivot end: suppose (EPT)ik，LPTik) And (EPT)ir，LPTir) Are respectively passengers ikAnd irThe earliest time to get on the bus and the latest time to get on the bus at the junction station. Whether the passengers are compatible at the non-junction end requires consideration of the distance between passengers and road traffic conditions. Suppose passenger ikTo passenger irTime t of tripkr pTo passenger irTo passenger ikTime t of triprk pEqual, i.e. tkr p＝trk p. When serving passenger ikRe-service passenger irWhen it is needed to satisfy
Figure BDA0001784466880000092
Or serve passenger i firstrRe-service passenger ikWhen it is needed to satisfy
Figure BDA0001784466880000093
And if the two conditions are both satisfied, the compatibility condition two is judged to be satisfied.
When the class D passenger is taken as the object set:
and (3) judging the compatibility of the pivot end: suppose passenger jkAnd passenger jrIs any two D-class passengers, and the earliest time of getting on the bus and the latest time of getting on the bus are respectively (EPT)jk，LPTjk) And (EPT)jr，LPTjr) If inequality is satisfied
Figure BDA0001784466880000094
Then the compatibility condition one is satisfied.
And (3) judging the compatibility of the non-pivot end: suppose (ED)Tjk，LDTjk) And (EDT)jr，LDTjr) Respectively the earliest time of getting off and the latest time of getting off for two passengers. Let tkr d＝trk dFor class d passengers jkAnd passenger jrWhen the passenger j goes out of the vehiclekTo passenger jrWhen it is needed to satisfy
Figure BDA0001784466880000095
Or by passenger jrTo passenger jkWhen it is needed to satisfy
Figure BDA0001784466880000096
If both of the two conditions are satisfied, it is determined that the compatible condition two is satisfied.
When the compatibility of two passengers is judged, the conditions of the terminal and the non-terminal must be simultaneously satisfied to judge that the two passengers are compatible, otherwise, the two passengers are considered to be incompatible and cannot be served by the same vehicle.
In one embodiment, class P passenger i1、i2、i3The travel time parameters and the travel time matrix are respectively shown in table 1 and table 2:
TABLE 1 class P passenger travel time parameter table (Unit: hour)
Figure BDA0001784466880000101
TABLE 2 class P passenger travel time matrix (units: hours)
Figure BDA0001784466880000102
Class D passenger j1、j2、j3The travel time parameters and the travel time matrix are respectively shown in table 3 and table 4:
TABLE 3 class D passenger travel time parameter Table (Unit: Times)
Figure BDA0001784466880000103
TABLE 4 class D passenger travel time matrix (units: hours)
Figure BDA0001784466880000104
Respectively for class P passengers i1And i2Compatibility, class D passenger j1And j2The compatibility determination exemplifies a specific determination process as follows:
for P type passenger i1And i2：
a) And (3) pivot end compatibility judgment:
max {8.2,7.8 }. ltoreq min {9.7,8.3} meets the condition;
b) and (3) non-pivot end compatibility judgment:
max {7.97+0.008,7.57 }. ltoreq min {8.66+0.008,8.26} meets the condition;
therefore passenger i1And i2And (4) compatibility.
For class D passenger j1And j2：
a) And (3) pivot end compatibility judgment:
max {12.67,13.25 }. ltoreq min {13.36,13.95} satisfies the condition;
b) and (3) non-pivot end compatibility judgment:
max {12.9+0.082,13.5} ≦ min {13.4+0.082,14} is false;
max {12.9,13.5+0.082} ≦ min {13.4,14+0.082} is false;
so passenger j1And j2Are not compatible.
(22) Constructing passenger compatibility matrices
And respectively taking passengers as rows and columns to construct a matrix, and taking the compatibility judgment result between the passengers as a matrix element. Take class P passenger as an example, when passenger ikAnd irWhen compatible, the corresponding element a in the matrixkrThe value is 1, otherwise the value is 0, and the matrix form is as follows:
Figure BDA0001784466880000111
in this embodiment, the two groups of passengers finally obtain compatibility matrices as shown in tables 5 and 6, where element 1 indicates compatibility and element 0 indicates incompatibility.
TABLE 5 passenger compatibility matrix of P class
Figure BDA0001784466880000112
TABLE 6 passenger compatibility matrix class D
Figure BDA0001784466880000121
(23) Determining a maximum incompatible passenger set
Firstly, selecting a column (row) with the most 0 elements, and marking the column (row); then dividing the row and the column corresponding to the element with the value of 1 in the column (row); the above steps are repeated until all columns (rows) are marked or scratched out. In order to obtain the maximum passenger set Ω, all the columns (rows) may be sequentially listed as initial marked columns (rows), and the method may be performed a plurality of times, taking the maximum number of elements of the incompatible set as the maximum incompatible set Ω ═ ik,im,in,ir… }. The total number of elements in the maximum set of incompatible passengers is the initial required number of vehicles, and each passenger in the set is a seed passenger for constructing an initial path of the vehicle.
