CN116307333B

CN116307333B - Method and device for acquiring round trip line and schedule of inter-city customized passenger transport

Info

Publication number: CN116307333B
Application number: CN202310551413.8A
Authority: CN
Inventors: 王成; 胡蝶
Original assignee: Huaqiao University
Current assignee: Huaqiao University
Priority date: 2023-05-17
Filing date: 2023-05-17
Publication date: 2023-08-08
Anticipated expiration: 2043-05-17
Also published as: CN116307333A

Abstract

The invention provides a method and a device for acquiring a round trip line and a schedule of inter-city customized passenger transport, and relates to the technical field of inter-city passenger transport planning. The acquisition method comprises the steps of S1, constructing a round trip line and schedule optimization model. S2, acquiring historical order data of the network vehicle between the city A and the city B. And S3, clustering the space and time of the orders according to historical order data of the network about vehicles, and obtaining a subset of the center points of getting on and off the vehicles. And S4, solving by using a greedy algorithm according to greedy rules with the maximum number of serviceable people according to the round trip line and schedule optimization model and the subset of the center points of getting on and off, and obtaining an initial solution. S5, randomly selecting a first disturbance operator to disturb the line in the current solution, and obtaining a local optimal solution. S6, randomly selecting a second disturbance operator to disturb the round trip loop in the local optimal solution, and obtaining the global optimal solution. And S7, outputting a global optimal solution when the iteration times reach an iteration threshold value, and obtaining a round trip line and a scheduling optimization scheme.

Description

Method and device for acquiring round trip line and schedule of inter-city customized passenger transport

Technical Field

The invention relates to the technical field of urban passenger transport planning, in particular to a method and a device for acquiring a round trip line and a schedule of urban customized passenger transport.

Background

The line operation schedule is the basis for dispatching vehicles and is also an important reference for the travel of passengers. The reasonable circuit and schedule design can improve the operation efficiency of the vehicle and reduce the travel cost of passengers.

The inter-city travel demands are complex and various, and the daily large-scale passenger traffic brings great burden to the whole urban traffic, and the urban traffic is particularly obvious in large cities. Traditional passenger transport often needs to reach a destination after multiple transfer, and travel efficiency is difficult to guarantee and can not meet the riding demands of most passengers. Thus, custom passenger traffic has emerged to increase the efficiency of passenger traffic.

The inter-city custom-made passenger transport distance is long, the transport range is wide, the inter-city passenger transport problem is solved in order, a driver can return to the rest place of the driver again, and the ordered scheduling of the vehicle running between two cities is planned in an overall way, so that the problem to be solved is urgent. In addition, the higher the full load rate of inter-city custom passenger traffic, the more considerable the enterprise revenue, while the generation of high full load rate loops is complex, requiring both up and down line generation and shift determination.

In view of this, the applicant has studied the prior art and has made the present application.

Disclosure of Invention

The invention provides a method and a device for acquiring round trip routes and schedules of inter-city custom passenger traffic, which are used for improving at least one of the technical problems.

A first aspect,

The embodiment of the invention provides a method for acquiring round trip routes and schedules of inter-city custom passenger traffic, which comprises steps S1 to S7.

S1, constructing a round-trip line and schedule optimization model which aims at maximizing the total income of all inter-city customized passenger lines in the round-trip line based on inter-city customized passenger traffic round-trip rings, lines, schedules and the number of passengers between two cities, aims at minimizing the travel cost of the passengers and meeting the running condition as basic constraint, and simultaneously comprises rest constraint.

S2, acquiring historical order data of the network vehicle between the city A and the city B. Wherein, the network about car history order data comprises a get-on position and a get-off position.

And S3, clustering the space and time of the orders according to historical order data of the network about vehicles, and obtaining a subset of the center points of getting on and off the vehicles.

And S4, solving by using a greedy algorithm according to greedy rules with the maximum number of serviceable people according to the round trip line and schedule optimization model and the subset of the center points of getting on and off, and obtaining an initial solution. Wherein the initial solution comprises a plurality of round trip rings. The shuttle ring includes at least one shuttle string. The round trip string contains 1 uplink and 1 downlink.

S5, randomly selecting a first disturbance operator to disturb the line in the current solution, and obtaining a first new solution. And judging whether the first new solution is better than the current solution according to the objective of the round trip line and the schedule optimization model after disturbance. If the first new solution is better than the current solution, the first new solution is directly accepted, and a local optimal solution is obtained. Otherwise, randomly selecting the first disturbance operator again to disturb the line in the first new solution until the disturbance times reach a first threshold value, and then receiving the first new solution by using the simulated annealing probability to obtain a local optimal solution. Wherein, when disturbance is performed for the first time, the initial solution is taken as the current solution.

S6, randomly selecting a second disturbance operator to disturb the round trip loop in the local optimal solution, and obtaining a second new solution. And judging whether the second new solution is better than the local optimal solution according to the round trip line and the target of the schedule optimization model after disturbance. If the second new solution is better than the local optimal solution, the second new solution is directly accepted, and the global optimal solution is obtained. Otherwise, randomly selecting a second disturbance operator again to disturb the line in the second new solution until the disturbance times reach a second threshold value, and then receiving the second new solution by using the simulated annealing probability to obtain a global optimal solution.

And S7, updating the iteration times and judging whether the iteration threshold is reached. And if the iteration threshold is reached, outputting a global optimal solution to acquire a round trip line and a scheduling optimization scheme. Otherwise, the global optimal solution of the current iteration times is used as the current solution to continue iteration.

A second aspect,

The embodiment of the invention provides a device for acquiring a round trip line and a schedule of inter-city custom passenger traffic, which comprises the following steps:

the model building module is used for building a round-trip line and schedule optimization model which aims at maximizing the total income of all inter-city customized passenger lines in the round-trip line based on inter-city customized passenger traffic round-trip rings, lines, schedules and the number of passengers between two cities, aims at minimizing the travel cost of the passengers and meeting the running condition as basic constraint, and simultaneously comprises rest constraint.

And the initial data acquisition module is used for acquiring historical order data of the network appointment vehicles between the A city and the B city. Wherein, the network about car history order data comprises a get-on position and a get-off position.

And the clustering module is used for clustering the space and time of the orders according to the historical order data of the network about vehicles and obtaining a subset of the center points of getting on and off the vehicles.

And the initial solution calculation module is used for solving according to the round trip line and schedule optimization model and the subset of the center points of the getting-on and getting-off, and a greedy algorithm is used for obtaining an initial solution according to a greedy rule with the maximum number of serviceable people. Wherein the initial solution comprises a plurality of round trip rings. The shuttle ring includes at least one shuttle string. The round trip string contains 1 uplink and 1 downlink.

