A modular bus dispatch optimization method for bus corridors

Abstract

A modular bus scheduling optimization method for bus corridors. The present invention belongs to the field of bus scheduling optimization, and specifically relates to a modular bus scheduling optimization method for bus corridors. The purpose of the present invention is to solve the problems of low operating efficiency of existing bus systems, long waiting time for passengers to transfer, long time for passengers on the bus, and high operating costs of bus companies. A modular bus scheduling optimization method for bus corridors has the following process: 1. Collect basic information of bus stops, configure modular vehicles, configure modular bus schedules, and collect passenger travel request data; 2. Define optimization variables; 3. Determine transfer strategies and calculate the number of transfer passengers based on the transfer strategies; 4. Split and combine vehicles to complete passenger transfers, and update schedule information based on passenger transfer results; 5. Establish a modular bus vehicle scheduling optimization model; 6. Solve the modular bus vehicle scheduling optimization model and output the optimal scheduling plan.

Description

Technical Field

[0001] The present invention belongs to the field of public transport scheduling optimization, and in particular relates to a modular public transport scheduling optimization method for public transport corridors. Background Art

[0002] Bus operations along urban arterial corridors meet the daily travel needs of a large number of citizens, playing a crucial role in reducing private car use, alleviating urban traffic congestion, and promoting the sustainable development of the transportation system. However, traditional arterial bus operations still face numerous challenges. For one thing, fixed bus capacity struggles to effectively respond to uneven passenger demand at various stops, and fixed departure intervals inevitably lead to wasted transport capacity during vehicle operation. Furthermore, passengers must wait for a short while before transferring, leading to inconvenience and increased travel time.

[0003] Modular buses, as an emerging public transportation vehicle, offer a new approach to addressing these challenges. During operation, modular buses can be combined into a fleet or split up to accommodate varying passenger flows across different sections. Passengers can also transfer between modular buses within a fleet, eliminating the inconvenience of traditional bus operations requiring passengers to disembark and transfer. Existing bus scheduling methods, primarily based on a fixed number of buses and routes, struggle to adapt to the dynamic passenger flow along urban bus corridors. Especially with modular buses, traditional methods fail to effectively coordinate fleet configuration changes, fail to account for the flexibility of fleet combination and splitting, and fail to optimize the time and efficiency of transfers. Therefore, traditional bus scheduling methods are unsuitable for modular buses. To improve the operational efficiency of modular buses along arterial passenger corridors, a new scheduling method is needed to precisely coordinate the departure times of each modular bus, reduce passenger wait times and travel uncertainty during transfers, and fully leverage the flexibility of modular buses. Summary of the Invention

[0004] The purpose of the present invention is to solve the problems that the existing bus scheduling methods cannot effectively coordinate the changes in the fleet structure, fail to consider the flexibility of fleet combination and splitting, are not suitable for modular buses, and result in low bus system operating efficiency, long passenger transfer waiting time, long passenger on-board time, and high bus company operating costs. A modular bus scheduling optimization method for bus corridors is proposed to solve the problems that the existing bus scheduling methods cannot effectively coordinate the changes in fleet structure, fail to consider the flexibility of fleet combination and splitting, and are not suitable for modular buses.

[0005] A modular bus dispatch optimization method for bus corridors. The specific process is as follows:

[0006] Step 1: Collect basic information of bus stops, configure modular vehicles, configure modular bus schedules, and collect passenger travel request data;

[0007] Step 2: Define optimization variables; the specific process is:

[0008] Defining 0-1 variables Represents a modular vehicle With segment On the flights If the relationship between modular vehicles Participate in the execution shift ,but ,otherwise ;

[0009] Defining 0-1 variables , if the first flights In the section Internal slave site Drive to the station ,but , otherwise it is equal to 0; where the site and All belong to the segment A collection of sites;

[0010] Defining 0-1 variables Indicates a passenger travel request With modular vehicles If the passenger's travel request Modular Vehicles Provide services, then ,otherwise ;

[0011] Defining continuous variables Indicates segment On the flights Arrival section Internal site moment;

[0012] Defining continuous variables Indicates segment On the flights In the section The average running speed within the unit is m / s.

[0013] Step 3: Determine the transfer strategy based on steps 1 and 2, and calculate the number of transfer passengers based on the transfer strategy;

[0014] Step 4: Based on step 3, the vehicles are split and combined to complete the passenger transfer, and the flight information is updated based on the passenger transfer results;

[0015] Step 5: Establish a modular bus dispatch optimization model based on steps 1, 2, 3, and 4;

[0016] Step 6: Solve the modular bus scheduling optimization model and output the optimal scheduling plan .

[0017] The beneficial effects of the present invention are:

[0018] In the context of trunk corridors, the present invention considers the operational characteristics of modular buses and proposes a new modular bus dispatching method, focusing on solving the following key problems:

[0019] The introduction of a modular bus combination and separation mechanism enables the fleet to be dynamically adjusted based on uneven passenger demand, avoiding waste of resources and ensuring that the bus system can more accurately meet passengers' travel needs;

[0020] This invention designs a precise transfer coordination strategy that supports both on-board and off-board transfers, eliminating the inconvenience of having to get off the bus to transfer in traditional public transportation systems. The proposed optimization scheme will improve the efficiency of public transportation systems, reduce passenger transfer waiting time, and shorten the time passengers spend on board.

[0021] The present invention combines the dynamic changes in passenger flow at key stations to fine-tune the distribution and scheduling of vehicle resources, ensuring that the resources of each station can be accurately matched according to real-time demand, avoiding the inefficiency and mismatch caused by fixed resource allocation in traditional methods, and improving the overall operating efficiency of the public transportation system.

[0022] The optimization method proposed in this paper considers the impact of fleet configuration adjustments, passenger transfers, and vehicle reallocation on modular bus operations. The resulting scheduling solution can reduce bus company operating costs, reduce passenger travel costs, improve bus system efficiency, and reduce passenger transfer wait times. Furthermore, this invention improves the service level of the bus system, provides strong support for future intelligent bus scheduling, and promotes the sustainable development and digital transformation of the bus system. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0024] Specific implementation method 1: This implementation method is a modular bus dispatch optimization method for bus corridors. The specific process is as follows:

[0025] Step 1: Collect basic information of bus stops, configure modular vehicles (1 vehicle), configure modular bus schedules, and collect passenger travel request data;

[0026] Step 2: Define optimization variables; the specific process is:

[0027] Defining 0-1 variables Represents a modular vehicle With segment On the flights If the relationship between modular vehicles Participate in the execution shift ,but ,otherwise ;

[0028] Defining 0-1 variables , if the first flights In the section Internal slave site Drive to the station ,but , otherwise it is equal to 0; where the site and All belong to the segment A collection of sites;

[0029] Defining 0-1 variables Indicates a passenger travel request With modular vehicles If the passenger's travel request Modular Vehicles Provide services, then ,otherwise ;

[0030] Defining continuous variables Indicates segment On the flights Arrival section Internal site moment;

[0031] Defining continuous variables Indicates segment On the flights In the section The average running speed within the unit is m / s.

[0032] Step 3: Determine the transfer strategy based on steps 1 and 2, and calculate the number of transfer passengers based on the transfer strategy;

[0033] Step 4: Split and combine the vehicles based on step 3 to complete the passenger transfer, and update the flight information based on the passenger transfer results;

[0034] Step 5: Establish a modular bus dispatch optimization model based on steps 1, 2, 3, and 4;

[0035] Step 6: Solve the modular bus scheduling optimization model and output the optimal scheduling plan .

[0036] Specific embodiment 2: This embodiment differs from specific embodiment 1 in that: in step 1, basic information of bus stops is collected, modular vehicles (1 vehicle) are configured, modular bus schedules are configured, and passenger travel request data is collected; the specific process is as follows:

[0037] Step 1.1: Collect basic information about bus stops; the specific process is as follows:

[0038] The bus operation on the main road passenger flow corridor is divided into the upward direction and the downward direction, each direction includes bus stops;

[0039] The site set in the upstream direction is denoted as , the set of sites in the downstream direction is recorded as ;

[0040] All stations on the passenger flow corridor are recorded as a set ;

[0041] Set a passenger flow threshold (there is one passenger flow threshold for each hour of the 24 hours a day) and designate all stations with passenger flow exceeding the threshold as key stations.

[0042] Key sites are used for modular bus fleets to be split and combined;

[0043] Store the key sites on the passenger flow corridor into the key site set , ;

[0044] in, Represents a collection of key sites The first key site, Represents a collection of key sites The second key site, Represents a collection of key sites Middle Key sites, represents a collection of key sites;

[0045] Taking key stations as boundaries, adjacent key stations are divided into 1 section, and the passenger flow corridor is divided into sections;

[0046] make It represents the set of segments divided in the upstream direction with key sites as the boundary;

[0047] make It represents the set of segments divided in the downstream direction with key sites as the boundary;

[0048] in, and They represent the maximum number of sections after the passenger flow corridor is divided in the upward and downward directions with the key station as the boundary;

[0049] All sections on the passenger flow corridor are recorded as a set ;

[0050] Step 1.2. Configure a modular vehicle (1 vehicle); the specific process is as follows:

[0051] make Indicates operating hours The set of all modular vehicle numbers participating in the dispatch;

[0052] in, The total number of modular vehicles deployed on the passenger corridor, with the number starting from 1 and increasing one by one;

[0053] To ensure smooth operation, the operation starts at At key sites storage modular vehicles;

[0054] Step 1.3. Configure modular bus schedules; the specific process is as follows:

[0055] Each shift consists of one or more modular vehicles. Each section includes shifts with different departure times. Each shift is a process of traveling from one key station to the adjacent key station and picking up and dropping off passengers along the way to complete the operation task.

