CN116523166A - High-speed rail train running path optimization method and device based on path distribution passenger flow - Google Patents

Abstract

The invention provides a high-speed rail train starting path optimization method and device based on path distribution passenger flow, which comprises the steps of firstly calculating the passenger flow distribution of a high-speed rail travel path based on the distribution passenger flow of each travel path on a given high-speed rail network, and further determining a candidate starting station and a candidate final destination station of the high-speed rail train starting; then combining the calculated passenger flow distribution of the high-speed rail travel path, and selecting the path as a candidate travel path of the high-speed rail train; then, taking the running number of each high-speed rail train candidate running path organization as a decision variable, taking the minimum running cost of the high-speed rail train as an optimization target, and taking the interval running train capacity limit and the passenger flow conveying capacity limit as constraint conditions to construct a high-speed rail train candidate running path running number optimization model; and finally, designing a decoding code of the number scheme of the train candidate route start-up, and solving a high-speed railway train candidate route start-up number optimization model by adopting a genetic algorithm to obtain an optimal solution. The invention has the advantages of strong operability, high calculation speed and the like.

Description

High-speed rail train running path optimization method and device based on path distribution passenger flow

Technical Field

The invention relates to the technical field of railway transportation, in particular to a high-speed railway train running path optimization method and device based on path distribution passenger flow.

Background

The method for compiling the running scheme of the passenger train is an important link of the operation and transportation organization of the high-speed railway, and simultaneously has important significance as an instructive technical document for implementing a pre-lapping stage of a newly built high-speed railway and completing the work of evaluating the social benefit, the economic benefit and the like of the railway. The new line design stage compiles a train running scheme taking the passenger flow requirement as a core, analyzes the characteristics of space-time distribution, structure and the like of the passenger flow requirement, takes resources such as actual transportation capacity of a road network, application of a motor train unit and the like as constraint conditions, and determines important contents such as running paths, quantity and the like of the running scheme according to utility targets of railway transportation enterprises and travel passengers so as to reasonably allocate the resources and realize networking reasonable transportation. The reasonable running scheme not only can rationalize passenger transportation organization and maximize the operation benefit of transportation enterprises in the operation stage, but also can make the evaluation of new lines more reasonable, objective and accurate in the new line design pre-research stage, and effectively improve the operation efficiency of the high-speed railway.

The 'driving by flow' as a basic principle for organizing the driving of a high-speed railway train can embody the important influence of the passenger flow on the driving scheme, and is particularly embodied in the research of passenger flow prediction and passenger flow distribution; along with the gradual perfection of expressway networks in recent years, the passenger flow distribution and the train running path under the networking condition are also gradually and deeply researched, and a foundation is laid for programming a reasonable running scheme.

However, in the prior art, the research on the running scheme is mostly the problems of the running scheme programming flow, optimization and the like facing the operation stage, and passenger flow distribution is performed by constructing the existing high-speed railway transportation network physical model, so that the running scheme programming and optimization is completed. Therefore, the running scheme has limitation in the function of running, such as transferring passenger flow in high-speed rail with excessive current situation, so that the capability of large-scale node stations, waiting areas and the like are seriously insufficient (such as Zhengzhou east, guangzhou south and the like), the passenger flow travel time is prolonged, the high-speed rail service quality is influenced, and the high-speed rail system cost is increased.

Disclosure of Invention

The invention discloses a high-speed rail train running path optimizing method and device based on path distribution passenger flow, which are used for solving or at least partially solving the technical problem of poor running scheme compiling effect in the prior art.

In order to solve the technical problem, the first aspect of the invention provides a high-speed railway train running path optimization method based on path distribution passenger flow, comprising the following steps:

s1: calculating the passenger flow distribution of the travel paths of the high-speed rail based on the allocated passenger flow of each travel path on the given high-speed rail network, wherein the passenger flow distribution of the travel paths of the high-speed rail comprises the passing passenger flow, the terminating passenger flow and the originating passenger flow in each section direction of each line of the high-speed rail;

s2: determining candidate starting stations and candidate final destination stations of the running of the high-speed rail train according to the calculated passenger flow distribution of the high-speed rail travel path and whether the section has the conditions of starting and final destination train equipment;

s3: combining the calculated passenger flow distribution of the high-speed rail travel path, and selecting a path between the candidate originating station and the candidate terminating station determined in the step S2 as a high-speed rail train candidate travel path;

s4: the method comprises the steps of constructing a high-speed train candidate route running number optimization model by taking running number of each high-speed train candidate running route organization as a decision variable, taking the minimum running cost of the high-speed train as an optimization target and taking interval running train capacity limit and passenger flow conveying capacity limit as constraint conditions;

s5: designing a decoding scheme of the number of the train candidate routes, designing an operation strategy of selection, intersection and variation, and solving a high-speed railway train candidate route start number optimization model by adopting a genetic algorithm to obtain an optimal solution, wherein the encoding of a chromosome corresponding to the optimal solution is the high-speed railway train start route, and the length of the chromosome is the start number.