In one embodiment, taking a class P passenger as an example of a set of objects, assume { i }1,i2,i3,i4,i5,i6,i7,i8The compatibility matrix for a class P passenger set is as follows:
Figure BDA0001784466880000122
the process of determining the maximum incompatible passenger set from the compatibility matrix is as follows:
s23-1: choose the column i with the most 0 elements6And the column and corresponding row are marked →;
s23-2 scratching off (×) i6The row corresponding to the element 1 in the column and its corresponding column i8；
Figure BDA0001784466880000123
S23-3: repeating the above steps, marking the column with the most 0 elements and the corresponding row in the unmarked or scratched columns, scratching the row and column corresponding to the element with the value of 1 in the column (row) until all the rows and columns in the matrix are marked or scratched.
Figure BDA0001784466880000131
The resulting set of incompatibilities is { i }2,i4,i6}. As mentioned above, all the requirements can be listed as the initial tag column in turn, and the method is performed multiple times, taking the maximum number of elements as the maximum incompatible set Ω.
And 3, determining a path neighborhood of each passenger according to the maximum incompatible passenger set, searching feasible insertion for the path of each passenger in the path neighborhood of each passenger, determining the optimal insertion of the passenger in each neighborhood path by calculating the repentance value, and realizing the primary planning of the path.
(31) Determining a path neighborhood
After the maximum incompatible passenger set omega is determined, each seed passenger in the set corresponds to an initial path r1,r2,r3,r4… are provided. In the passenger compatibility matrix, except for the seed passenger, the path set represented by the seed passenger corresponding to the element with the value of 1 in the row corresponding to each remaining passenger is the path neighborhood of the passenger. After the neighborhood of the route is determined, the passenger can only find feasible insertion in the driving route in the neighborhood of the route and is taken into service. The concept of 'path neighborhood' is put forward, so that the search range of feasible solutions can be greatly reduced, and the efficiency and the quality of the method are improved.
By class P passengersFor example, after the maximum incompatible set Ω is determined, each seed passenger in the set is determined to correspond to one initial path r, and three initial paths are determined as in the above embodiment: r is1＝{i2}，r2＝{i4}，r3＝{i6}. In the compatibility matrix, each row corresponds to one passenger, and except for the seed passenger, the set formed by the initial path corresponding to the row element 1 corresponding to each passenger is the path neighborhood of the passenger, such as i8Has a path neighborhood of { i2,i6}。
(32) Finding a feasible insertion
After the path neighborhood of each passenger is determined, feasible insertion is searched for in the path of each passenger in the path neighborhood, and the optimal insertion of the passenger in each neighborhood path is determined to be used as data input for constructing a marginal cost matrix later. Finding a viable insertion for a passenger is divided into two steps: and calculating the travel parameters of the current path and judging feasible insertion.
S32-1: calculation of current path travel parameters
Before an unserviced passenger inserts a certain path in the adjacent paths, travel parameters of the path are required to be calculated, wherein the travel parameters comprise the earliest departure time, the latest departure time, the earliest arrival time and the latest arrival time of a vehicle; and the travel time parameters of the passengers in the path are updated by considering the mutual restriction of the passengers in the same train number.
When P-type passengers are taken as an object set: time Window (WD) of vehicle m at junction end under current route1 m,WD2 m) Serving passenger P in the pathmCommon time window at the hinge side:
Figure BDA0001784466880000141
Figure BDA0001784466880000142
at the same time, the passenger i in the shiftkCorresponding earliest and latest boarding time parameters also occurChanging:
Figure BDA0001784466880000143
Figure BDA0001784466880000144
for the entire route, the time window for vehicle m to start and arrive at the junction end is calculated as follows:
Figure BDA0001784466880000145
Figure BDA0001784466880000146
Figure BDA0001784466880000147
Figure BDA0001784466880000148
Figure BDA0001784466880000149
Figure BDA00017844668800001410
wherein the content of the first and second substances,
Figure BDA00017844668800001411
indicating arrival of vehicle m at class P passenger ikThe latest time of the point of departure,
Figure BDA00017844668800001412
indicating arrival of vehicle m at class P passenger ikThe time of flight after the point of departure,
Figure BDA00017844668800001417
indicating the latest departure time of the vehicle m from the junction end,
Figure BDA00017844668800001413
indicating the dwell time of the vehicle m at the junction end,
Figure BDA00017844668800001414
indicating the earliest departure time of the vehicle m from the junction end,
Figure BDA00017844668800001415
indicating arrival of vehicle m at class P passenger ikThe time of flight before the point of departure,
Figure BDA00017844668800001416
indicating arrival of vehicle m at class P passenger ikEarliest time of departure point.