[0056] Order set Indicates operating hours All services on the inner bus corridor;

[0057] in,

[0058] represents the set of all shifts in segment 1 based on the segment division in step 1.1;

[0059] represents the set of all shifts in segment 2 based on the segment division in step 1.1;

[0060] Indicates the segment division based on step 1.1, segment All shifts within the meeting;

[0061] Indicates the key site segmentation based on step 1.1, segment All shifts within the meeting;

[0062] gather Further expressed as ;

[0063] in, Indicates segment The first flight on Indicates segment On the second flight, Indicates segment On the shifts, Indicates segment On the shifts; Indicates segment Total number of shifts, section ;

[0064] Step 1.4. Collect passenger travel request data; the specific process is as follows:

[0065] Collect the operating hours of the past 30 working days Passenger travel request collection on the inner passenger flow corridor ;

[0066] A passenger travel request The information included is: boarding station , Get-off point , Earliest expected service start time , Latest expected service start time and the number of passengers to be served ;

[0067] ;

[0068] To facilitate the determination of transfer strategies in step 3, passenger travel requests are divided into three categories;

[0069] Traverse the passenger travel request set Each request , judge the request Boarding station Section and drop-off points Section ;

[0070] If requested Boarding station Section and drop-off points Section In the same section, that is , then request Classified as intra-segment direct passengers , no need to transfer;

[0071] If requested Boarding station Section and drop-off points Section In adjacent segments, that is , then request Classified as a set of passengers transferring across sections , a transfer is required;

[0072] If requested Boarding station Section and drop-off points Section Not in the same segment and not in adjacent segments, that is , then request Classified as cross-segment Transfer passengers collection , Greater than 1 and a positive integer;

[0073] Until all requests are classified.

[0074] Other steps and parameters are the same as those in the first embodiment.

[0075] Specific embodiment 3: This embodiment differs from specific embodiment 1 or 2 in that: in step 3, the transfer strategy is determined based on steps 1 and 2, and the number of transfer passengers is calculated based on the transfer strategy; the specific process is:

[0076] Step 3.1

[0077] Segment Key sites and The segment bounded by the key site and The sections The starting and ending sites of Calculation section On the flights At the end site Number of passengers waiting to transfer :

[0078]

[0079] Where, Indicates the shift At the end site Gathering of passengers waiting to transfer across sections;

[0080] Indicates the shift At the end site Waiting for transfer across sections The transfer passenger set, Greater than 1 and a positive integer;

[0081] For collection A request in For collection A request in

[0082] Express a request The number of passengers to be served included in , the unit is person;

[0083] Express a request The number of passengers to be served included in , the unit is person;

[0084] Indicates segment On the flights At the end site The number of passengers waiting to transfer across sections at one time, in persons;

[0085] Indicates segment On the flights At the end site Waiting for transfer across sections The number of passengers transferring at this time, in persons;

[0086] Step 3.2: Use 0-1 variables Judgment section On the flights The transfer strategy adopted;

[0087] If the segment On the flights If the full in-car transfer strategy is adopted, ;

[0088] If the segment On the flights If the strategy of transferring within the vehicle as the main method and transferring after getting off the vehicle as the auxiliary method is adopted, ;

[0089] According to the formula Calculated variables :

[0090]

[0091] Where, Represents the unit modular vehicle capacity, in persons / vehicle;

[0092] represents the ceiling function, which is used to calculate the minimum number of modular vehicles required to carry passengers, in units of vehicles;

[0093] Indicates operating hours The set of all modular vehicle numbers participating in the dispatch, For collection The number is modular vehicles;

[0094] A 0-1 variable representing a modular vehicle With segment On the flights If the relationship between modular vehicles Participate in the execution shift ,but ,otherwise ;

[0095] Indicates the shift The number of vehicles called, in units of vehicles;

[0096] Step 3.3

[0097] when When, according to the formula and Calculation section On the flights At the end site Number of passengers getting off and transferring and the number of passengers transferring within the vehicle :

[0098]

[0099]

[0100] when When, according to the formula and Calculation section On the flights At the end site Number of passengers getting off and transferring and the number of passengers transferring within the vehicle :

[0101]

[0102]

[0103] Where, represents the remainder function, which is used to calculate the number of passengers that cannot make a single modular vehicle reach a full load state, in units of people;

[0104] By passenger travel request collection Identify and determine shifts Passenger transfer numbers within the vehicle and flights Passengers getting off and transferring to other buses are numbered and collected ;

[0105] According to the passenger travel request classification method in step 1.4, the flights are formed The number set of passengers who transfer within the train and transfer across sections and flights Transfer within the train and cross sections The number set of the transfer passengers ; Greater than 1 and a positive integer;

[0106] According to the passenger travel request classification method in step 1.4., form the flight The number set of passengers who get off and transfer across sections and flights Get off and transfer across sections The number set of the transfer passengers ; Greater than 1 and a positive integer.

[0107] Step 3.1, step 3.2, and step 3.3 are performed in sequence.

[0108] Other steps and parameters are the same as those in the first or second embodiment.

[0109] Specific embodiment 4: This embodiment differs from any one of specific embodiments 1 to 3 in that: in step 4, the vehicles are split and combined based on step 3 to complete the passenger transfer, and the flight information is updated based on the passenger transfer result;

[0110] The specific process is:

[0111] Step 4.1

[0112] when or When transferring within the car and the passengers are transferring across sections Calculate shifts The convoy is at the end station The number of vehicles that need to be split is as follows: As shown:

[0113] when or When transferring within the car and crossing sections Transfer passengers , calculate shifts The convoy is at the end station The number of vehicles that need to be split is as follows: As shown:

[0114]

[0115]

[0116] Where,

[0117] Indicates that the passengers are transferring within the vehicle and are transferring across sections. , flight The convoy is at the end station The number of vehicles that need to be split, in units of vehicles;

[0118] Indicates that the vehicle is used for transfer and it is a cross-section Transfer passengers , flight The convoy is at the end station The number of vehicles that need to be split, in units of vehicles;

[0119] Represents the unit modular vehicle capacity, in persons / vehicle;

[0120] For collection A request in For collection A request in

[0121] Express a request The number of passengers to be served included in , in persons;

[0122] Express a request The number of passengers to be served included in , in persons;

[0123] and Representing shifts At the end site The number of passengers transferring across sections and waiting for transfers within the vehicle The number of passengers transferring at this time, in persons;

[0124] represents the ceiling function, which is used to calculate the minimum number of modular vehicles required to carry passengers, in units of vehicles;

[0125] For passengers transferring within the train and transferring across sections Transfer within the train and cross sections Transfer passengers The transfer process is divided into the following four situations:

[0126] (1) If and , passengers transferring within the vehicle and By ending at the site Split shifts The fleet was transferred to the new route and ; New flights and It is in the section The additional flights are based on the existing flights. Indicates segment The total number of classes currently available, in units of classes; The fleet is split up to form new shifts and The number of vehicles is Vehicle and vehicles; among them, Indicates segment On the shifts; Indicates segment On the shifts;

[0127] (2) If and , passengers transferring within the vehicle By ending at the site Split shifts The fleet transferred to the new route ; New flights It is in the section The additional flights are based on the existing flights. Indicates segment Total number of classes currently attended; The fleet was split into new shifts The number of vehicles is vehicles;

[0128] (3) If and , passengers transferring within the vehicle By ending at the site Split shifts The fleet transferred to the new route ; New flights It is in the section The additional flights are based on the existing flights. Indicates segment Total number of classes currently attended; The fleet is split up to form new shifts The number of vehicles is vehicles;

[0129] (4) If and , for passengers who do not have to transfer within the vehicle, there is no need to create a new bus for service transfer;

[0130] Follow step 4.2.