And the local optimization module is used for randomly selecting a first disturbance operator to disturb the line in the current solution to obtain a first new solution. And judging whether the first new solution is better than the current solution according to the objective of the round trip line and the schedule optimization model after disturbance. If the first new solution is better than the current solution, the first new solution is directly accepted, and a local optimal solution is obtained. Otherwise, randomly selecting the first disturbance operator again to disturb the line in the first new solution until the disturbance times reach a first threshold value, and then receiving the first new solution by using the simulated annealing probability to obtain a local optimal solution. Wherein, when disturbance is performed for the first time, the initial solution is taken as the current solution.

And the global optimization module is used for randomly selecting a second disturbance operator to disturb the round trip ring in the local optimal solution to obtain a second new solution. And judging whether the second new solution is better than the local optimal solution according to the round trip line and the target of the schedule optimization model after disturbance. If the second new solution is better than the local optimal solution, the second new solution is directly accepted, and the global optimal solution is obtained. Otherwise, randomly selecting a second disturbance operator again to disturb the line in the second new solution until the disturbance times reach a second threshold value, and then receiving the second new solution by using the simulated annealing probability to obtain a global optimal solution.

And the iteration module is used for updating the iteration times and judging whether the iteration threshold is reached. And if the iteration threshold is reached, outputting a global optimal solution to acquire a round trip line and a scheduling optimization scheme. Otherwise, the global optimal solution of the current iteration times is used as the current solution to continue iteration.

By adopting the technical scheme, the invention can obtain the following technical effects:

the round trip line and the timetable planned by the round trip line and the timetable acquiring method provided by the embodiment of the invention can greatly improve the income of inter-city custom passenger transport. And the calculation speed of the method is faster.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a flow diagram of a round trip line and schedule acquisition method.

FIG. 2 is a logical block diagram of clustering orders spatially and temporally.

Fig. 3 is a logical block diagram of calculating an initial solution using a greedy algorithm.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Embodiment 1,

Referring to fig. 1 to 3, a first embodiment of the present invention provides a method for acquiring a round trip line and a schedule of inter-city customized passenger traffic, which can be performed by an acquiring apparatus (hereinafter referred to as an acquiring apparatus) for the round trip line and the schedule of inter-city customized passenger traffic. In particular, by one or more processors in the acquisition device, to implement steps S1 to S7.

It is understood that the acquiring device may be an electronic device with computing performance, such as a portable notebook computer, a desktop computer, a server, a smart phone, or a tablet computer.

Specifically, the embodiment of the invention aims to mine potential travel rules through large-scale inter-city historical network vehicle order data, and according to a series of travel constraint conditions, a line and a schedule which can be opened between two cities and comprise round trips are manufactured. In addition, the practical factors that the driver can return to the original place of departure are fully considered, and a certain rest time is set in the way of round trip, so that the method has good practical significance and plays a certain guiding role in the coordinated transportation of urban traffic.

Based on the above embodiments, in an alternative embodiment of the present invention, the objective function of the round trip line and schedule optimization model is:

constraint functions of the round trip line and schedule optimization model are:

in the method, in the process of the invention,

the representation aims at maximizing the total income,

To be from->Return from city,

Representing from->City departure round trip ring set,/->Representing from->A round trip ring for city departure,

Indicating round trip ring->The number of lines, & gt>Numbering the circuit,

Departure date set for historical demand points, +.>Is the departure date,

For departure time set, < >>Is the departure time,

Is ticket price,

Is an uplink set, ">Is downlink set, ">For uplink, & gt>Is a downlink,

For uplink +.>Total number of shifts, & gtof->For downlink +.>The total number of shifts,

Numbering the shifts of the lines,

To choose the uplink +.>Is>Shift as round trip ring->Is>Decision variables of the lines,

For whether or not to select the downlink +.>Is>Shift as round trip ring->Is>Decision variables of the lines,

For uplink +.>In (1), departure time is->Departure date->The number of people getting on the car,

For downlink +.>In (1), departure time is->Departure date->The number of people getting on the car,

Indicating round trip ring->The number of lines of (C),

To choose whether to get on the bus station->As uplink +.>Decision variables of the station,

For get-on center point subset set, +.>Is a set of center points for getting off,

To choose whether to get on the bus station->Corresponding get-off station- >As uplink +.>Decision variables of the station,

For uplink +.>Station count of (4),

Numbering the stations,

For uplink +.>Whether or not to get from site->To site->A passing decision variable,

Representing uplink +.>At the first city->Each site is,

For uplink +.>Whether or not in the starting city from->Personal site to->Decision variables passed by individual sites,

Representing uplink +.>At the destination city->Each site is,

For uplink +.>Whether or not the city is from +.>Personal site to->Decision variables passed by individual sites,

Representing uplink +.>At the last site of the starting city,

Representing city->High-speed entrance/exit of (a),>representing city->High speed of out of (a)An inlet port,

For uplink +.>Decision variables for whether to pass from the last station of the starting city to the high-speed entrance,

For uplink +.>Whether or not to get from city->High-speed gateway to city->Decision variables for the passage of the high-speed gateway,

Representing uplink +.>At the destination city->Each site is,

For uplink +.>Whether or not to go from the high-speed entrance of the destination city to the first +.>Decision variables passed by individual sites,

Is city->The maximum number of boarding stations,

Is city->The maximum number of the stops for getting off,

For uplink +.>At the first city->Personal site and->Travel time between stations,

For uplink +.>Travel time between the last stop of the starting city and the high speed entrance of city A,

Is the maximum time limit of city A,

For uplink +.>Travel time between the high-speed entrance of city B and the first departure station of the destination city,

For uplink +.>At the destination city->Personal site and->Travel time between stations,

Is the maximum time limit of city B,

For uplink +.>The get-on detour coefficient,

Is the maximum detour coefficient of the city A,

For uplink +.>A get-off detour coefficient,

Is the maximum detour coefficient of city B,

Is the earliest departure time,

For uplink +.>Whether or not at time->Decision variable capable of departure,

For uplink +.>Is>The departure time of the shift,

Is the latest departure time,

To meet the minimum full load rate of custom passenger operation,

For uplink +.>In departure time->The daily full rate of the shift,

For customizing passenger vehiclesMaximum passenger carrying number,

For site->Travel time difference of (2),

Can tolerate travel time difference for passengers,

A boarding walking distance which is the point of the boarding requirement,

Service distance for boarding station,

A distance for getting off the vehicle at the required point,

Service distance for getting-off station,

Is the shortest time to come and go,

For downlink +.>Is>The departure time of the shift,

For uplink +.>Is>The end point of shift reaches the moment,

Is the longest rest time,

For maximum number of edges of vehicle,/-for>Is a positive integer set,

For uplink +.>Is>Shift numberA departure time of (a),

For downlink +.>Is>The end point of shift reaches the moment,

Is round trip ring->Is a full load ratio of (2).