Line time window WWm(the time it takes for vehicle m to get on the junction and then to go off for continued docking) is calculated as follows:
Figure BDA0001784466880000151
when the class D passenger is taken as the object set: time window of vehicle g at the junction end under the current train number (WO)1 g,WO2 g) For all passengers P in the pathgThe common time window from the hinge end is shown as follows:
Figure BDA0001784466880000152
Figure BDA0001784466880000153
at the same time, the passenger j of the trainrThe corresponding time parameters of the earliest and latest alighting are also changed:
Figure BDA0001784466880000154
Figure BDA0001784466880000155
for the entire route, the time windows for the vehicle g to go from and return to the terminal are calculated as follows:
Figure BDA0001784466880000156
Figure BDA0001784466880000157
Figure BDA0001784466880000158
Figure BDA0001784466880000159
Figure BDA00017844668800001510
Figure BDA00017844668800001511
wherein the content of the first and second substances,
Figure BDA00017844668800001512
indicating that vehicle g is traveling to class D passenger jrThe earliest time at which the destination is to be reached,
Figure BDA00017844668800001513
indicates that the vehicle g will be a class D passenger jrThe travel time before the destination is reached,
Figure BDA00017844668800001514
indicating the earliest arrival time of the vehicle g at the junction end,
Figure BDA00017844668800001515
indicating the dwell time of the vehicle g at the junction end,
Figure BDA00017844668800001516
representing the latest arrival time of the vehicle g at the junction end,
Figure BDA00017844668800001518
indicates that the vehicle g will be a class D passenger jrThe travel time after the delivery to the destination,
Figure BDA00017844668800001517
indicating that vehicle g is traveling to class D passenger jrThe latest time of the destination.
Line time window WWg(the time it takes for the vehicle g to leave the terminal to evacuate the class D passengers and then return to the terminal) is calculated as follows:
Figure BDA0001784466880000161
s32-2: feasible insertion determination
For a vehicle m serving class P passengers, consider a passenger i in the travel path of the vehicle mzAnd iz+1Between which a new passenger i is insertednewThen, it is determined that the insertion is feasible and the following constraints are satisfied:
a) maximum travel time constraint: newly inserted passengers need to meet the maximum travel time constraint of the passengers, and the maximum travel time constraint of the original passengers before the insertion point is also influenced and needs to be checked again.
Figure BDA0001784466880000162
Figure BDA0001784466880000163
Figure BDA0001784466880000164
Wherein the content of the first and second substances,
Figure BDA0001784466880000165
indicating vehicle arrival of new passenger class P inewThe time of flight after the point of departure,
Figure BDA0001784466880000166
indicating arrival of vehicle m at class P passenger ikTravel time after departure, Δ T, is new passenger inewResulting in an increase in the travel time of the vehicle, wherein
Figure BDA0001784466880000167
Represents the slave passenger iaTo ibThe travel time in between.
b) And (3) common time window constraint of the pivot terminal: the new passenger must have a common time window at the terminal with the passenger already involved in the train service.
Figure BDA0001784466880000168
Figure BDA0001784466880000169
ΔWD1 m+ΔWD2 m≤WWm
The above equation illustrates that the insertion of a new passenger gradually reduces the slack time of the train:
Figure BDA00017844668800001610
Figure BDA00017844668800001611
the insertion of a new passenger shortens the time window of the junction terminal, and then affects the travel time parameters of each passenger, and the related parameters need to be updated so as to determine the travel non-junction terminal constraint conditions.
Has been incorporated intoServiced passenger ikTime of boarding, time of subsequent travel of passengers before insertion point
Figure BDA0001784466880000171
And the previous travel time of the passenger after the insertion point
Figure BDA0001784466880000172
Updating:
Figure BDA0001784466880000173
Figure BDA0001784466880000174
Figure BDA0001784466880000175
Figure BDA0001784466880000176
new passenger inewUpdating the getting-on time parameter and calculating the previous and subsequent travel time:
Figure BDA0001784466880000177
Figure BDA0001784466880000178
Figure BDA0001784466880000179
Figure BDA00017844668800001710
updating a line time parameter:
Figure BDA00017844668800001711
Figure BDA00017844668800001712
Figure BDA00017844668800001713
Figure BDA00017844668800001714
Figure BDA00017844668800001715
Figure BDA00017844668800001716
c) and (3) time parameter constraint of the passenger on the trip non-junction terminal: the present invention uses a hard time window to determine a viable insertion that the arrival time of the vehicle must be within a passenger acceptable time window (EPT)ik m,LPTik m) And (4) the following steps. It can also be understood that updated EATik m≤LATik mTherefore, the following are:
Figure BDA0001784466880000181
as can be seen from the above equation, when a hard time window is used, to check the non-hub constraint relationship of the class P passenger already included in the train service, the LAT is verifiedD m-EATO m-TOD mThe algorithm efficiency is improved by only being more than or equal to 0 and updating the related parameters after the conditions are met.