[0131] Step 4.2: Passengers gather at All passengers in the terminal are at the terminal Get off the bus and transfer to another bus, then go to step 4.3;

[0132] Step 4.3: or Update the number of passengers transferring within the vehicle New flights and If the information is correct, go to step 4.4. The specific process is as follows:

[0133] (1) If and , calculate the number of split vehicles according to step 4.1 and ;

[0134] From the composition shift Select the vehicle from the vehicle collection in ascending order of number. The vehicles are split and combined into new shifts ;

[0135] From the composition of the shift Select the vehicle from the vehicle collection in ascending order of number. The vehicles are split and combined into new shifts ;

[0136] According to the set of transfer passenger numbers obtained in step 3.3, the numbers of passengers who transfer within the car and are transferring across sections are Assign to new shift The set of travel passenger numbers , transfer within the car and cross sections Number of the passenger transferring Assign to new shift The set of travel passenger numbers ;

[0137] ; ;

[0138] Set up new shifts Departure time The value of ;

[0139] Set up new shifts Departure time The value of ;

[0140] in, Indicates segment On the flights Arrival section End site moment; Indicates segment The end site of Indicates segment The total number of classes currently attended, in units of classes;

[0141] (2) If and , calculate the number of split vehicles according to step 4.1 ;

[0142] From the composition of the shift Select the vehicle from the vehicle collection in ascending order of number. The vehicles are split and combined into new shifts ;

[0143] According to the transfer passenger number set obtained in step 3.3, transfer within the car and belong to cross-segment Number of the passenger transferring Assign to new shift The set of travel passenger numbers ; ;

[0144] Set up new shifts Departure time The value of ;

[0145] in, Indicates segment On the flights Arrival section End site moment; Indicates segment The end site of Indicates segment The total number of classes currently attended, in units of classes;

[0146] (3) If and , calculate the number of split vehicles according to step 4.1 ;

[0147] From the composition of the shift Select the vehicle from the vehicle collection in ascending order of number. The vehicles are split and combined into new shifts ;

[0148] According to the set of transfer passenger numbers obtained in step 3.3, the numbers of passengers who transfer within the car and are transferring across sections are Assign to new shift The set of travel passenger numbers ; ;

[0149] Set up new shifts Departure time The value of ;

[0150] in, Indicates segment On the flights Arrival section End site moment; Indicates segment The end site, Indicates segment The total number of classes currently attended, in units of classes;

[0151] (4) If and , no new shift is generated, no need to update the shift information;

[0152] Step 4.4: Update the number of passengers getting off and transferring Shift information; the specific process is:

[0153] (1) If , , then record the segment On the flights Arrival section End site Moment , traverse the segment Take existing flights , record shifts Departure time , find satisfaction and satisfy the capacity constraint Among all eligible shifts, select Smallest shift ; According to the transfer passenger number set obtained in step 3.3, the flight The number set of passengers who get off and transfer across sections Add to shift The set of travel passenger numbers middle, ;

[0154] in, Indicates segment On the shifts; ;

[0155] Indicates the segment division based on step 1.1, segment All shifts within the meeting;

[0156] (2) If , , then record the segment On the flights Arrival section End site Moment , traverse the segment Take existing flights , record shifts Departure time , find satisfaction and satisfy the capacity constraint Among all eligible shifts, select Smallest shift ; According to the transfer passenger number set obtained in step 3.3, the flight Get off and transfer across sections The number set of the transfer passengers Add to shift The set of travel passenger numbers middle, .

[0157] The other steps and parameters are the same as those in the first to third embodiments.

[0158] Specific embodiment 5: This embodiment differs from any one of specific embodiments 1 to 4 in that: in step 5, a modular bus scheduling optimization model is established based on steps 1, 2, 3, and 4;

[0159] The specific process is:

[0160] Step 5.1: According to the formula Construct the objective function:

[0161]

[0162] in, represents the modular bus operating cost, in yuan; It represents the passenger travel cost, in yuan; It represents the total cost in yuan;

[0163] Step 5.2: According to the formula ~ Calculate the operating cost of modular buses; the specific process is:

[0164]

[0165]

[0166]

[0167] Where,

[0168] represents the fixed cost of modular bus, in yuan; represents the energy consumption cost of modular bus, in yuan;

[0169] represents the fixed cost of each modular bus, in yuan / vehicle;

[0170] is a binary variable, if the modular vehicle Participate in the operation, , otherwise it is equal to 0;

[0171] It represents the unit average operating cost, in yuan / km;

[0172] Indicates a site With site The distance between them, in km;

[0173] and Representing segments The starting and ending sites;

[0174] Step 5.3: According to the formula ~ Calculate the passenger travel cost; the specific process is:

[0175]

[0176]

[0177]

[0178]

[0179]

[0180] Where, It represents the cost of passengers in the car, in yuan; It represents the waiting cost of passengers, in yuan; represents the penalty cost for passengers getting off and transferring, in yuan;

[0181] Indicates segment On the flights Arrival pick-up request Get-off point moment;

[0182] Indicates segment On the flights Arrival pick-up request Pickup point moment;

[0183] Indicates segment On the flights Arrival pick-up request Get-off point moment;

[0184] Indicates segment On the flights Arrival pick-up request Get-off point moment;

[0185] Express a request The earliest expected time to start service;

[0186] function Used to calculate passenger travel requests Waiting service time, in min;

[0187] For a passenger trip request, , Assembling passenger travel requests;

[0188] Indicates segment On the flights At the end site The number of passengers getting off and transferring, in persons;

[0189] Passenger travel request collection Divided into three categories: 、 、 ;

[0190] Indicates the gathering of direct passengers within the section; Indicates a collection of passengers transferring across sections; Indicates cross-segment Gathering of transfer passengers;

[0191] It represents the cost per unit time of the passenger in the car, in yuan / min; It represents the waiting cost per unit time for passengers, in yuan / min; It represents the penalty cost of passengers getting off the bus and transferring, in yuan / person;

[0192] 5.4. Set constraints; the specific process is as follows:

[0193] Constraints on modular bus fleets not to exceed the maximum vehicle formation length :

[0194]

[0195] Constraint Section On the flights capacity to ensure that the demand carried by the shift does not exceed the total carrying capacity of the actual vehicle:

[0196]

[0197] Where, Indicates segment On the flights Arrival at the site The number of passengers still in the car at the time, in persons;

[0198] Constraining key sites The number of vehicles stored at the end of the operation is the same as at the beginning of the operation:

[0199]

[0200] Where,

[0201] Indicates that before the start of the operating period, at key sites The number of modular vehicles stored, in units of vehicles;

[0202] Indicates that after the operation period, at key sites The number of modular vehicles stored, in units of vehicles;

[0203] Constraining the speed of modular buses Do not exceed the safety range:

[0204]

[0205] Where, and They represent the minimum operating speed and maximum operating speed of the modular bus, respectively, in m / s;

[0206] Constraining modular buses at the end of their operating hours Before reaching key sites:

[0207]

[0208] Where, Indicates segment On the flights Arrival section End site moment;

[0209] Indicates the end time of the operating period;

[0210] Constraining buses to start service within the time window expected by passengers Arrive at the passenger boarding point within:

[0211]

[0212] Where, Express a request The earliest expected time to start service; Indicates segment On the flights Arrival Request Pickup point moment; Express a request The latest expected service start time;

[0213] Restrained Vehicle Shifts performed and shifts There is no time conflict between:

[0214]

[0215] Where,

[0216] Indicates segment On the flights Arrival section End site moment;

[0217] Indicates segment On the flights Arrival section End site moment;

[0218] Segment , , , ;

[0219] Is a binary variable, if the modular vehicle Participate in the execution shift ,but ,otherwise .

[0220] Other steps and parameters are the same as those in Specific Embodiments 1 to 4-1.

[0221] Specific embodiment 6: This embodiment differs from any one of the specific embodiments 1 to 5 in that: in step 6, the modular bus scheduling optimization model is solved to output the optimal scheduling plan ;

[0222] The specific process is:

[0223] Adopting the adaptive large neighborhood search algorithm to solve the model, the initial solution is optimized and iterated to dynamically optimize the vehicle number sequence, service request sequence and departure time sequence of the operating shift. This algorithm needs to set the maximum number of iterations. , annealing temperature , cooling rate and reaction coefficient and other parameters.

[0224] Step 6.1. Construct the initial solution:

[0225] Define the first level coding operation shift sequence , ;

[0226] ;

[0227] ;

[0228] ;

[0229] in,

[0230] Indicates the vehicle number sequence of all shifts on section 1. Indicates the composition segment The vehicle number sequence for all shifts, Indicates the composition segment The vehicle number sequence for all shifts;

[0231] Indicates the first shift on segment 1 Vehicle number, Indicates the first shift on segment 1 Vehicle number; Indicates the first flights Vehicle number;

[0232] Indicates the composition segment The first flight Vehicle number; Indicates the composition segment On the flights Vehicle number; Indicates the composition segment On the flights Vehicle number;

[0233] Indicates the composition segment The first flight Vehicle number; Indicates the composition segment On the flights Vehicle number; Indicates the composition segment On the flights Vehicle number;

[0234] Defines the second layer coding service request sequence ;

[0235] ;

[0236] ;

[0237] ;

[0238] in,

[0239] represents the set of travel requests for all services on segment 1, Indicates segment The set of travel requests for all services on the flight, Indicates segment The set sequence of travel requests for all services on the flight;

[0240] Indicates the first shift on segment 1 The set of travel requests for the service, Indicates the first flights The set of travel requests for the service; Indicates the first flights The set of travel requests for the service;

[0241] Indicates segment The first flight The set of travel requests for the service; Indicates segment On the flights The set of travel requests for the service; Indicates segment On the flights The set of travel requests for the service;