Wherein, the formulas (1) to (3) are the objective functions of the model. Equations (4) to (22) are constraints of the model.

Formulas (1) to (3) represent maximizing the total profit of all the constituent round trip ring routes, wherein,for round-trip benefits from city A, +.>To obtain the return ring from city B, the return ring includes both the uplink and downlink returns that make up the return ring.

Equation (4) ensures that one site is not selectable by other lines after being selected by a line, and can only be selected at most once by that line. Equation (5) ensures that if a pick-up point is selected as a station on a line, its corresponding pick-up point is also a station on the line, i.e., one line can provide both pick-up and pick-up services. Equation (6) ensures continuity from station to station on the line. The formula (7) is a station number constraint, so that the line is ensured to stop at least one pair of boarding and alighting stations in the whole process, no load is avoided, and meanwhile, the station number does not exceed the maximum station number limit, so that the passenger riding satisfaction and comfort level are prevented from being reduced due to the fact that the station number is too large. Equation (8) ensures that the time between the first site location on the line to the point of departure from the starting city does not exceed the maximum time limit for the starting city. Equation (9) ensures that the time between the entry point of the destination city on the line to the last site of the destination city does not exceed the maximum time limit of the destination city. The formula (10) is the detour coefficient constraint of the getting on/off vehicle. And the formula (11) is a departure time constraint, namely, the departure time is not earlier than the earliest departure time and not later than the latest departure time. Equation (12) is a line opening constraint, i.e., no lower than the minimum full rate requirement, otherwise line opening is meaningless. Equation (13) ensures that the number of boarding passes for any line shift does not exceed the maximum passenger capacity of the custom passenger vehicle. Equation (14) provides that the passenger can tolerate travel time difference constraint, and the arrival time is ensured to be within the acceptable time range of the passenger. Equations (15) and (16) are passenger travel distance constraints, and the passenger travel distance from the nearest boarding station is appropriate, and the travel distance to the alighting station is appropriate. Equation (17) ensures that the uplink for each shift can only be selected once by the round trip ring. Equation (18) ensures that the downlink per shift can only be selected once by the round trip ring. Equation (19) ensures that a certain time is required for the vehicle to return after the vehicle is routed, and the longest resting time cannot be exceeded. Equation (20) ensures that the number of lines going to and from the ring cannot exceed the maximum number of edges. Equation (21) ensures that a certain time is required to rest between the round trip lines of the round trip ring. Equation (22) ensures that the round trip ring full rate of opening is not lower than the minimum full rate.

Specifically, the round trip route and schedule optimization model of the embodiment of the invention aims at maximizing the total income of all the round trip loop routes, and simultaneously aims at minimizing the travel cost of passengers and meeting the running condition as basic constraint, and simultaneously considers the rest constraint during the round trip of a driver and the maximum limit frequency constraint of a vehicle, wherein the optimization variables comprise route variables, scheduling variables, arrival time and departure time.

In an alternative embodiment of the present invention, based on the above embodiment, the get-on detour coefficientThe calculation model of (2) is as follows:

in the method, in the process of the invention,for uplink +.>Station count and->For uplink +.>First->Personal site to->Distance of individual sites->And->Respectively represent uplink +.>At the first city->And (b)Personal site,/->For uplink +.>Last site in starting City to City +.>Is a distance from the high-speed entrance to the high-speed exit; />For uplink +.>Last site in the starting city, +.>For uplink +.>Station count and->Representing city->High-speed entrance/exit of (a),>for uplink +.>At the first city of origin1 site to City->Distance of high-speed entrance/exit of (2)>Representing uplink +. >Site 1 in the starting city;

based on the above embodiments, in an alternative embodiment of the present invention, the get-off detour coefficientThe calculation model of (2) is as follows:

in the method, in the process of the invention,for uplink +.>Station count and->For uplink +.>At the destination city->Personal site and->Distance of individual sites->And->Respectively represent the uplinkLine->At the destination city->And (b)Personal site,/->For uplink +.>First site in destination city to city +.>Distance of high-speed entrance/exit of (2)>For uplink +.>First site in destination city, +.>Is city->A high-speed inlet and outlet,For uplink +.>Last site in destination City to City +.>Distance of high-speed entrance/exit of (2)>For uplink +.>At the last site of the destination city; />

In an alternative embodiment of the present invention, based on the above embodiment, the vehicle is in an uplinkTo->Daily-average full rate for the time of departure +.>The calculation model of (a) is shown in the formula (25) and the formula (26):

in the method, in the process of the invention,departure date set for historical demand points, +.>For departure date,/->Is of no meaning for the alternative symbol>For uplink +.>Whether or not at time->Decision variable for departure, ++ >For uplink +.>In (1), departure time is->The departure date isThe number of people getting on the bus and the number of people getting on the bus>To customize the maximum passenger capacity of the passenger vehicle.

Some definitions in the scenario of constructing round trip lines and schedule optimization models are described below:

first, a road network diagram between two cities is recorded as. Wherein (1)>Representing a set of all points on the map, +.>Representing points on a map and a set of edges of the points. For->，/>Represents the optimal distance between any two points, +.>Indicating the travel time between the two points. Point set->Can be split into->，、/>、/>，/>And->The passenger getting-on and getting-off points are respectively set, and the passenger getting-on and getting-off points are in one-to-one correspondence with one another, and are +.>Is a set of highway entrance points between two cities, wherein +.>、/>Respectively represent city->And city->。

Order theRepresentation->、/>Two city passengers get on the car point set, city +.>Passenger boarding point setThe method comprises the steps of carrying out a first treatment on the surface of the City->Passenger get-on point set +.>。

Order theRepresentation->、/>Two city passengers get off the point set, city +.>Passenger drop-off point setThe method comprises the steps of carrying out a first treatment on the surface of the City->Passenger drop-off point set。

Set of boarding points for passengersAnd passenger get-off set +.>In (1) select->For alternative sites, constitute the alternative site set +.>. City->Alternative station for getting onSet- >City->Get-off candidate site set。

Set of boarding points for passengersAnd passenger get-off set +.>In (1) select->For alternative sites, constitute the alternative site set +.>. City->Is a set of alternative stops for boarding->City->Get-off candidate site set。

Let the departure date set of the historical demand points beDeparture date Co->Day, arbitrary departure date is->. Departure time set is +.>Co-ordination of->The departure time is +.>. Uplink set->The number of lines is +.>Strip, arbitrary line is->. Downlink setThe number of lines is +.>Strip, arbitrary line is->。

Other definitions:

definition 1: the detour coefficient reflects the degree of detour of the route during the running of the vehicle.