For a vehicle g serving class D passengers, consider a passenger j in the path of the vehicle gzAnd jz+1Insert a new passenger j betweennewThen, it is determined that the following constraints are also satisfied for the feasible insertion:
a) maximum travel time constraint:
Figure BDA0001784466880000182
Figure BDA0001784466880000183
Figure BDA0001784466880000184
wherein the content of the first and second substances,
Figure BDA0001784466880000185
indicating that the vehicle will be a class D new passenger jnewThe travel time before the destination is reached,
Figure BDA0001784466880000186
indicating that the vehicle will be a class D passenger jrThe travel time before the destination is reached, Δ T being the new passenger jnewResulting in an increase in the vehicle travel time.
b) And (3) common time window constraint of the pivot terminal: the new passenger must have a common time window at the terminal with the passenger already involved in the train service, and needs to satisfy:
Figure BDA0001784466880000187
Figure BDA0001784466880000188
ΔWO1 g+ΔWO2 g≤WWg
the above equation illustrates that the insertion of a new passenger gradually reduces the slack time of the train:
Figure BDA0001784466880000189
Figure BDA00017844668800001810
the insertion of a new passenger shortens the time window of the junction terminal, and then affects the travel time parameters of each passenger, and the related parameters need to be updated so as to determine the travel non-junction terminal constraint conditions.
Passenger j who has taken in servicerGet-off time parameter, subsequent travel time of passenger before insertion point
Figure BDA0001784466880000191
And the previous travel time of the passenger after the insertion point
Figure BDA0001784466880000192
Updating:
Figure BDA0001784466880000193
Figure BDA0001784466880000194
Figure BDA0001784466880000195
Figure BDA0001784466880000196
new passenger jnewUpdating the get-off time parameter and calculating the previous and subsequent travel times:
Figure BDA0001784466880000197
Figure BDA0001784466880000198
Figure BDA0001784466880000199
Figure BDA00017844668800001910
updating a line time parameter:
Figure BDA00017844668800001911
Figure BDA00017844668800001912
Figure BDA00017844668800001913
Figure BDA00017844668800001914
Figure BDA00017844668800001915
Figure BDA00017844668800001916
c) and (3) time parameter constraint of the passenger on the trip non-junction terminal: the determination of a viable insertion is made using a hard time window, i.e. the arrival time of the vehicle must be within a passenger acceptable time window (EDT)jr g,LDTjr g) And (4) the following steps. It can also be understood that the updated EDTjr g≤LDTjr gTherefore, the following are:
Figure BDA0001784466880000201
also from the above equation, it can be seen that when hard time windows are employed, to verify non-pivot end constraint relationships for class D passengers that have been included in a vehicle class service, the LAT is verified a prioriD g-EATO g-TOD gNot less than 0, and correlating after satisfying the conditionParameters are updated, and algorithm efficiency is improved.
(33) Determining the current optimal inserted passenger through regret insertion heuristic algorithm
After the vehicle and the seed passenger are identified, it is necessary to identify the next passenger for inclusion from among passengers who have not been included in the service. For each non-service passenger, finding feasible inserts in each path in the neighborhood of the path, calculating the cost of each feasible insert, and taking the minimum marginal cost as the optimal insert of the passenger under the path. The invention introduces a regret value to calculate an optimal inserting path, wherein the regret value is defined as the sum of the marginal cost of a passenger insertable path and the marginal cost difference of the optimal inserting path, the passenger with the maximum regret value is taken as the next passenger who brings service, and the optimal inserting path of the passenger is the current inserting path. The regret value calculation process is as follows:
s33-1: firstly, calculating the marginal cost delta C corresponding to the insertion position of each path in the insertion neighborhood path for each passenger, wherein the calculation formula is as follows:
ΔC＝ΔC1+ΔC2+ΔC3
wherein, is1Is the marginal cost of deviation of the actual arrival time of the passenger from the ideal arrival time, and is the increase Δ C of the deviation of the ideal service time of the existing passenger in the path caused by the new passenger11Deviation Δ C from ideal service time of new passenger12Summing; delta C2Is the marginal cost of the deviation of the travel time of the passenger, and is the increase Delta C of the deviation of the ideal travel time of the passenger in the current path21Deviation Δ C from ideal travel time of new passenger22Summing; delta C3Is the marginal cost of the next trip time, i.e., the new passenger induced increase in the next trip time Δ T.