[0242] Indicates segment The first flight The set of travel requests for the service; Indicates segment On the flights The set of travel requests for the service; Indicates segment On the flights The set of travel requests for the service;

[0243] Define the third-level coded departure time sequence ;

[0244] ;

[0245] ;

[0246]

[0247] in,

[0248] represents the departure time sequence of all trains on section 1. Indicates segment The departure time sequence of all trains, Indicates segment The departure time sequence of all trains;

[0249] Indicates the first shift on segment 1 The departure time, Indicates the first flights departure time; Indicates the first flights departure time;

[0250] Indicates segment The first flight departure time; Indicates segment On the flights departure time; Indicates segment On the flights departure time;

[0251] Indicates segment The first flight departure time; Indicates segment On the flights departure time; Indicates segment On the flights departure time;

[0252] The specific process is:

[0253] Step 6.1.1: Based on passenger travel request , combined with each request Pickup point and drop-off points The respective sections and , calculate the passenger flow demand in each section, and use the formula Calculations are stored in sections Starting site Number of modular vehicles ; expressed as:

[0254]

[0255] Where,

[0256] Indicates the time when the operation starts , stored in the segment Starting site The number of modular vehicles, in units;

[0257] Indicates segment The passenger flow demand on the platform is in units of people;

[0258] From the operating period The set of all modular vehicle numbers participating in the dispatch In, randomly selected Vehicles assigned to the section Starting site , and add it to the site before operation starts Stored vehicle number collection middle;

[0259] During this process, ensure that each vehicle can only be assigned once;

[0260] Step 6.1.2: When the maximum shift group length constraint is met In this case, traverse the storage generated in step 6.1.1. at the starting site Vehicle number collection , randomly select 1 to Vehicles are combined into shifts Vehicle number collection , until each vehicle is assigned to a shift;

[0261] For each request , if satisfied And the flight Satisfy capacity constraints Condition, then the request Assigned to shift Service request collection Until each request finds the corresponding boarding schedule;

[0262] Meeting the speed constraint and service request time window constraints Under the condition of random determination of shifts Departure time , until the departure time of each shift is determined;

[0263] Express a request Pickup point The section where it is located;

[0264] To meet the needs of transfer passengers, the generated set of vehicle numbers, service requests, and departure times will be updated in step 6.1.3.

[0265] Step 6.1.3: According to the formula in step 3.1 Calculate shifts At the end site Number of transfer passengers

[0266] if , according to step 3.2 shift It is necessary to determine the transfer strategy, and then split and combine the vehicles according to step 4 to complete the passenger transfer, and update the vehicle number set based on the passenger transfer results. , service request collection and departure time Otherwise, skip the shift , continue to determine the next flight; until the operating period Gathering at the inner bus corridor All shifts within the company have been inspected;

[0267] Step 6.1.4: Combine the updated vehicle number set of the shift in step 6.1.3 , updated shift service request collection and updated departure times , find the one with the largest departure time in the existing set of flights , determine the shift Arrival at the end station Moment ; judge at the moment Key Sites Number of modular vehicles stored ,if , no reallocation is required; if , for key sites Redistribute to key sites satisfy ;

[0268] Repeat step 6.1.4 until all key sites meet the ;

[0269] Among them, key sites The redistribution process is as follows:

[0270] 1) Traverse the key site collection For each key site, find the Key sites of conditions , and at the site Stored vehicle number collection Random selection Vehicles, reallocated to meet Key sites of conditions , and include key sites Segment Generate a new shift based on an existing shift , determine the composition of new shifts Vehicle number collection , new flights Departure time for , service passenger request set is empty;

[0271] 2) Update key sites after redistribution and Stored vehicle number collection 、 and number of stored vehicles 、 ;

[0272] Judge at the moment Key Sites Number of modular vehicles stored ,if , no reallocation is required; if , then re-execute 1) and 2) until the key site satisfy ;

[0273] Indicates the start time of operation At key sites the number of modular vehicles stored;

[0274] Indicates the start time of operation At key sites the number of modular vehicles stored;

[0275] Step 6.1.5, Step 6.1.4 updated the vehicle number set of the shift , updated shift service request collection and updated departure times Together they form the initial solution ;

[0276] Step 6.2: Design the destruction operator and repair operator. The specific process is as follows:

[0277] Step 6.2.1. Design five damage operators Expand the neighborhood of candidate solutions, including:

[0278] (1) Random destruction operator ; The specific process is:

[0279] Randomly select 10% of the total demand from the current solution Remove it and get the solution after destruction And add the deleted request to the list of pending service requests middle;

[0280] The total demand is collected during the past 30 working days. Passenger travel request collection on the inner passenger flow corridor ;

[0281] (2) Worst damage operator ; The specific process is:

[0282] Defining Insertion Cost ;

[0283] in, Indicates the current solution travel costs, Indicates that from the current solution Remove travel request The subsequent travel costs;

[0284] Sort by insertion cost in descending order, select the top 10% of the travel requests from the current solution Remove it and get the solution after destruction And add the deleted request to the list of pending service requests middle;

[0285] (3) Correlation destruction operator ; The specific process is:

[0286] Randomly select a travel request , according to the formula Find and Request Most relevant travel requests , remove these two requests from the current solution Repeat the above operation until the number of removal requests reaches 10% of the total demand, and then get the solution after destruction. And add the deleted request to the list of pending service requests middle;

[0287] The total demand is collected during the past 30 working days. Passenger travel request collection on the inner passenger flow corridor ;

[0288]

[0289] Where, Express a request and The correlation between the request and The correlation between It is obtained based on time, request load and distance (items 1 to 3);

[0290] and Represents the request and Expected earliest service start time;

[0291] and Represents the request and Expected latest service start time;

[0292] and Represents the request and The number of passengers included in , in persons;

[0293] and Respectively represent the distances between the two requested boarding stations and the reference station 1, in km;

[0294] and Respectively represent the distances between the two requested alighting stops and the benchmark stop 1, in km.

[0295] Indicates parameters, each item uses parameters Perform weighting;

[0296] (4) Modular vehicle destruction operator ; The specific process is:

[0297] Randomly select 10% of the total number of modular vehicles and select At the same time, due to the change of the capacity of the class, it is necessary to randomly select the travel request within the class and select the one from the current solution. Remove until the capacity constraint is met Then stop; finally, get the solution after destruction And add the deleted request to the list of pending service requests middle;

[0298] (5) Bus schedule disruption operator ; The specific process is:

[0299] Sort by passenger load factor in descending order, remove the last 10% of the flights, and get the solution after the destruction Add the travel requests served by the shift to the list of requests to be served middle;

[0300] Step 6.2.2: Solution after destruction and a list of pending service requests , two repair operators are designed Repairing a corrupted solution Get a new solution , specifically including:

[0301] (1) Solution after destruction and a list of pending service requests , design random repair operator Repairing a corrupted solution Get a new solution , specifically including:

[0302] Traverse the list of requests to be serviced Each travel request , according to step 1.4. Classification, randomly inserted into the Update the operating shift sequence , the sequence of travel requests served by the flight and departure time sequence ;

[0303] Until the list of pending service requests All travel requests are inserted into the new solution. ;

[0304] (2) Solution after destruction and a list of pending service requests , design greedy repair operator Repairing a corrupted solution Get a new solution , specifically including:

[0305] Traverse the list of requests to be serviced Each travel request , according to step 1.4. Classification, randomly inserted into the middle;

[0306] Calculate inserted travel requests of Total cost after and the solution after destruction Total cost The difference between the two values ​​is inserted into the travel request corresponding to the minimum difference value. Insert into Update the operating shift sequence , the sequence of travel requests served by the flight and departure time sequence ;

[0307] Until the list of pending service requests All travel requests are inserted into the new solution. ;

[0308] Step 6.3: Generate operator pairs and initialize operator pair weights. The specific process is as follows:

[0309] For the damage operator designed in step 6.2 and repair operator Combine two by two to generate operator pairs ; Initially, each operator pair The weights are all 1 and the scores are all 0;

[0310] Step 6.4: Solve the modular bus scheduling optimization model based on steps 6.1, 6.2, and 6.3, and output the optimal scheduling plan. ;

[0311] The specific process is:

[0312] 6.4.1, let the number of iterations ;

[0313] 6.4.2. Select destruction and repair operators and generate new solutions;

[0314] 6.4.3. Update the current solution and the optimal solution;

[0315] 6.4.4. Update the score of the operator pair;

[0316] 6.4.5. Update operator pair weights;

[0317] 6.4.6, Let the number of iterations , the updated operator score and the updated operator pair weights Substitute into step 6.4.2 and repeat steps 6.4.2 to 6.4.6 until the maximum number of iterations is reached. Output the optimal scheduling plan .

[0318] This includes the set of vehicle numbers, the set of service requests, and the departure time for each operating shift in the scheduling plan.

[0319] Other steps and parameters are the same as those in Specific Implementations 1 to 5-1.