In one embodiment, in step S1, the calculation modes of the passing passenger flow volume, the terminating passenger flow volume and the originating passenger flow volume in each section direction of each line of the high-speed rail are as follows:

wherein ,is the section of the high-speed rail line, < >>For a passenger flow travel path set, < > for>A passenger flow travel path is shown,to select a passenger flow travel path->Is to travel passenger flow, is to be treated>The direction of the initial section and the direction of the final section of the passenger flow travel path are respectively +.>、/>、/>The sections of the high-speed railway lines are respectively +>Through traffic, terminating traffic, and originating traffic.

In one embodiment, step S2 includes:

for only one section being joinedStation->At this time->For the end station if its originating traffic satisfies +.>Then select it as a candidate originator; if its final passenger flow volume satisfies + ->Then select it as a candidate terminating station;

for joining only two intervalsAnd->Station->At this time->For non-cross-point stations, if from section +.>Is +.>Terminating site->The difference between the end-to-end passenger flows of a train is greater than the minimum passenger flow required to travel an originating train, then it is determined as a candidate originating station:

if the slave sectionFinally get->Is equal to the end-to-end passenger flow volume and the slave interval- >The difference between the originating passenger flows is greater than that of a train from one end to the nextThe minimum amount of traffic needed is determined to be a candidate terminating station:

wherein ,for train-officer->Minimum originating boarding rate required for starting originating trains for station organization, < >>For site->In section->Originating passenger flow in direction, +.>For +.>Terminating site->Is to the end of the passenger flow, ">For +.>Terminating site->Is to the end of the passenger flow, ">For site->In section->Originating traffic in the direction;

for stations joining three or more sectionsAt this time->The method comprises the steps of calculating the number of initial trains and the number of final trains required to be driven by a station according to the total initial passenger flow and the total final passenger flow of the station, and calculating the station->From interval->After arriving at the station, the station is further divided into sections->The number of passing trains leaving, simultaneously ensuring that the end-to-end passenger flow volume of the former section is equal to the original passenger flow volume of the latter section when the passing trains serve two sections, and finally determining the station->Whether it is a candidate originating station or a candidate terminating station.

In one embodiment, for a station that links three or more intervalsDetermining the number of originating trains and the number of terminating trains required to be organized and running, and determining the station ∈ - >Whether it is a candidate originating station or a candidate terminating station specifically includes:

calculating the number of initial trains and the number of final trains required to be started at a station:

wherein ,representing site->The total number of trains that need to be organized for the originating passenger flow trip, < >>Representing site->The total number of trains required to be organized for the final passenger flow trip, including final and passing trains, +>For train-officer->Minimum originating boarding rate required for a station organization to start an originating train;

constructing a linear programming model:

wherein ,for a set of all intervals, constraints of the linear programming model include:

1) Menstrual intervalAll passenger carrying capacity provided by the train to and from other sections is no higher than the sectionIs the final passenger flow volume of (1), i.e

wherein ,for interval->Is the final passenger flow volume;

2) Arriving via other intervals and arriving from intervalsAll passenger carrying capacity offered by the train at departure is not higher than the slave section +.>Originating passenger traffic, i.e

wherein ,for +.>Originating passenger traffic;

calculating the number of initial trains and the number of final trains required to be organized by solving a linear programming model:

wherein ,and->Respectively represent site->The number of initial trains and the number of final trains which are started are organized, and when the number is decimal, the number is an integer.

In one embodiment, step S3 includes:

s301: initializing a set of train candidate paths；

S302: for any candidate originator-zoneCycling selection from a set of passenger travel pathsPassenger flow travel route as origin +.>If->Terminal interval-station belonging to the group->The passenger flow travel path is +.>Add to the collection->The method comprises the steps of carrying out a first treatment on the surface of the Otherwise, from->The terminal section of (a) station starts to find the nearest one belonging to the set +.>To add this route to +.>Wherein the candidate originator-zone represents a candidate to zone,representing a set of candidate starting station to station, terminal station to station,/>Representing a set of candidate intervals to the end station;

s303: deleting the repeated paths contained in the obtained train candidate path set, and taking the reserved paths as train candidate running paths;

s304: and judging whether the conditions of the originating and terminating train equipment are met or not for the candidate originating station and the candidate terminating station in the train candidate starting path, and deleting the candidate originating station or the candidate terminating station if the conditions are not met.