For class P passengers there are:
Figure BDA0001784466880000202
Figure BDA0001784466880000211
wherein, Δ WD2 mIs a new passenger inewThe change value of the upper limit of the common time window of all the passengers at the public transport hub station is caused; i PmI represents the number of passengers of the class P passenger served by the train number m; z represents the feasible insertion position of the new passenger on the current path, and since the first position and the last position in the path represented by the train number m are the junction ends, when the new passenger is inserted at the position z, the travel time of z-2 passengers is actually influenced; LDT (laser direct structuring) deviceinewIs a new passenger inewTime of last alighting, TAinew mIs a new passenger inewWhen the driver takes the train number m, the time that the vehicle of the train number continues to run after getting on the train is up; DRTinewIs a new passenger inewThe shortest ride time.
For class D passengers there are:
Figure BDA0001784466880000212
Figure BDA0001784466880000213
wherein, Delta WO1 gIs a new passenger jnewThe lower limit of the common time window of all passengers at the public transport hub station is caused to change; i PgI represents the number of passengers whose class D passengers are served by the train number g; EPTjnewIs a new passenger jnewThe earliest time of getting on the vehicle; n represents the number of passengers in the current path; TBjnew gIs a new passenger jnewThe time of driving by the number g before getting on the bus; DRTjnewIs a new passenger jnewThe shortest ride time.
The insertion position of the new passenger in each neighborhood path with the minimum marginal cost is the optimal insertion position of the passenger in the neighborhood path, and the corresponding marginal cost is the optimal insertion marginal cost.
S33-2: with passengers i not taken into serviced,ie…, with all paths r presentk,rm… is a column, matrix element bijIndicating that the passenger corresponding to the ith row is at the jthInserting the marginal cost optimally into the path corresponding to the column to obtain a marginal cost matrix; then, subtracting the minimum value of each row of the matrix and summing the minimum values to obtain the regret value of the passenger, wherein the regret value is the maximum passenger preferential insertion. The marginal cost matrix is of the form:
Figure BDA0001784466880000214
in one embodiment, taking class P passengers as an example, the calculation of the regret currently inserted by a passenger is as follows:
according to the three determined initial paths: r is1＝{i2}，r2＝{i4}，r3＝{i6And i, and i8Has a path neighborhood of { r1,r3Suppose i8Feasible insertion can be found in the adjacent domain paths, and the optimal insertion marginal cost obtained in the two adjacent domain paths is C81，C83. And similarly, calculating the optimal insertion cost of the rest passengers in the respective path neighborhoods, wherein when the passenger has no feasible insertion in the path or the path is not in the passenger path neighborhoods, the insertion marginal cost is a set large value M, and the calculation result of the marginal cost matrix is as follows:
Figure BDA0001784466880000221
the calculation process and the result of the regret value are as follows:
Figure BDA0001784466880000222
the element in matrix (1) is the marginal cost of optimal insertion of each path in the respective path neighborhood by passengers not taking service; the elements of the matrix (2) are obtained by subtracting the minimum value of each row from each row of the matrix (1), and the rightmost column of the matrix sums each row, namely the regret value of each passenger. The remorse value is understood to mean that if the passenger is not the current insertion object, the late insertion would result in an increase in insertion cost, the larger the value the more the passenger should be brought into service in advance, otherwise a different degree of remorse would be brought. It can be seen from the matrix that the calculation method of the regret value provided by the invention gives the passengers with fewer insertable paths a more preferential insertion right, which is helpful for improving the overall satisfaction degree of users.
And 4, when all passengers who do not incorporate the service cannot find feasible insertion in the current path, releasing the passengers in the low-passenger-load-rate path, taking the released passengers and the rest passengers as a new object set, re-determining the maximum incompatible set, determining the initial path and searching the feasible insertion in the new path. The process is repeatedly circulated until the number of the remaining passengers is smaller than a certain threshold value theta or the newly generated path does not meet the requirement of the passenger carrying rate alpha all the time.