The detour coefficient is divided into an upper detour coefficient and a lower detour coefficient. Coefficient of detouring on busThe ratio of the actual vehicle mileage from the first station on the line to the expressway exit point of the starting city through each station in the starting city to the direct road mileage from the first station on the line to the expressway exit point of the starting city is shown in the formula (23). Get-off detour coefficient->The ratio of the actual vehicle mileage from the entrance point of the expressway of the destination city to the final station of the destination city, through each station of the destination city, to the direct road mileage from the entrance point of the expressway of the destination city to the final station of the destination city is shown in the formula (24).

Definition 2: round trip ring means a round trip string (i.e., a plurality of round trip strings are connected) that combines the uplink and downlink lines in one day into one starting point and one ending point, both of which are one city, under the condition that the vehicle operation is satisfied. A round trip string refers to a plurality of uplinks and downlinks or a combination of downlinks and uplinks that meet the engagement time and place.

Make the round trip ring set as. Wherein (1)>Represents the round-trip ring set starting from city A with the round-trip ring number +.>Any round trip ring thereof is +.>。/>Represents the round-trip ring set starting from city B with the round-trip ring number +.>Any round trip ring thereof is +.>。

Specifically, the network about vehicle history order data includes an order in which a city is opened to B city and B city is opened to a city. The order information content comprises order id, reserved departure time, starting point information, starting point longitude and latitude, end point position, end point longitude and latitude, number of people and the like.

The embodiment of the invention processes the historical order data of the network about vehicles and screens out completed (state=100) orders in all orders.

And S3, clustering the space and time of orders according to the historical order data of the network about vehicles, and obtaining a subset of center points of getting on and off the vehicles.

Specifically, the round trip line and timetable acquisition method in the embodiment of the invention is based on historical order data of the network bus, and the line and timetable meeting the inter-city bus running conditions are optimized according to the travel characteristics of the historical passenger order data. Therefore, the historical order data of the network about vehicles needs to be preprocessed, and needed information is extracted from the historical order data.

On the basis of the above embodiment, in an alternative embodiment of the present invention, step S3 specifically includes steps S31 to S35.

S31, calculating the sum of the distance between the boarding stations and the distance between the alighting stations according to the historical order data of the network appointment vehicles.

S32, judging whether the sum of the get-on station distance and the get-off station distance is smaller than the sum of a get-on radius threshold and a get-off radius threshold. If the data is smaller than the historical order data, classifying the two orders into a cluster, otherwise, continuing to traverse the historical order data of the network taxi taking, and until the traversing is completed.

S33, calculating longitude and latitude average values of the get-on position and the get-off position of the order in the same cluster, and obtaining a get-on temporary point and a get-off temporary point.

S34, acquiring a get-on position closest to the get-on temporary point and a get-off position closest to the get-off temporary point in the same cluster order, marking the get-on central point and the get-off central point of the same cluster order, and acquiring a get-on and get-off central point set.

And S35, splitting the get-on/off center point set according to the departure time to obtain a get-on/off center point subset in different time periods.

Specifically, according to the historical order data of the network about vehicles in the step S2, the on-off station point pairs taking the A city as the starting city, the B city as the ending city and the B city as the starting city and the A city as the ending city are respectively determined, and the on-off alternative station space-time clustering design is carried out.

Alternative site design based on spatial distance referring to fig. 2, the same principle is designed based on temporal distance. Taking the boarding station as an example, the alighting station is the same as the alighting station:

and the first step, inputting all the information of the getting-on and getting-off points in sequence, and setting a maximum getting-on radius threshold value and a maximum getting-off radius threshold value. And calculating the distance between the getting-on points and the getting-off points between every two orders, and finding a pair of getting-on and getting-off points closest to the distance to be classified into a cluster. Judging whether the sum of the getting-on distance and the getting-off distance of the pair of getting-on and getting-off points is smaller than the sum of the maximum getting-on radius threshold value and the maximum getting-off radius threshold value, classifying the getting-on and getting-off points into one cluster if the sum is smaller than the sum of the maximum getting-on radius threshold value and the maximum getting-off radius threshold value, and classifying the getting-on and getting-off points into two different clusters if the sum is smaller than the sum of the maximum getting-off radius threshold value and the maximum getting-off radius threshold value.

And step two, judging whether all orders are traversed, if not, continuing to traverse, repeating the step one, and jumping out the circulation until the orders are traversed, and outputting the number of samples in all clusters from high to low.

And thirdly, determining the position of the central point of each cluster. Specifically, the longitude sum of all points in the cluster obtained in the second step is divided by the number of points, the latitude calculation method is the same, and the point obtained by the longitude and the latitude is set as a temporary point. And simultaneously calculating the distances from all points in the category to the temporary point, defining the nearest point as the center point in the category, and recording the position of an alternative boarding station.

And fourthly, taking the fact that the difference of the reserved departure time of passengers in the same alternative station is large after the spatial clustering of the upper station is completed, causing pressure to the time arrangement of the subsequent lines and vehicles, and increasing the calculated amount. It is therefore proposed to split the passenger demands of the same station further, i.e. to split the departure time set of passengers within the station into several departure periods according to the departure time differences.

Specifically, the time distance of the sample is determined by Euclidean distance method. The Euclidean distance method converts the numerical value of the time format into the time stamp format, and the time stamp format is placed on a time axis with the vertical axis of 0, so that the conversion from the Euclidean distance two-dimensional space calculation method to the one-dimensional space is completed. Such as 07:15:00 is converted into a time stamp 1638900, 07:30: and (3) converting 00 into 1639800, wherein the time distance between the two is 900 as the time stamp.

This step may result in a further division of the time attribute under each category, i.e. a large set under each same center point may be divided into a plurality of time-different subsets. At this time, it should be noted that the departure point does not include the reserved departure time information, so that secondary clustering of the departure point is not required.

And S4, solving by using a greedy algorithm according to greedy rules with the maximum number of serviceable people according to the round trip route and schedule optimization model and the on-off center point subset, and obtaining an initial solution. Wherein the initial solution includes a plurality of round trip loops. The shuttle ring includes at least one shuttle string. The round trip string contains 1 uplink and 1 downlink.

On the basis of the above embodiment, in an alternative embodiment of the present invention, step S4 specifically includes steps S41 to S47.

S41, initializing a slave according to the network about vehicle historical order data and the on-off center point subsetCity departure round trip ring set->And from->City departure round trip ring set->。

S42, according to the number of serviceable persons at the site, returning to the ring setLine addition->A pair of departure/departure stations for city departure and often the return set +. >Line addition->A pair of boarding and alighting stations for city departure.

S43, judging whether the line added with the station meets the single line constraint according to the round trip line and the schedule optimization model.

And S44, if the line added with the station meets the single line constraint, further judging whether the line added with the station meets the round trip ring constraint. If the line after adding the station does not meet the single line constraint, deleting the added station, and then adding the next pair of boarding and alighting stations to judge again.