[0320] Specific embodiment seven: This embodiment differs from any one of specific embodiments one to six in that: in step 6.4.2, the destruction and repair operators are selected and a new solution is generated;

[0321] The specific process is:

[0322] Step 6.4.2.1. Select the destruction and repair operators: Based on the roulette strategy, randomly select the operator pair according to the normalized weight of the operator. ; The specific process is:

[0323] First, according to the formula The operator pair Weight standardization:

[0324]

[0325] Where, Represents operator pairs The weight of

[0326] represents the sum of all operator pairs’ weights;

[0327] Represents an operator pair The probability of being selected satisfies ;

[0328] Among them, setting parameters To balance the relationship between solution time and timeliness of weight update.

[0329] Then, according to the formula Construct a cumulative probability interval for each operator pair (each operator pair corresponds to 1 cumulative probability interval, for example ) (Cumulative probability interval range ):

[0330]

[0331] In the formula, the initial cumulative probability is 0, Represents the cutoff operator pair The cumulative probability of

[0332] Then, generate a uniformly distributed random number , and then according to the random number The cumulative probability interval falls into, select the corresponding operator pair ;

[0333] Step 6.4.2.2: Generate a new solution. The specific process is as follows:

[0334] Operator pairs selected according to 6.4.2.1 , determine the selected destruction operator and repair operators , according to the destruction process and repair process in step 6.2 (select one of the five and one of the two) to solve the current solution. Operate and get new solutions .

[0335] The other steps and parameters are the same as those in the first to sixth embodiments.

[0336] Specific embodiment eight: This embodiment differs from any one of specific embodiments one to seven in that the current solution and the optimal solution are updated in step 6.4.3. The specific process is as follows:

[0337] definition Represent the current solution, new solution, and optimal solution respectively (the optimal solution is the comparison of solutions between iterations, the current solution is the solution obtained in step 6.4.3 of the previous iteration, and the new solution is the solution obtained in step 6.4.2.2 of this iteration);

[0338] like , then the optimal solution The value of is replaced by the new solution The value of

[0339] like , then the current solution The value of is replaced by the new solution The value of

[0340] like , the simulated annealing criterion is used to decide whether to accept the new solution; the specific process is:

[0341] Generate random numbers ,like , then the current solution The value of is replaced by the new solution Otherwise, the current solution The value of remains unchanged and no new solution is accepted ;

[0342] According to the formula Calculating simulated annealing probability :

[0343]

[0344] in, represents the annealing temperature; New interpretation The objective function value of Represents the optimal solution The objective function value of Indicates the current solution The objective function value of .

[0345] Other steps and parameters are the same as those in Specific Embodiments 1 to 7-1.

[0346] Specific embodiment 9: This embodiment differs from any one of specific embodiments 1 to 8 in that the scores of the operator pairs are updated in step 6.4.4. The specific process is as follows:

[0347] Design operator pair scoring Update rules:

[0348] like , then the operator pair score increases ;

[0349] like , then the operator pair score increases ;

[0350] like , if accepted by the simulated annealing criterion, the operator pair score increases ; If it is not accepted by the simulated annealing criterion, the operator pair score remains unchanged.

[0351] The other steps and parameters are the same as those in the specific implementation modes 1 to 8-1.

[0352] Specific embodiment 10: This embodiment differs from any one of specific embodiments 1 to 9 in that: in step 6.4.5, the weights of the operator pairs are updated; the specific process is as follows:

[0353] definition Represents operator pairs In the The weight of the iteration, represents the reaction coefficient, Represents an operator pair The score, Represents an operator pair Number of successful applications;

[0354] According to the formula Update weights:

[0355] .

[0356] The other steps and parameters are the same as those in the specific implementation modes 1 to 9-1.

[0357] The present invention may have many other embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art may make various corresponding changes and modifications based on the present invention, but these corresponding changes and modifications should all fall within the scope of protection of the claims attached to the present invention.

Claims

1. A modular bus dispatch optimization method for bus corridors, characterized by: The specific process of the method is: Step 1: Collect basic information of bus stops, configure modular vehicles, configure modular bus schedules, and collect passenger travel request data; Step 2: Define optimization variables; the specific process is: Define a 0-1 variable x s,k,m Denotes the modular vehicle m and the kth shift p on segment s s,k If modular vehicle m participates in the execution of shift p s,k , then x s,k,m =1, otherwise x s,k,m =0; Define a 0-1 variable y i,j,s,k , if the kth shift p on segment s s,k Travel from station i to station j in segment s, then y i,j,s,k =1, otherwise equal to 0; where sites i and j both belong to the site set of segment s; Define a 0-1 variable z m,r represents the relationship between a passenger travel request r and a modular vehicle m. If a passenger travel request r is served by a modular vehicle m, then z m,r =1, otherwise z m,r =0; Defining continuous variables represents the kth shift p on segment s s,k The time of arrival at station i in segment s; Define the continuous variable v s,k represents the kth shift p on segment s s,k The average running speed in section s, in m / s; Step 3: Determine the transfer strategy based on steps 1 and 2, and calculate the number of transfer passengers based on the transfer strategy; Step 4: Based on step 3, the vehicles are split and combined to complete the passenger transfer, and the flight information is updated based on the passenger transfer results; Step 5: Establish a modular bus dispatch optimization model based on steps 1, 2, 3, and 4; Step 6: Solve the modular bus scheduling optimization model and output the optimal scheduling solution sol * ; In step 1, basic information of bus stops is collected, modular vehicles are configured, modular bus schedules are configured, and passenger travel request data is collected. The specific process is as follows: Step 1.1: Collect basic information about bus stops; the specific process is as follows: The bus operations on the main road passenger flow corridor are divided into the up direction and the down direction, each direction contains N bus stops; The site set in the uplink direction is denoted as N up ={1,2,...,N}, where the set of sites in the downlink direction is N dn ={N+1,N+2,...,2N}; All stations on the passenger flow corridor are recorded as a set N′={1,2,...,N,N+1,...,2N}; Set a passenger flow threshold and designate all stations with passenger flow exceeding the threshold as key stations. Key sites are used for modular bus fleets to be split and combined; Store the key sites on the passenger flow corridor into the key site set Among them, N1 represents the key site set N KEY The first key site in N2 represents the key site set N KEY The second key site, Represents the key site set N KEY Middle Key sites, N KEY represents a collection of key sites; Taking key stations as boundaries, adjacent key stations are divided into 1 section, and the passenger flow corridor is divided into sections; make It represents the set of segments divided in the upstream direction with key sites as the boundary; make It represents the set of segments divided in the downstream direction with key sites as the boundary; in, S up and S dn They represent the maximum number of sections after the passenger flow corridor is divided in the upward and downward directions with the key station as the boundary; All sections on the passenger flow corridor are recorded as a set Step 1.

2. Configure the modular vehicle; the specific process is: make represents the set of all modular vehicle numbers involved in scheduling during the operation period T; Where M is the total number of modular vehicles deployed on the passenger corridor, and the numbering starts from 1 and increases one by one; Before the operation starts at time t0, at the key site u∈N KEY storage modular vehicles; Step 1.

3. Configure modular bus schedules; the specific process is as follows: Each shift consists of one or more modular vehicles. Each section includes shifts with different departure times. Each shift is a process of traveling from one key station to the adjacent key station and picking up and dropping off passengers along the way to complete the operation task. Order set Represents all bus trips on the bus corridor during the operating period T; in, P1 represents the set of all shifts in section 1; P2 represents the set of all shifts in section 2; P s represents the set of all shifts in segment s; Indicates segment S up +S dn All shifts within the meeting; Set P s Further expressed as Among them, p s,1 represents the first shift on segment s, p s,2 represents the second shift on segment s, p s,k represents the kth shift on segment s, Indicates the Kth s shifts; K s Indicates the total number of shifts in section s, section Step 1.

4. Collect passenger travel request data; the specific process is as follows: Collect the passenger travel request set R on the passenger flow corridor during the operating period T in the past 30 working days; A passenger travel request r contains the following information: boarding station o r , get-off point d r , Earliest expected service start time Latest expected service start time and the number of passengers to be served, q r ; r∈R； Traverse each request r in the passenger travel request set R and determine the boarding station o of request r r Section and the drop-off point r Section If you request r to board the bus at station o r Section and the drop-off point r Section In the same section, that is Then request r is classified as direct passenger R within the segment 1 , no need to transfer; If you request r to board the bus at station o r Section and the drop-off point r Section In adjacent segments, that is Then the request r is classified as the set of passengers transferring across sections R 2 , a transfer is required; If you request r to board the bus at station o r Section and the drop-off point r Section Not in the same segment and not in adjacent segments, that is Then the request r is classified as the set of passengers transferring across sections ξ times R 3 , the ξ is greater than 1 and is a positive integer; Until all requests are classified.