Step 5, adopting a replacement and insertion mode, if the replaced passenger can construct a driving plan meeting a certain passenger load factor requirement with the rest of the un-served passengers, the replacement is successful, otherwise, the replacement and insertion position is continuously searched in the neighborhood path, specifically, when the number of the un-served passengers is lower than a certain threshold value theta or all newly generated paths can not meet the vehicle passenger load factor α requirement, the whole optimization program is executed on the current driving plan, as shown in FIG. 2, the whole optimization refers to that the new passenger replaces the passenger already served in the neighborhood range of the path, if the new passenger i can construct the driving plan meeting the certain passenger load factor requirement, the whole optimization program is executed on the current driving plan, and if the new passenger i can notnewCan find feasible insertion in the replaced path and the replaced passenger ikA new path meeting the requirement of the passenger carrying rate can be formed by the set of the rest passengers, so that the overall optimization program is successful; otherwise replaced passenger ikIt is also necessary to replace other passengers i in the neighborhood of their pathvIf i iskFind feasible insertions in the permuted path and ivAnd forming a new path meeting the passenger carrying rate requirement with the rest passengers, and then successfully replacing. The successive permutations are only cycled twice, taking into account the method time consumption, and as long as the permutations are successful, no more optimal permutations are sought. The running path can be optimized in real time by utilizing the overall better program, so that the overall operation cost of the system is reduced.

Claims (7)

1. A demand response type connection bus route optimization method is characterized by comprising the following steps:
(1) calculating passenger travel time parameters according to the passenger appointment time and the passenger appointment place, and constructing a mutual constraint relation of the passenger travel time parameters;
(2) judging passenger compatibility based on the passenger trip time parameter relationship, constructing a corresponding compatibility matrix, and finding out a maximum incompatible passenger set to obtain the number of initial required vehicles and seed passengers of each initial path;
(3) determining a path neighborhood of each passenger according to the maximum incompatible passenger set, searching feasible insertion and determining optimal insertion for each passenger in the path of each passenger in the path neighborhood, determining the passenger who is preferentially taken into service at present by calculating the repentance value, and realizing the primary planning of the path; wherein the content of the first and second substances,
the path neighborhood determination method comprises the following steps: after the maximum incompatible set is determined, each passenger in the set corresponds to an initial path of the vehicle, the vehicle starts from the junction station, and the passengers in the service path return to the junction station; in the passenger compatibility matrix, except for the seed passenger, a path set formed by initial paths corresponding to the seed passenger corresponding to an element with the value of 1 in a row corresponding to each passenger is a path neighborhood of the passenger, and any passenger can only find feasible insertion in the path neighborhood and is brought into vehicle service;
said finding a feasible insertion for each passenger in a path in its path neighborhood comprises the steps of:
(3a) calculating travel parameters of each route in the route neighborhood, wherein the travel parameters comprise the earliest departure time, the latest departure time, the earliest arrival time and the latest arrival time of the vehicle; considering the mutual constraint of the passengers going out in the same train number, and updating the travel time parameters of the passengers in the path;
(3b) and sequentially carrying out feasible insertion judgment on each service sequence position in each neighborhood path, wherein whether the insertion is feasible or not needs to meet the following constraint conditions:
maximum travel time constraint: newly inserted passengers need to meet the constraint of self maximum travel time at the insertion sequence position, and meanwhile, the constraint of the maximum travel time of the original passengers on the path is also influenced and needs to be checked again;
and (3) common time window constraint of the pivot terminal: the new passenger must have a common time window at the terminal with the passenger already engaged in the train service, and the insertion of the new passenger gradually narrows the common time window at the terminal for the train passenger;
non-pivot end time parameter constraint: the service time of the vehicle at the passenger trip non-junction end must be within the time window acceptable for all passengers;
the calculation method of the regret value comprises the following steps:
(31) calculating the marginal cost delta C of each path inserted into the neighborhood path for each passenger, wherein the calculation formula is as follows:
ΔC＝ΔC1+ΔC2+ΔC3＝(ΔC11+ΔC12)+(ΔC21+ΔC22)+ΔT
wherein, is1The marginal cost for deviation of actual arrival time of a passenger from ideal arrival time is the incremental Δ C of deviation of ideal service time of an existing passenger in the path caused by a new passenger11Deviation Δ C from ideal service time of new passenger12Summing; delta C2For the marginal cost of the deviation of the travel time of the passenger, the deviation of the ideal travel time of the passenger in the current path is increased by deltaC21Deviation Δ C from ideal travel time of new passenger22Summing; delta C3The marginal cost of the travel time of the train number is the increase delta T of the travel time of the train number caused by the new passenger;