S45, if the line added with the station meets the round trip ring constraint, collecting the round trip ringsThe uplink and the downlink of (a) are paired and the round trip ring set is +.>And (3) pairing the downlink and the uplink, and judging whether the paired round trip strings meet the constraint of a round trip line and a schedule optimization model.

S46, if the paired round trip strings meet the constraint of the round trip line and the schedule optimization model, judging whether all stations in the center point subset of the on-off vehicles are arranged in the line.

S47, if the sites of the central point subset of the getting-on and getting-off vehicles are all arranged, outputting a final round-trip ring setAnd round trip ring set- >. Otherwise, continuing to add unscheduled sites to the line until all sites are scheduled.

As shown in fig. 3, the embodiment of the present invention obtains a feasible round trip ring initial solution by using a greedy algorithm according to a greedy rule with the maximum number of serviceable people for all the upper and lower stops (the stops obtained according to step S3) input into the round trip line and schedule optimization model. Wherein, the formulas (1) to (3) in the step S1 are taken as evaluation functions, and the current optimal solution is initialized. This step is illustrated with reference to fig. 3. Specific:

and step one, inputting according to the order obtained in the step S2 and the alternative site set obtained in the step S3. Initializing a round-trip ring setRound trip ring set->. Wherein, round trip ring set at the beginning +.>Round trip ring set->Is an empty set.

And secondly, respectively adding a pair of getting-on and getting-off stations from A to B and from B to A, wherein the number of the serviceable people is the largest.

Thirdly, judging whether single line constraint is met, if yes, turning to a fourth step; otherwise, deleting the station, adding the next station with the largest number of servable persons to get on or off, and continuing to return to the third step. Wherein the single line constraint comprises equations (4) through (16). The constraint condition of the whole model is represented by the formulas (4) to (22). Equation (17) to equation (22) are constraint of the shuttle ring.

And step four, judging whether the routes from A to B and B to A are generated or not, if yes, turning to step five, otherwise, adding the next pair of upper and lower stops, and returning to the step three. The condition of the route generation is that all the alternative sites are traversed or the constraint of the maximum number of sites in the route is no longer met.

And fifthly, executing opposite operations, respectively adding a pair of boarding and alighting stations from A to B and from A to B, then executing single line judging operation (same as the third step), judging whether the lines from B to A and from A to B are generated or not, if yes, turning to the sixth step, otherwise, returning to the fifth step. Specifically, the addition of each means that the lines from a to B and B to a are generated in the fourth step, respectively. The opposite is then performed, with the lines from B to A and A to B immediately following the lines from A to B and B to A. That is: a is to B: b to A, and B to A: a and B form a round trip string. The fifth step is different from the second step in that the order of the inserted start city and end city is changed.

And sixthly, judging whether the maximum round trip frequency constraint is met, if yes, turning to a seventh step, otherwise, turning back to the second step. In this embodiment, the maximum round trip number is 4, which is a value considered to be defined, and the present invention is not particularly limited thereto. The reason for setting this value is that the driver has a working time in one day and cannot carry passengers with unlimited trips, and is therefore limited by the maximum number of trips.

Seventh, judging whether the site set is empty, if so, outputting the round trip ring setAnd round trip ring set->Otherwise, continuing the operation of the next round trip ring, and returning to the second step.

Specifically, a disturbance operator is selected to locally disturbance the line, so that a locally optimal solution is obtained. The purpose of the perturbation operator is to further improve the solution quality of the initial solution. The inventor analyzes specific conditions, and designs three neighborhood operators to disturb the current solution after a great deal of creative labor. In this embodiment, the probabilities of the three neighborhood operators are the same, and the disturbance operator is selected by adopting a mode of randomly selecting the disturbance operator, so that the randomness and the effectiveness of disturbance are ensured, and the situation of trapping in local optimum is avoided. In other embodiments, the perturbation operator may be selected by other means, such as adaptive weights, which are not particularly limited by the present invention.

In an alternative embodiment of the present invention, the first perturbation operator includes a first swap neighbor operator, a first reorganization neighbor operator, and a first interpolation neighbor operator. And each time the first disturbance operator is selected, carrying out disturbance for a first preset number of times.

The first switching neighborhood operator is used to select two stations at a time from different lines and switch the two different stations into the line to which each other belongs.

The first reassembly neighborhood operator is used to shuffle two different uplinks, and the scattered sites reassemble into two new routes.

The first insertion neighborhood operator is used for inserting the unassigned sites into the line, if the constraints of the round trip line and the schedule optimization model are met, the insertion is successful, otherwise, the unassigned sites are inserted into the next line until the insertion is successful or all lines fail.

Specifically, after 1 first disturbance operator is selected each time, 30 times of disturbance are carried out by using the selected disturbance operator, one time of result evaluation is carried out after each disturbance, if the total income after the local optimization is not improved, the neighborhood search is ended, and otherwise, the next local optimization is carried out. The complexity of the operation is . In other embodiments, the scramblingThe number of movements may be set to other values, which are not particularly limited by the present invention.

S6, randomly selecting a second disturbance operator to disturb the round trip loop in the local optimal solution, and obtaining a second new solution. And judging whether the second new solution is better than a local optimal solution or not according to the objective of the round trip line and the schedule optimization model after disturbance. If the second new solution is better than the local optimal solution, the second new solution is directly accepted, and the global optimal solution is obtained. Otherwise, randomly selecting a second disturbance operator again to disturb the line in the second new solution until the disturbance times reach a second threshold value, and then receiving the second new solution by using the simulated annealing probability to obtain a global optimal solution.

Specifically, a disturbance operator is selected to carry out overall disturbance on the round trip ring, and a global optimal solution is obtained. The second perturbation operator is similar to the first perturbation operator except that the neighborhood of perturbations is shifted from the line to the round trip ring.

In an alternative embodiment of the present invention, the second perturbation operator includes a second swap neighbor operator, a first merge neighbor operator, and a second insert neighbor operator. And carrying out disturbance for a second preset number of times when the second disturbance operator is selected each time.

The second switching neighborhood operator is used to select two uplinks or downlinks from different round trip rings and switch the two uplinks into the round trip ring to which each other belongs.

The first merge neighborhood operator is used to select all lines contained in the two round-trip rings and form one round-trip ring.

And the second insertion neighborhood operator is used for inserting the unallocated line into the round-trip ring, if the constraint of the round-trip line and the schedule optimization model is met, the insertion is successful, otherwise, the unallocated line is inserted into the next round-trip ring until the insertion is successful or all round-trip rings are failed to be inserted.