2. The modular bus dispatch optimization method for bus corridors according to claim 1 is characterized by: In step 3, the transfer strategy is determined based on steps 1 and 2, and the number of transfer passengers is calculated based on the transfer strategy. The specific process is as follows: Step 3.1 Segment s is based on key sites and The segment bounded by the key site and are the starting and ending stations of section s respectively; according to formula (1), the kth shift p on section s is calculated s,k At the end site Number of passengers waiting to transfer Where, Indicates shift p s,k At the end site Gathering of passengers waiting to transfer across sections; Indicates shift p s,k At the end site The set of inter-segment transfer passengers waiting for transfer with ξ times, where ξ is greater than 1 and is a positive integer; r′ is a set A request in , r″ is a set A request in q r ′ represents the number of passengers to be served contained in the request r′, The unit is a person; q r″ represents the number of passengers to be served contained in the request r″, The unit is a person; represents the kth shift p on segment s s,k At the end site The number of passengers waiting to transfer across sections at one time, in persons; represents the kth shift p on segment s s,k At the end site The number of inter-segment transfer passengers waiting to transfer, in persons; Step 3.2 Using 0-1 variable φ s,k Determine the kth shift p on segment s s,k The transfer strategy adopted; If the kth shift p on segment s s,k If the full in-car transfer strategy is adopted, then φ s,k =1; If the kth shift p on segment s s,k If the strategy of transferring within the vehicle as the main method and transferring after getting off the vehicle as the auxiliary method is adopted, then φ s,k =0; Calculate the variable φ according to formula (2) s,k : Where c represents the unit modular vehicle capacity, and the unit is person / vehicle; represents the ceiling function; Represents the set of all modular vehicle numbers participating in the scheduling within the operation period T, m is the set The modular vehicle numbered m; x s,k,m is a 0-1 variable representing the kth shift p of the modular vehicle m and the segment s s,k If modular vehicle m participates in the execution of shift p s,k , then x s,k,m =1, otherwise x s,k,m =0; Indicates shift p s,k The number of vehicles called, in units of vehicles; Step 3.3 When φ s,k = 1, calculate the kth shift p on section s according to equations (3) and (4): s,k At the end site Number of passengers getting off and transferring and the number of passengers transferring within the vehicle When φ s,k = 0, calculate the kth shift p on section s according to equations (5) and (6): s,k At the end site Number of passengers getting off and transferring and the number of passengers transferring within the vehicle Where mod represents the remainder function; Identify and determine the flight schedule p through the passenger travel request set R s,k Passenger transfer numbers within the vehicle and flight p s,k Passengers getting off and transferring to other buses are numbered and collected According to the passenger travel request classification method in step 1.4., the flight p is formed s,k The number set of passengers who transfer within the train and transfer across sections and flight p s,k The set of numbers of passengers who transfer within the car and transfer across sections ξ times The ξ is greater than 1 and is a positive integer; According to the passenger travel request classification method in step 1.4., the flight p is formed s,k The number set of passengers who get off and transfer across sections and flight p s,k The set of numbers of passengers who get off and transfer across sections ξ times The ξ is greater than 1 and is a positive integer.

3. The modular bus dispatch optimization method for bus corridors according to claim 2, characterized in that: In step 4, the vehicles are split and combined based on step 3 to complete the passenger transfer, and the flight information is updated based on the passenger transfer result; The specific process is: Step 4.1 When φ s,k =1 or φ s,k = 0, based on the transfer within the car and the cross-section transfer passengers Calculate shift p s,k The convoy is at the end station The number of vehicles that need to be split is shown in formula (7): When φ s,k =1 or φ s,k = 0, according to the in-car transfer and the cross-section transfer passengers Calculate shift p s,k The convoy is at the end station The number of vehicles that need to be split is shown in formula (8): Where, Indicates that the passengers are transferring within the vehicle and are transferring across sections. Flight p s,k The convoy is at the end station The number of vehicles that need to be split, in units of vehicles; Indicates that the purpose is to carry passengers who are transferring within the vehicle and are transferring across sections. Flight p s,k The convoy is at the end station The number of vehicles that need to be split, in units of vehicles; c represents the unit modular vehicle capacity, in persons / vehicle; For collection A request in For collection A request in Express a request The number of passengers to be served included in The unit is a person; Express a request The number of passengers to be served included in The unit is a person; and Represents shift p s,k At the end site The number of passengers waiting for intra-train transfers and the number of passengers transferring across sections ξ times, in units of persons; represents the ceiling function; For passengers transferring within the train and transferring across sections Passengers transferring within the train and transferring across sections The transfer process is divided into the following four situations: (1) If and Passengers transferring within the vehicle and By ending at the site Split shift p s,k The fleets were transferred to the new route p s+1,k′+1 and p s+1,k′+2 ; New flight p s+1,k′+1 and p s+1,k′+2 It is added on the basis of the existing shifts in section s+1, k′ represents the total number of existing shifts in section s+1, the unit is shift; shift p s,k The fleet is split into new shifts p s+1,k′+1 and p s+1,k′+2 The number of vehicles is Vehicle and vehicles; Among them, p s+1,k′+1 represents the k′+1th shift on segment s+1; p s+1,k′+2 represents the k′+2th shift on segment s+1; (2) If and Passengers transferring within the vehicle By ending at the site Split shift p s,k The fleet transfers to the new route p s+1,k′+1 ; New flight p s+1,k′+1 It is added on the basis of the existing shifts on section s+1, k′ represents the total number of existing shifts on section s+1; shift p s,k The fleet is split into new shifts p s+1,k′+1 The number of vehicles is vehicles; (3) If and Passengers transferring within the vehicle By ending at the site Split shift p s,k The fleet transfers to the new route p s+1,k′+1 ; New flight p s+1,k′+1 It is added on the basis of the existing shifts on section s+1, k′ represents the total number of existing shifts on section s+1; shift p s,k The fleet is split into new shifts p s+1,k′+1 The number of vehicles is vehicles; (4) If and For passengers who do not have to transfer within the vehicle, there is no need to create a new bus service transfer; Follow step 4.

2. Step 4.2, when φ s,k = 0, passengers gather All passengers in the terminal are at the terminal Get off the bus and transfer to another bus, then go to step 4.3; Step 4.3, when φ s,k =1 or φ s,k = 0, update the passengers transferring in the vehicle New flights p s+1,k′+1 and p s+1,k′+2 If the information is correct, go to step 4.

4. The specific process is as follows: (1) If and Calculate the number of vehicles to be split according to step 4.1 and From the composition shift p s,k Select the vehicle from the vehicle collection in ascending order of number. The vehicles are split and combined into new shifts p s+1,k′+1 ; From the composition shift p s,k Select the vehicle from the vehicle collection in ascending order of number. The vehicles are split and combined into new shifts p s+1,k′+2 ; According to the set of transfer passenger numbers obtained in step 3.3, the numbers of passengers who transfer within the car and are transferring across sections are Assign to new shift p s+1,k′+1 The set of passenger numbers R s+1,k′+1 , the numbers of passengers who transfer within the car and cross sections Assign to new shift p s+1,k′+2 The set of passenger numbers R s+1,k′+2 ; Set up new shift p s+1,k′+1 Departure time The value of Set up new shift p s+1,k′+2 Departure time The value of in, represents the kth shift p on segment s s,k Arrival at the end station of segment s moment; represents the end station of section s; k′ represents the total number of existing shifts in section s+1, in units of shifts; (2) If and Calculate the number of vehicles to be split according to step 4.1 From the composition shift p s,k Select the vehicle from the vehicle collection in ascending order of number. The vehicles are split and combined into new shifts p s+1,k′+1 ; According to the set of transfer passenger numbers obtained in step 3.3, the numbers of passengers who transfer within the car and are cross-segment transfers are Assign to new shift p s+1,k′+1 The set of passenger numbers R s+1,k′+1 ; Set up new shift p s+1,k′+1 Departure time The value of in, represents the kth shift p on segment s s,k Arrival at the end station of segment s moment; represents the end station of section s; k′ represents the total number of existing shifts in section s+1, in units of shifts; (3) If and Calculate the number of vehicles to be split according to step 4.1 From the composition shift p s,k Select the vehicle from the vehicle collection in ascending order of number. The vehicles are split and combined into new shifts p s+1,k′+1 ; According to the set of transfer passenger numbers obtained in step 3.3, the numbers of passengers who transfer within the car and are transferring across sections are Assign to new shift p s+1,k′+1 The set of passenger numbers R s+1,k′+1 ; Set up new shift p s+1,k′+1 Departure time The value of in, represents the kth shift p on segment s s,k Arrival at the end station of segment s moment; represents the end station of section s, k′ represents the total number of existing shifts in section s+1, in units of shifts; (4) If and No new shifts were generated, so there is no need to update the shift information; Step 4.4, when φ s,k = 0, update the passengers who get off and transfer Shift information; the specific process is: (1) If Then record the kth shift p on segment s s,k Arrival at the end station of segment s Moment Traverse the existing flights in segment s+1 Record shifts Departure time Finding satisfaction And the shift that meets the capacity constraint (19); among all the shifts that meet the conditions, select Smallest shift According to the set of transfer passenger numbers obtained in step 3.3, the flight number p s,k The number set of passengers who get off and transfer across sections Add to shift The set of travel passenger numbers middle, in, Indicates the first shifts; P s+1 represents the set of all shifts in segment s+1; Where, represents the kth shift p on segment s s,k The number of passengers still in the car when arriving at station i, in persons; (2) If Then record the kth shift p on segment s s,k Arrival at the end station of segment s Moment Traverse the existing flights in segment s+1 Record shifts Departure time Finding satisfaction And the shift that meets the capacity constraint (19); among all the shifts that meet the conditions, select Smallest shift According to the set of transfer passenger numbers obtained in step 3.3, the flight number p s,k The set of numbers of passengers who get off and transfer across sections ξ times Add to shift The set of travel passenger numbers middle, 4. The modular bus dispatch optimization method for bus corridors according to claim 3 is characterized by: In step 5, a modular bus scheduling optimization model is established based on steps 1, 2, 3 and 4; The specific process is: Step 5.1: Construct the objective function according to formula (9): minC=C1+C2(9) Among them, C1 represents the modular bus operating cost, in RMB; C2 represents the passenger travel cost, in RMB; C represents the total cost, in RMB; Step 5.2: Calculate the modular bus operating cost according to equations (10) to (12); the specific process is as follows: C1=C 1,1 +C 1,2 (10) Where, C 1,1 represents the fixed cost of modular bus, in yuan; C 1,2 represents the energy consumption cost of modular bus, in yuan; ω 1,1 represents the fixed cost of each modular bus, in yuan / vehicle; η m is a binary variable. If modular vehicle m is involved in the operation, then η m =1, otherwise equal to 0; ω 1,2 It represents the unit average operating cost, in yuan / km; d i,j Indicates the distance between site i and site j, in km; and Represent the starting site and ending site of segment s respectively; Step 5.3: Calculate the passenger travel cost according to equations (13) to (17); the specific process is as follows: C2=C 2,1 +C 2,2 +C 2,3 (13) Where, C 2,1 Indicates the cost of passengers on board, in yuan; C 2,2 represents the waiting cost of passengers, in yuan; C 2,3 represents the penalty cost for passengers getting off and transferring, in yuan; represents the kth shift p on segment s s,k Arrives at the drop-off point d for the picked-up request r r moment; represents the kth shift p on segment s s,k Arrives at the boarding station o of the pickup request r r moment; Indicates the kth r Shifts p s,k Arrives at the drop-off point d for the picked-up request r r moment; Indicates segment kth r flights Arrives at the drop-off point d for the picked-up request r r moment; represents the earliest expected service start time of request r; Function t W (r) is used to calculate the waiting service time of passenger trip request r, in minutes; r is a passenger travel request, r∈R, R is the set of passenger travel requests; represents the kth shift p on segment s s,k At the end site The number of passengers getting off and transferring, in persons; The passenger travel request set R is divided into three categories: R 1 、R 2 、R 3 ; R 1 Indicates the collection of direct passengers within the section; R 2 represents the set of passengers transferring across sections; R 3 represents the set of passengers transferring across sections ξ times; ω 2,1 The unit of passenger time in the vehicle is RMB / min; ω 2,2 The unit of waiting time for passengers is RMB / min; ω 2,3 It represents the penalty cost of passengers getting off the bus and transferring, in yuan / person; 5.