for class P passengers there are:
Figure FDA0002633166510000021
ΔC21＝(z-2)×ΔT，
Figure FDA0002633166510000022
wherein, Δ WD2 mAll passengers caused by new passengers are in public transport junction vehicleA change value of an upper limit of the station common time window; i PmI represents the number of passengers of the class P passenger served by the train number m; z represents the position of feasible insertion on the current path of the new passenger;
Figure FDA0002633166510000023
is a new passenger inewThe latest getting-off time;
Figure FDA0002633166510000024
the time window upper limit of the train number m in the public transport junction station under the current route;
Figure FDA0002633166510000025
is a new passenger inewWhen the driver takes the train number m, the time that the vehicle of the train number continues to run after getting on the train is up;
Figure FDA0002633166510000026
is a new passenger inewThe shortest riding time;
for class D passengers there are:
Figure FDA0002633166510000027
ΔC21＝(n-z)×ΔT，
Figure FDA0002633166510000028
wherein the content of the first and second substances,
Figure FDA0002633166510000029
is a new passenger jnewThe lower limit of the common time window of all passengers at the public transport hub station is caused to change; i PgI represents the number of passengers whose class D passengers are served by the train number g;
Figure FDA00026331665100000210
is a new passenger jnewThe earliest time of getting on the vehicle;
Figure FDA00026331665100000211
is the time window lower limit of the train number g at the public transport hub station; n is the number of passengers in the current path;
Figure FDA00026331665100000212
is a new passenger jnewThe time of driving by the number g before getting on the bus;
Figure FDA00026331665100000213
is a new passenger jnewThe shortest riding time;
the class P passengers are passengers starting from all places and going to the junction end, and the class D passengers are passengers returning to all places from the junction station;
(32) calculating the marginal cost delta C of the insertion position of each passenger without taking the service as a row and the current driving paths of all the vehicles as a column, and taking the marginal cost delta C as a matrix element to obtain a marginal cost matrix; then, subtracting the minimum value of each row of the matrix and summing the subtracted values to obtain the regret value of the passenger, wherein the regret value is inserted preferentially by the maximum value;
(4) and (5) repeating the steps (2) - (3) for the passengers which cannot be inserted into the existing path until the number of the remaining passengers is lower than a specified threshold or the passenger carrying rate of the obtained path is lower than a specified threshold.
2. The demand-responsive docking bus route optimization method according to claim 1, wherein the specific method of the step (1) is as follows:
(11) the passengers are divided into two types according to different directions of coming from and going from the public transport junction station, the passengers going to the junction end from various places are P-type passengers, the passengers going back to the various places from the junction station are D-type passengers, when the passengers reserve the receiving and delivering service, the expected service time and place of each passenger need to be appointed, the P-type passengers are supposed to only pay attention to the time of arriving at the junction end, the D-type passengers pay attention to the time of departing from the junction station, and the P-type passengers i are rememberedkThe latest time of arriving at the junction end, namely the latest getting-off time is
Figure FDA0002633166510000031
Class D passenger jrThe earliest time from the hub end, namely the earliest time of getting on the bus is
Figure FDA0002633166510000032
The width of the service change time window acceptable by the two types of passengers at the terminal is set as w by the public transport company; the shortest travel time for class P and class D passengers is
Figure FDA0002633166510000033
The maximum travel time is respectively
Figure FDA0002633166510000034
(12) Calculating the travel time parameter of the passenger:
for class P passengers there are:
Figure FDA0002633166510000035
Figure FDA0002633166510000036
Figure FDA0002633166510000037
wherein the content of the first and second substances,
Figure FDA0002633166510000038
respectively P-class passengers ikThe earliest getting-off time, the latest getting-on time and the earliest getting-on time of the vehicle;
for class D passengers there are:
Figure FDA0002633166510000039
Figure FDA00026331665100000310
Figure FDA00026331665100000311
wherein the content of the first and second substances,
Figure FDA00026331665100000312
class D passengers jrThe latest getting-on time, the earliest getting-off time and the latest getting-off time;
(13) constructing a constraint relation of travel time parameters of passengers in the same train:
Figure FDA0002633166510000041
Figure FDA0002633166510000042
wherein the content of the first and second substances,
Figure FDA0002633166510000043
representing a departure time window for vehicle g to evacuate class D passengers from the departure of the hub station,
Figure FDA0002633166510000044
and
Figure FDA0002633166510000045
respectively earliest departure time and latest departure time;
Figure FDA0002633166510000046
representing the arrival time window at the terminal station when vehicle m is docked with a class P passenger,
Figure FDA0002633166510000047
and
Figure FDA0002633166510000048
respectively the earliest arrival time and the latest arrival time; pmAnd PgRepresenting the set of passengers serviced by vehicle m and vehicle g, respectively.