Specifically, after 1 second disturbance operator is selected each time, 30 times of disturbance are carried out by using the selected second disturbance operator, one time of result evaluation is carried out after each disturbance, if the total income after global optimization is not improved, the neighborhood search is ended, otherwise, the next office is carried outAnd (5) optimizing. The complexity of the operation is。

In this embodiment, the evaluation steps after the first disturbance operator and the second disturbance operator are the same, and the overall optimal solution is judged according to the evaluation function to be better than the current solution, if so, the optimal solution is updated, the iteration number is increased once, otherwise, the new solution is accepted by the simulated annealing probability, the optimal solution is updated, and the iteration number is increased once. For example: the current iteration number is 12, and the neighborhood search is finished if the total gain after optimization is not improved, and the 12 th iteration is terminated. Otherwise, the new solution is accepted by the simulated annealing probability, the optimal solution is updated, the iteration number is increased once, whether the 12 th iteration scheme is accepted or not is judged, then the iteration number is increased by 1, and the 13 th iteration is ready to start.

The new solution of the simulated annealing probability is specifically: is provided withFor the current solution->The new solutions obtained after operator removal and insertion are calculated by the evaluation function, and the total gains are +.>Andlet the initial temperature be +.>The temperature change rate is->Temperature->The update formula for each iteration is as follows:

simulated annealing probabilityThe calculation formula of (2) is as follows

Specifically, after the preset iteration times are reached, iteration is terminated, and an iteration result is output. The output result is a round trip ring set; and parameters of each line in the round trip ring set. Which includes round trip routes and schedules, daily full rate and revenue for each shift of the round trip ring.

Specifically, the round trip line and the timetable planned by the round trip line and the timetable acquiring method provided by the embodiment of the invention can greatly improve the income of inter-city custom-made passenger transport. And the calculation speed of the method is faster. The method for acquiring the round trip line and the timetable can ensure riding experience and comfort of passengers. And simultaneously, decision support is provided for an operation enterprise.

Embodiment II,

And the clustering module is used for clustering the space and time of orders according to the network about vehicle historical order data to acquire a subset of the center points of getting on and off the vehicle.

And the initial solution calculation module is used for solving according to the round trip line and schedule optimization model and the on-off center point subset by using a greedy algorithm and according to greedy rules with the maximum number of serviceable people, so as to obtain an initial solution. Wherein the initial solution includes a plurality of round trip loops. The shuttle ring includes at least one shuttle string. The round trip string contains 1 uplink and 1 downlink.

And the global optimization module is used for randomly selecting a second disturbance operator to disturb the round trip ring in the local optimal solution to obtain a second new solution. And judging whether the second new solution is better than a local optimal solution or not according to the objective of the round trip line and the schedule optimization model after disturbance. If the second new solution is better than the local optimal solution, the second new solution is directly accepted, and the global optimal solution is obtained. Otherwise, randomly selecting a second disturbance operator again to disturb the line in the second new solution until the disturbance times reach a second threshold value, and then receiving the second new solution by using the simulated annealing probability to obtain a global optimal solution.

Based on the foregoing embodiment, in an optional embodiment of the present invention, the clustering module specifically includes:

and the distance calculating unit is used for calculating the sum of the distance between the boarding stations and the distance between the alighting stations according to the historical order data of the network appointment vehicles.

And the clustering unit is used for judging whether the sum of the distance between the boarding station and the distance between the alighting station is smaller than the sum of the threshold value of the boarding radius and the threshold value of the alighting radius. If the data is smaller than the historical order data, classifying the two orders into a cluster, otherwise, continuing to traverse the historical order data of the network taxi taking, and until the traversing is completed.

The temporary point acquisition unit is used for calculating longitude and latitude mean values of the get-on position and the get-off position of the same cluster of orders and acquiring the get-on temporary point and the get-off temporary point.

The central point acquisition unit is used for acquiring a get-on position closest to the get-on temporary point and a get-off position closest to the get-off temporary point in the same cluster of orders, marking the get-on central point and the get-off central point of the same cluster of orders, and acquiring a get-on and get-off central point set.

And the center point sub-splitting unit is used for splitting the get-on and get-off center point set according to the departure time to obtain the get-on and get-off center point subsets in different time periods.

In an alternative embodiment of the present invention, based on the above embodiment, the initial solution calculation module specifically includes:

an initialization unit for initializing slave units according to the network about vehicle history order data and the on-off center point subsetCity departure round trip ring set->And from->City departure round trip ring set->。

Site joining unit for returning ring set according to the number of serviceable persons at siteLine addition->A pair of departure/departure stations for city departure and often the return set +.>Line addition->A pair of boarding and alighting stations for city departure.

And the first constraint judging unit is used for judging whether the line added with the station meets the single line constraint according to the round trip line and the schedule optimization model.

And the second constraint judging unit is used for further judging whether the line added with the station meets the round trip ring constraint if the line added with the station meets the single line constraint. If the line after adding the station does not meet the single line constraint, deleting the added station, and then adding the next pair of boarding and alighting stations to judge again.

A line pairing unit for aggregating the round-trip ring if the line added with the station meets the constraint of the round-trip ringThe uplink and the downlink of (a) are paired and the round trip ring set is +.>And (3) pairing the downlink and the uplink, and judging whether the paired round trip strings meet the constraint of a round trip line and a schedule optimization model.

And the first iteration unit is used for judging whether all stations in the on-off center point subset are arranged in the route or not if the paired round trip strings meet the constraint of the round trip route and the schedule optimization model.

A second iteration unit for outputting a final round trip ring set if the stations of the subset of the center points of the getting-on and getting-off have been arrangedAnd round trip ring set->. Otherwise, continuing to add unscheduled sites to the line until all sites are scheduled.

In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. The apparatus and method embodiments described above are merely illustrative, for example, flow diagrams and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In addition, functional modules in the embodiments of the present invention may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.

The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, an electronic device, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes. It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It should be understood that the term "and/or" as used herein is merely one relationship describing the association of the associated objects, meaning that there may be three relationships, e.g., a and/or B, may represent: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.

Depending on the context, the word "if" as used herein may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to detection". Similarly, the phrase "if determined" or "if detected (stated condition or event)" may be interpreted as "when determined" or "in response to determination" or "when detected (stated condition or event)" or "in response to detection (stated condition or event), depending on the context.

References to "first\second" in the embodiments are merely to distinguish similar objects and do not represent a particular ordering for the objects, it being understood that "first\second" may interchange a particular order or precedence where allowed. It is to be understood that the "first\second" distinguishing aspects may be interchanged where appropriate, such that the embodiments described herein may be implemented in sequences other than those illustrated or described herein.