4. Set constraints; the specific process is as follows: Constraint modular bus fleet shall not exceed the maximum vehicle formation length l max : The kth shift p on the constraint segment s s,k capacity to ensure that the demand carried by the shift does not exceed the total carrying capacity of the actual vehicle: Where, represents the kth shift p on segment s s,k The number of passengers still in the car when arriving at station i, in persons; Constrained key site u∈N KEY The number of vehicles stored at the end of the operation is the same as at the beginning of the operation: Where, It represents the number of modular vehicles stored at the key site u before the start of the operation period, in units of vehicles; Indicates the number of modular vehicles stored at the key site u after the operation period ends, in units of vehicles; Constrain the driving speed v of the modular bus s,k Do not exceed the safety range: Where, v min and v max They represent the minimum operating speed and maximum operating speed of the modular bus, respectively, in m / s; Constraining modular bus at the end of the operating period t fin Before reaching key sites: Where, represents the kth shift p on segment s s,k Arrival at the end station of segment s moment; t fin Indicates the end time of the operating period; Constraining buses to start service within the time window expected by passengers Arrive at the passenger boarding point within: Where, represents the earliest expected service start time of request r; represents the kth shift p on segment s s,k Arrive at the boarding station o of request r r moment; The latest expected service start time for request r; Constrain vehicle m to perform shift p s,k and shifts There is no time conflict between: Where, represents the kth shift p on segment s s,k Arrival at the end station of segment s moment; Indicates segment On the flights Arrival section End site moment; Segment is a binary variable, if the modular vehicle m participates in the execution of the shift but otherwise 5. The modular bus dispatch optimization method for bus corridors according to claim 4 is characterized by: In step 6, the modular bus scheduling optimization model is solved to output the optimal scheduling solution sol * ; The specific process is: Step 6.

1. Construct the initial solution: Define the first level coding operation shift sequence G, in, g1 represents the vehicle number sequence of all shifts on section 1, g s represents the vehicle number sequence of all shifts on segment s, Indicates the composition segment S up +S dn The vehicle number sequence for all shifts; g 1,1 Indicates the first shift p on segment 1 1,1 Vehicle number, g 1,k Indicates the first shift p on segment 1 1,k Vehicle number; Indicates the K1th shift on segment 1 Vehicle number; g s,1 Indicates the first shift p on the component segment s s,1 Vehicle number; g s,k represents the kth shift p on the component segment s s,k Vehicle number; Indicates the Kth s flights Vehicle number; Indicates the composition segment S up +S dn The first shift Vehicle number; Indicates the composition segment S up +S dn The kth shift on Vehicle number; Indicates the composition segment S up +S dn On the flights Vehicle number; Defines the second layer coding service request sequence in, R1 represents the set of travel requests for all services on segment 1, R s represents the set sequence of travel requests for all services on segment s, Indicates segment S up +S dn The set sequence of travel requests for all services on the flight; R 1,1 Indicates the first shift p on segment 1 1,1 The set of travel requests for the service, R 1,k represents the kth shift p on segment 1 1,k The set of travel requests for the service; Indicates the K1th shift on segment 1 The set of travel requests for the service; R s,1 represents the first shift p on segment s s,1 The set of travel requests for the service; R s,k represents the kth shift p on segment s s,k The set of travel requests for the service; Indicates the Kth s flights The set of travel requests for the service; Indicates segment S up +S dn The first shift The set of travel requests for the service; Indicates segment S up +S dn The kth shift on The set of travel requests for the service; Indicates segment S up +S dn On the flights The set of travel requests for the service; Define the third-level coded departure time sequence t A , in, represents the departure time sequence of all trains on section 1. represents the departure time sequence of all trains on section s, Indicates segment S up +S dn The departure time sequence of all trains; Indicates the first shift p on segment 1 1,1 The departure time, represents the kth shift p on segment 1 1,k departure time; Indicates the K1th shift on segment 1 departure time; represents the first shift p on segment s s,1 departure time; represents the kth shift p on segment s s,k departure time; Indicates the Kth s flights departure time; Indicates segment S up +S dn The first shift departure time; Indicates segment S up +S dn The kth shift on departure time; Indicates segment S up +S dn On the flights departure time; The specific process is: Step 6.1.1: Based on the passenger travel request R, combine the boarding station o of each request r r and the drop-off point r The respective sections and Count the passenger flow demand on each segment and calculate the starting station stored in segment s using formula (25) Number of modular vehicles Expressed as: Where, Indicates that at the start time t0 of the operation, the starting station stored in segment s The number of modular vehicles, in units; C s represents the passenger flow demand on segment s, in units of persons; From the set of all modular vehicle numbers involved in scheduling within the operating period T In, randomly selected Vehicles are assigned to the starting station of segment s And add it to the site before operation starts Stored vehicle number collection middle; During this process, ensure that each vehicle can only be assigned once; Step 6.1.2: Under the condition of satisfying the maximum shift group length constraint (18), traverse the data stored at the starting station generated in step 6.1.