3. The demand response type connection bus route optimization method according to claim 2, wherein the passenger compatibility judgment in the step (2) includes a hub-end compatibility judgment and a non-hub-end compatibility judgment, and only when the hub-end and non-hub-end compatibility judgment results of two passengers are compatible, the two passengers are considered to be compatible and can be served by the same bus, wherein,
for any two P-class passengers ikAnd irAnd the pivot end compatibility judgment condition is as follows:
Figure FDA0002633166510000049
wherein the content of the first and second substances,
Figure FDA00026331665100000410
and
Figure FDA00026331665100000411
are respectively passengers ikAnd irThe earliest getting-off time and the latest getting-off time when arriving at a hub station;
the compatibility determination conditions of the non-pivot terminal are as follows:
first-serve passenger ikRe-service passenger irWhen it is satisfied
Figure FDA00026331665100000412
Or serve passenger i firstrRe-service passenger ikWhen it is satisfied
Figure FDA00026331665100000413
Wherein the content of the first and second substances,
Figure FDA00026331665100000414
and
Figure FDA00026331665100000415
are respectively passengers ikAnd irThe earliest time of getting on the bus and the latest time of getting on the bus when arriving at the hub station;
Figure FDA00026331665100000416
for vehicle slave passenger ikTo passenger irThe travel time of the department is as follows,
Figure FDA00026331665100000417
for vehicle slave passenger irTo passenger ikThe travel time of the department is as follows,
Figure FDA00026331665100000418
for any two class D passengers jkAnd jrAnd the compatibility judgment condition of the pivot end is as follows:
Figure FDA00026331665100000419
wherein the content of the first and second substances,
Figure FDA00026331665100000420
and
Figure FDA00026331665100000421
are respectively passenger jkAnd passenger jrThe earliest getting-on time and the latest getting-on time from the hub end;
the compatibility determination conditions of the non-pivot terminal are as follows:
when the passenger jkTo passenger jrWhen it is satisfied
Figure FDA0002633166510000051
Or by passenger jrTo passenger jkWhen it is satisfied
Figure FDA0002633166510000052
Wherein
Figure FDA0002633166510000053
And
Figure FDA0002633166510000054
are respectively passenger jkAnd jrThe earliest getting-off time and the latest getting-off time,
Figure FDA0002633166510000055
for vehicle slave passenger jkTo passenger jrThe time of the trip between the two persons,
Figure FDA0002633166510000056
for vehicle slave passenger jrTo passenger jkThe time of the trip between the two persons,
Figure FDA0002633166510000057
4. the demand-responsive docking bus route optimization method according to claim 2, wherein the method for constructing the passenger compatibility matrix in the step (2) is as follows: and respectively taking passengers as rows and columns to construct a matrix, taking the compatibility judgment result between the passengers as matrix elements, and when two passengers are compatible, taking the value of the corresponding element in the matrix as 1, otherwise, taking the value as 0.
5. A demand-responsive docked bus route optimization method as claimed in claim 3, wherein the method of determining the maximum incompatible passenger set, initial vehicle number and seed passenger in step (2) is as follows:
2a) selecting a column or a row with the most 0 elements, marking the column or the row and the corresponding row or column, and then dividing the row and the column corresponding to the element with the value of 1 in the column or the row;
2b) repeating the step 2a) until all the columns or rows are marked or scratched, wherein passengers corresponding to the marked columns or rows form incompatible passenger sets;
2c) sequentially arranging all the columns or rows as initial mark columns or rows, carrying out the steps for multiple times, and taking the maximum number of the incompatible set elements as a maximum incompatible set omega;
2d) the number of passengers in the maximum incompatible set omega is the initial number of vehicles, and each passenger is a seed passenger of the corresponding vehicle.
6. The demand response type connection bus route optimization method as claimed in claim 1, further comprising the step of executing an overall optimization program on the current driving plan when the number of passengers not taking service is lower than a certain threshold value theta or all newly generated routes can not meet the requirement of the vehicle passenger capacity α, wherein the overall optimization means that a new passenger replaces a passenger who has taken service in the neighborhood range of the route, and if the new passenger i is a passengernewCan find feasible insertion in the replaced path and the replaced passenger ikA new path meeting the requirement of the passenger carrying rate can be formed by the set of the rest passengers, so that the overall optimization program is successful; otherwise replaced passenger ikIt is also necessary to replace other passengers i in the neighborhood of their pathvIf i iskFind feasible insertions in the permuted path and ivAnd forming a new path meeting the passenger carrying rate requirement with the rest passengers, and then successfully replacing.
7. The demand-responsive docked bus route optimization method of claim 6, wherein the overall optimization routine is such that passengers do not continue to seek better replacement as long as the replacement is successful.
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