The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for acquiring round trip routes and schedules for inter-city custom passenger traffic, comprising:

constructing a round-trip line and schedule optimization model which aims at maximizing the total income of all inter-city customized passenger lines in the round-trip line, aims at minimizing the travel cost of passengers and meeting the running condition as basic constraint and simultaneously comprises rest constraint based on inter-city customized passenger traffic round-trip rings, lines, schedules and the number of passengers between two cities;

Acquiring historical order data of a network vehicle between an A city and a B city; the network appointment vehicle history order data comprises a vehicle loading position and a vehicle unloading position;

clustering the space and time of orders according to the historical order data of the network taxi, and obtaining a central point subset of getting on and getting off;

according to the round trip line and timetable optimization model and the getting-on and getting-off center point subset, solving by a greedy algorithm according to greedy rules with the maximum number of serviceable people, and obtaining an initial solution; wherein the initial solution comprises a plurality of round trip rings; the shuttle ring includes at least one shuttle string; the round trip string comprises 1 uplink and 1 downlink;

randomly selecting a first disturbance operator to disturb a line in a current solution to obtain a first new solution; judging whether the first new solution is better than the current solution according to the objective of the round trip line and the schedule optimization model after disturbance; if the first new solution is better than the current solution, directly receiving the first new solution to obtain a local optimal solution; otherwise, randomly selecting a first disturbance operator again to disturb the line in the first new solution until the disturbance times reach a first threshold value, and then receiving the first new solution by using the simulated annealing probability to obtain a local optimal solution; when disturbance is performed for the first time, taking the initial solution as the current solution;

Randomly selecting a second disturbance operator to disturb the round trip loop in the local optimal solution to obtain a second new solution; judging whether the second new solution is better than a local optimal solution or not according to the round trip line and the target of the schedule optimization model after disturbance; if the second new solution is better than the local optimal solution, directly receiving the second new solution to obtain a global optimal solution; otherwise, randomly selecting a second disturbance operator again to disturb the circuit in the second new solution until the disturbance times reach a second threshold value, and then receiving the second new solution by using the simulated annealing probability to obtain a global optimal solution;

updating the iteration times and judging whether the iteration threshold is reached; if the iteration threshold is reached, outputting a global optimal solution to acquire a round trip line and a scheduling optimization scheme; otherwise, taking the global optimal solution of the current iteration times as the current solution to continue iteration;

according to the historical order data of the network taxi, clustering the space and time of the orders to obtain a taxi getting-on and getting-off central point subset, which comprises the following steps:

calculating the sum of the distance between the boarding stations and the distance between the alighting stations according to the historical order data of the network appointment vehicles;

judging whether the sum of the distance of the boarding station and the distance of the alighting station is smaller than the sum of a boarding radius threshold value and a alighting radius threshold value; if the data is smaller than the historical order data, classifying the two orders into a cluster, otherwise, continuing to traverse the historical order data of the network vehicle, until the traversing is completed;

Calculating longitude and latitude average values of a get-on position and a get-off position of an order in the same cluster, and acquiring a get-on temporary point and a get-off temporary point;

acquiring a get-on position closest to the get-on temporary point and a get-off position closest to the get-off temporary point in the same cluster of orders, marking the get-on central point and the get-off central point of the same cluster of orders, and acquiring a get-on and get-off central point set;

and splitting the get-on and get-off center point set according to the departure time to obtain a get-on and get-off center point subset in different time periods.

2. The method for acquiring the round trip line and the schedule of the inter-city customized passenger traffic according to claim 1, wherein the objective function of the round trip line and the schedule optimization model is:

in the method, in the process of the invention,

the representation aims at maximizing the total income,

To be from->Return from city,

Indicating round trip ring->The number of lines, & gt>Numbering the circuit,

Departure date set for historical demand points, +. >Is the departure date,

For departure time set, < >>Is the departure time,

Is ticket price,

Is an uplink set, ">Is downlink set, ">For uplink, & gt>Is a downlink,

Numbering the shifts of the lines,

Indicating round trip ring->The number of lines of (C),

For get-on center point subset set, +. >Is a set of center points for getting off,

To choose whether to get on the bus station->Corresponding get-off station->As uplink +.>Decision variables of the station,

For uplink +.>Station count of (4),

Numbering the stations,

Representing uplink +.>At the first city->Each site is,

Representing uplink +.>At the destination city->Each site is,

Representing uplink +.>At the last site of the starting city,

Representing city->High-speed entrance/exit of (a),>representing city->A high-speed inlet and outlet,

Representing uplink +.>At the destination city->Each site is,

Is city->The maximum number of boarding stations,

Is city->The maximum number of the stops for getting off,

Is the maximum time limit of city A,

Is the maximum time limit of city B,

For uplink +.>The get-on detour coefficient,

Is the maximum detour coefficient of the city A,

For uplink +.>A get-off detour coefficient,

Is the maximum detour coefficient of city B,

Is the earliest departure time,

For uplink +.>Whether or not at time->Decision variable capable of departure,

For uplink +.>Is>The departure time of the shift,

Is the latest departure time,

To meet the minimum full load rate of custom passenger operation,

For uplink +.>In departure time->Is of the class (f)The next day is full of load rate,

To customize the maximum passenger capacity of a passenger vehicle,

For site->Travel time difference of (2),

Can tolerate travel time difference for passengers,

A boarding walking distance which is the point of the boarding requirement,

Service distance for boarding station,

A distance for getting off the vehicle at the required point,

Service distance for getting-off station,

Is the shortest time to come and go,

For downlink +.>Is>The departure time of the shift,

For uplink +.>Is>The end point of shift reaches the moment,

Is the longest rest time,

For maximum number of edges of vehicle,/-for>Is a positive integer set,

For uplink +.>Is>The departure time of the shift,

For downlink +.>Is>The end point of shift reaches the moment,

Is round trip ring->Is a full load ratio of (2).

3. The method for obtaining round trip routes and schedules for interurban customized passenger transport as claimed in claim 2, wherein the on-board detour coefficients areThe calculation model of (2) is as follows:

in the method, in the process of the invention,for uplink +.>Station count and->For uplink +.>First->Personal site to->Distance of individual sites->And->Respectively represent uplink +. >At the first city->And (b)Personal site,/->For uplink +.>Last site in starting City to City +.>Is a distance from the high-speed entrance to the high-speed exit; />For uplink +.>Last site in the starting city, +.>Representing city->High-speed entrance/exit of (a),>for uplink +.>Site 1 in origin city to city +.>Is higher than the height of (1)Distance of speed entrance/exit->Representing uplink +.>Site 1 in the starting city;

coefficient of detourThe calculation model of (2) is as follows:

in the method, in the process of the invention,for uplink +.>Station count and->For uplink +.>At the destination city->Personal site and->Distance of individual sites->And->Respectively represent uplink +.>At the destination city->Person and->Personal site,/->For uplink +.>First site in destination city to city +.>Distance of high-speed entrance/exit of (2)>For uplink +.>First site in destination city, +.>Is city->A high-speed inlet and outlet,For uplink +.>Last site in destination City to City +.>Distance of high-speed entrance/exit of (2)>For uplink +.>At the last site of the destination city;

daily average full load rateThe calculation model of (2) is as follows:

in the method, in the process of the invention,departure date set for historical demand points, +. >For departure date,/->Is of no meaning for the alternative symbol>For uplink +.>Whether or not at time->Decision variable for departure, ++>For uplink +.>In (1), departure time is->Departure date->The number of people getting on the bus and the number of people getting on the bus>To customize the maximum passenger capacity of the passenger vehicle.