1. Vehicle number collection Randomly select 1 to l max Vehicles are combined into a shift p s,k The vehicle number set g s, k, until each vehicle is assigned to a shift; For each request r, if And the flight number p s,k If the capacity constraint (19) is satisfied, then request r is assigned to shift p. s,k The service request set R s,k Until each request finds the corresponding boarding schedule; Under the conditions of satisfying the speed constraint (21) and the service request time window constraint (23), the shift p is randomly determined. s,k Departure time Until the departure time of each bus is confirmed; Indicates the boarding station o for request r r The section where it is located; Step 6.1.3: Calculate the shift p according to formula (1) in step 3.1 s,k At the end site Number of transfer passengers if According to step 3.2, shift p s,k It is necessary to make a transfer strategy judgment, and then split and combine the vehicles according to step 4 to complete the passenger transfer. Based on the passenger transfer results, the shift vehicle number set G and the service request set are updated. and departure time t A Otherwise, determine the next bus schedule; until the bus schedules in the bus corridor within the operating period T are gathered All shifts within the company have been inspected; Step 6.1.4: Combine the updated shift vehicle number set G and the updated shift service request set in step 6.1.3 and updated departure timetable set t A , find the one with the largest departure time in the existing set of flights Confirm the shift Arrival at the end station Moment Judge at the moment Number of modular vehicles stored at key sites if No reallocation is required; if Redistribute the key site u until the key site u meets Repeat step 6.1.4 until all key sites meet the The process of reallocating the key site u is as follows: 1) Traverse the key site set N KEY For each key site, find the The key site u of the condition and the vehicle number set M stored at site u u Random selection Vehicles, reallocated to meet The key station u′ of the condition is generated and a new shift is generated on the existing shift of the segment s containing the key station u′ Determine the composition of new shifts Vehicle number collection New flights Departure time for Service Passenger Request Collection is empty; 2) Update the vehicle number set M stored in the key sites u and u′ after reallocation u 、M u′ and number of stored vehicles Judge at the moment Number of modular vehicles stored at key sites if No reallocation is required; if Then re-execute 1) and 2) until the key site u satisfies Indicates that before the operation starts at time t0, at the key site u∈N KEY the number of modular vehicles stored; Indicates that before the operation starts at time t0, at the key site u′∈N KEY the number of modular vehicles stored; Step 6.1.5, the updated set of vehicle numbers G of the shift in step 6.1.4, and the updated set of shift service requests and updated departure times t A Together they constitute the initial solution sol0; Step 6.2: Design the destruction operator and repair operator. The specific process is as follows: Step 6.2.

1. Design five damage operators Specifically include: (1) Random destruction operator The specific process is: Randomly select 10% of the travel requests in the total demand and remove them from the current solution sol to obtain the destroyed solution sol d And add the deleted request to the list of requests to be served R d middle; The total demand is the set R of passenger travel requests collected on the passenger flow corridor during the operating period T in the past 30 working days; (2) Worst damage operator The specific process is: Define the insertion cost ΔS -r =C(sol)-C -r (sol); Among them, C(sol) represents the travel cost of the current solution sol, C -r (sol) represents the travel cost after removing travel request r from the current solution sol; Sort by insertion cost in descending order, select the top 10% of the travel requests and remove them from the current solution sol to obtain the destroyed solution sol d And add the deleted request to the list of requests to be served R d middle; (3) Correlation destruction operator The specific process is: Randomly select a travel request r, find the travel request r″′ that has the strongest correlation with request r according to formula (26), remove these two requests from the current solution sol, and repeat the above operation until the number of removed requests reaches 10% of the total demand, and then obtain the destroyed solution sol d And add the deleted request to the list of requests to be served R d middle; The total demand is the set R of passenger travel requests collected on the passenger flow corridor during the operating period T in the past 30 working days; Where, R(r, r″′) represents the correlation between requests r and r″′; and Represent the earliest service start time expected by requests r and r″′ respectively; and Represent the latest service start time expected by requests r and r″′ respectively; q r and q r″′ Represents the number of passengers contained in requests r and r″′ respectively, in units of persons; and Respectively represent the distances between the two requested boarding stations and the reference station 1, in km; and Respectively represent the distances between the two requested alighting stations and the benchmark station 1, in km; α, β, and χ represent parameters; (4) Modular vehicle destruction operator The specific process is: Randomly select 10% of the total number of modular vehicles and remove them from the current solution sol. Randomly select travel requests within the shift and remove them from the current solution sol until the capacity constraint (19) is met. Finally, the destroyed solution sol is obtained. d And add the deleted request to the list of requests to be served R d middle; (5) Bus schedule disruption operator The specific process is: Sort by passenger load factor in descending order, remove the last 10% of the flights, and get the solution after destruction. d And add the travel requests served by the shift to the waiting service request list R d middle; Step 6.2.2: Solution after destruction d and the list of requests to be serviced R d , two repair operators are designed Repair the damaged solution d Get the new solution sol′, which specifically includes: (1) Solution after destruction d and the list of requests to be serviced R d , design random repair operator Repair the damaged solution d Get the new solution sol′, which specifically includes: Traverse the list of requests to be served R d For each travel request r, according to step 1.4, the request r is classified and randomly inserted into the sol according to the category to which the request belongs. d In the process, update the operating shift sequence G and the travel request sequence served by the shift and the departure time sequence t A ; Until the waiting service request list R d All travel requests are inserted into the final solution sol′; (2) Solution after destruction d and the list of requests to be serviced R d , design greedy repair operator Repair the damaged solution d Get the new solution sol′, which specifically includes: Traverse the list of requests to be served R d For each travel request r, according to step 1.4, the request r is classified and randomly inserted into the sol according to the category to which the request belongs. d middle; Calculate the sol for inserting travel request r d The total cost C after destruction and the solution sol d The difference in the total cost C of the insert trip request r corresponding to the minimum difference is inserted into sol d In the process, update the operating shift sequence G and the travel request sequence served by the shift and the departure time sequence t A ; Until the waiting service request list R d All travel requests are inserted into the final solution sol′; Step 6.3: Generate operator pairs and initialize operator pair weights. The specific process is as follows: For the destruction operator γ designed in step 6.2 des With the repair operator γ rep Combine two by two to generate 5×2 operator pairs Initially, each operator pair The weights are all 1 and the scores are all 0; Step 6.4: Solve the modular bus scheduling optimization model based on steps 6.1, 6.2, and 6.3, and output the optimal scheduling solution sol * ; The specific process is: 6.4.

1. Let the number of iterations θ = 1; 6.4.

2. Select destruction and repair operators and generate new solutions; 6.4.

3. Update the current solution and the optimal solution; 6.4.

4. Update the score of the operator pair; 6.4.

5. Update operator pair weights; 6.4.

6. Let the number of iterations θ = θ + 1, and the updated operator score sc `i,`j and the updated operator pair weights Substitute into step 6.4.2, repeat steps 6.4.2 to 6.4.6 until the maximum number of iterations G is reached, and output the optimal scheduling solution sol * ; This includes the set of vehicle numbers, the set of service requests, and the departure time for each operating shift in the scheduling plan.

6. The modular bus dispatch optimization method for bus corridors according to claim 5 is characterized in that: in step 6.4.2, the destruction and repair operators are selected and a new solution is generated; the specific process is: Step 6.4.2.

1. Select the destruction and repair operators: Based on the roulette strategy, randomly select the operator pair according to the normalized weight of the operator. The specific process is: First, according to formula (27), the operator Weight standardization: Where, Represents operator pairs The weight of represents the sum of all operator pairs’ weights; Represents operator pairs The probability of being selected satisfies Among them, the parameter σ is set to balance the relationship between solution time and timeliness of weight update; Next, the cumulative probability interval is constructed for each operator pair according to formula (28): In the formula, the initial cumulative probability is 0, Represents the cutoff operator pair The cumulative probability of Then, a uniformly distributed random number `r∈[0,1] is generated, and the corresponding operator pair is selected according to the cumulative probability interval that the random number `r falls into. Step 6.4.2.2: Generate a new solution. The specific process is as follows: Operator pairs selected according to 6.4.2.1 Determine the selected destruction operator and repair operators Follow step 6.2 to operate on the current solution sol and obtain a new solution sol′.

7. The modular bus dispatch optimization method for bus corridors according to claim 6, characterized in that: In step 6.4.3, the current solution and the optimal solution are updated; the specific process is: Define sol, sol′, sol * Represent the current solution, new solution and optimal solution respectively; If C(sol′)>C(sol*), then the optimal solution sol * The value of is replaced by the value of the new solution sol′; If C(sol′)>C(sol), the value of the current solution sol is replaced by the value of the new solution sol′; If C(sol′)≤C(sol), the simulated annealing criterion is used to decide whether to accept the new solution; the specific process is: Generate a random number `r∈[0,1], if `r<p ac , the value of the current solution sol is replaced by the value of the new solution sol′; otherwise, the value of the current solution sol remains unchanged and the new solution sol′ is not accepted; Calculate the simulated annealing probability p according to formula (29) ac : Among them, T tem represents the annealing temperature; C(sol′ represents the objective function value of the new solution sol′; C(sol*) represents the optimal solution sol * The objective function value of the current solution sol.

8. The modular bus dispatch optimization method for bus corridors according to claim 7, characterized in that: In step 6.4.4, the scores of the operator pairs are updated; the specific process is: Design operator to score sc `i,`j Update rules: If C(sol′)>C(sol*), the operator pair score increases by δ1; If C(sol′)>C(sol), the operator pair score increases by δ2; If C(sol′)≤C(sol), if it is accepted by the simulated annealing criterion, the score of the operator pair increases by δ3; if it is not accepted by the simulated annealing criterion, the score of the operator pair remains unchanged.

9. The modular bus dispatch optimization method for bus corridors according to claim 8, characterized in that: In step 6.4.5, the weight of the operator pair is updated; the specific process is: definition Represents operator pairs In the The weight of the iteration, κ,κ∈(0,1) represents the reaction coefficient, sc `i,`j Represents operator pairs The score, t `i,`j Represents operator pairs Number of successful applications; Update the weight according to formula (30):

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