4. The method for obtaining the round trip route and the schedule of inter-city customized passenger traffic according to claim 1, wherein the method for obtaining the initial solution comprises the steps of solving according to a greedy rule with the maximum number of serviceable persons by using a greedy algorithm according to the round trip route and schedule optimization model and the subset of getting-on and getting-off center points, and the method specifically comprises the following steps:

initializing a slave according to the network about vehicle historical order data and the subset of the get-on and get-off central pointsCity departure round trip ring set->And from->City departure round trip ring set->；

Often, a set of loops is returned according to the number of servable people at a siteLine addition->A pair of departure/departure stations for city departure and often the return set +.>Line addition->A pair of boarding and alighting stations for city departure;

judging whether the line added with the station meets the single line constraint according to the round trip line and the schedule optimization model;

if the line added with the station meets the single line constraint, further judging whether the line added with the station meets the round trip ring constraint; if the line added with the stations does not meet the single line constraint, deleting the added stations, and then adding the next pair of boarding and alighting stations to judge again;

If the line added with the site meets the round trip ring constraint, the round trip ring is assembledThe uplink and the downlink of (a) are paired and the round trip ring set is +.>The downlink and the uplink in the network are paired, and whether the paired round trip strings meet the constraint of a round trip line and a schedule optimization model is judged;

if the paired round trip strings meet the constraint of the round trip line and the schedule optimization model, judging whether all stations in the center point subset of the on-off vehicles are arranged in the line or not;

if the stations of the subset of the center points of the getting-on and getting-off have all been arranged, a final round trip ring set is outputAnd round trip ring setThe method comprises the steps of carrying out a first treatment on the surface of the Otherwise, continuing to add unscheduled sites to the line until all sites are scheduled.

5. The method for obtaining round trip routes and schedules for interurban customized passenger transport according to any one of claims 1 to 4, wherein the first perturbation operator comprises a first swap neighbor operator, a first reorganization neighbor operator, and a first interpolation neighbor operator; each time a first disturbance operator is selected, disturbance of a first preset number of times is carried out;

the first switching neighborhood operator is used for selecting two stations from different lines at a time and switching the two different stations into the lines to which the two stations belong;

The first recombination neighborhood operator is used for disturbing two different uplink lines, and the scattered stations are recombined into two new lines;

6. The method for obtaining round trip routes and schedules for interurban customized passenger transport according to any one of claims 1 to 4, wherein the second perturbation operator comprises a second swap neighbor operator, a first merge neighbor operator and a second insert neighbor operator; each time a second disturbance operator is selected, disturbance of a second preset number of times is carried out;

a second switching neighborhood operator for selecting two uplink or downlink lines from different round trip rings and switching the two lines into the round trip rings to which each other belongs;

the first merging neighborhood operator is used for selecting all lines contained in the two round-trip rings and forming a round-trip ring;

7. An apparatus for acquiring a round trip line and a schedule for interurban customized passenger transport, comprising:

the model building module is used for building a round-trip line and schedule optimization model which aims at maximizing the total income of all inter-city customized passenger lines in the round-trip ring, minimizing the travel cost of passengers and meeting the running condition as basic constraint and simultaneously comprises rest constraint based on inter-city customized passenger traffic round-trip rings, lines, schedules and the number of passengers between two cities;

the initial data acquisition module is used for acquiring historical order data of the network vehicle between the city A and the city B; the network appointment vehicle history order data comprises a vehicle loading position and a vehicle unloading position;

the clustering module is used for clustering the space and time of orders according to the historical order data of the network taxi taking, and obtaining a central point subset of the taxi taking;

the initial solution calculation module is used for solving according to the round trip line and schedule optimization model and the on-off center point subset by using a greedy algorithm and a greedy rule with the maximum number of serviceable people to obtain an initial solution; wherein the initial solution comprises a plurality of round trip rings; the shuttle ring includes at least one shuttle string; the round trip string comprises 1 uplink and 1 downlink;

The local optimization module is used for randomly selecting a first disturbance operator to disturb the line in the current solution to obtain a first new solution; judging whether the first new solution is better than the current solution according to the objective of the round trip line and the schedule optimization model after disturbance; if the first new solution is better than the current solution, directly receiving the first new solution to obtain a local optimal solution; otherwise, randomly selecting a first disturbance operator again to disturb the line in the first new solution until the disturbance times reach a first threshold value, and then receiving the first new solution by using the simulated annealing probability to obtain a local optimal solution; when disturbance is performed for the first time, taking the initial solution as the current solution;

the global optimization module is used for randomly selecting a second disturbance operator to disturb the round trip ring in the local optimal solution to obtain a second new solution; judging whether the second new solution is better than a local optimal solution or not according to the round trip line and the target of the schedule optimization model after disturbance; if the second new solution is better than the local optimal solution, directly receiving the second new solution to obtain a global optimal solution; otherwise, randomly selecting a second disturbance operator again to disturb the circuit in the second new solution until the disturbance times reach a second threshold value, and then receiving the second new solution by using the simulated annealing probability to obtain a global optimal solution;

The iteration module is used for updating the iteration times and judging whether the iteration threshold is reached or not; if the iteration threshold is reached, outputting a global optimal solution to acquire a round trip line and a scheduling optimization scheme; otherwise, taking the global optimal solution of the current iteration times as the current solution to continue iteration;

the clustering module specifically comprises:

the distance calculating unit is used for calculating the sum of the distance between the boarding stations and the alighting stations according to the historical order data of the network appointment vehicles;

the clustering unit is used for judging whether the sum of the distance between the boarding station and the distance between the alighting station is smaller than the sum of the threshold value of the boarding radius and the threshold value of the alighting radius; if the data is smaller than the historical order data, classifying the two orders into a cluster, otherwise, continuing to traverse the historical order data of the network vehicle, until the traversing is completed;

the temporary point acquisition unit is used for calculating longitude and latitude average values of the get-on position and the get-off position of the same cluster of orders and acquiring a get-on temporary point and a get-off temporary point;

the central point acquisition unit is used for acquiring a get-on position closest to the get-on temporary point and a get-off position closest to the get-off temporary point in the same cluster of orders, marking the get-on central point and the get-off central point of the same cluster of orders, and acquiring a get-on and get-off central point set;