In one embodiment, step S4 includes:

S401: selecting the number of running trains organized by the candidate running paths of each high-speed rail train as a model decision variable；

S402: selecting a model optimization target, and constructing a high-speed train candidate path running number optimization model:

wherein the first partFor the total operation mileage of the running train +.>Represents the average cost per kilometer of train operation, +.>For the path->Is a running mileage of (1); second part->Organizing costs for running trains, < >>The constraint conditions for representing the average cost for organizing a train and the optimization model of the running number of the candidate paths of the high-speed rail train comprise:

constraint 1:

wherein ,representing the path->A person on the train to drive, +.>Representing the path->And section->If the association relation of (a) is intervalBelonging to the path->Then->The method comprises the steps of carrying out a first treatment on the surface of the Otherwise, go (L)>，/>For interval->Is a total trip amount of the vehicle;

constraint 2:

wherein ,for the line interval->Maximum number of trains running in the whole day operating time range,/-for>For train running pathAnd line interval->If the line interval is +.>Belongs to the train driving path->1 if not, otherwise 0;

constraint 3:

(1) for non-cross point stations that join only one or two line intervals:

wherein ,、/>the starting interval and the ending interval of the path p;

(2) For a fork station that joins more than two line intervals:

from fork point stationThe number of the starting trains through each connection interval meets the following conditions:

terminating to fork station via each connection intervalThe number of final trains satisfies:

wherein ,for a given number of floating trains, < > a->And->Separate list site->It is necessary to organize the number of originating trains and the number of terminating trains that are in progress.

In one embodiment, step S5 includes:

s501: constructing a solution code of a candidate path starting train number scheme, wherein the code length is the number of candidate paths, each bit code corresponds to one candidate path, the codes are expressed by non-negative integers, and when a certain bit code is 0, the corresponding candidate path does not organize the starting train; otherwise, organizing and running trains with corresponding integer numbers;

s502: random generation according to designed coding schemeIndividual initial individuals added to the initial population +.>In which, if an unsatisfactory individual is produced, the individual is discarded from the re-random generation until +.>A plurality of initial individuals;

s503: selection operation: computing populationFitness of all individuals>Sequencing from big to small according to fitness, and calculating the individual +.>Selection probability of +.>And cumulative probability- >As the probability that each individual in the population is selected into the next generation population:

randomly generating a random numberAnd select to satisfy->Is->This is repeated until a selection of +.>Individual individuals are used as individuals of the next generation population; wherein (1)>For individuals->，/>For individuals->Is adaptive to->Representing the sub-population->Selecting the fitness of the individual with the greatest fitness +.>For individuals->Is selected according to the selection probability of (1);

s504: crossover operation: randomly generating a random numberIf it is smaller than the set crossover probability +.>Then selectSelecting two chromosomes->And->And (3) crossing:

wherein ,random numbers, 0-1 for +.>,/>Is chromosome->And->Crossing offspring chromosomes;

s505: mutation operation: randomly generating a random numberIf it is smaller than the set mutation probability +.>Randomly selecting the +.>The individual genes are used as mutation sites, and new gene values are randomly generated to replace the original gene values;

s506: returning to S503 for selection operation, cross operation and variation operation, if the population keeps the optimal value continuous generation unchanged or reaches the maximum iteration number, stopping the algorithm, and returning to the optimal chromosome; otherwise, the algorithm continues iterative optimization, wherein the optimal chromosome is the optimal solution of the genetic algorithm, the length of the chromosome is the number of candidate paths, and each bit code corresponds to one candidate path.

Based on the same inventive concept, a second aspect of the present invention provides a high-speed railway train running path optimizing device based on path distribution passenger flow, comprising:

the high-speed railway travel path passenger flow distribution calculation module is used for calculating high-speed railway travel path passenger flow distribution based on the distribution passenger flow of each travel path on a given high-speed railway network, wherein the high-speed railway travel path passenger flow distribution comprises the passing passenger flow, the ending passenger flow and the starting passenger flow in each section direction of each high-speed railway line;

the candidate starting station and final destination station determining module is used for determining candidate starting stations and candidate final destination stations for starting the high-speed rail train according to the calculated passenger flow volume distribution of the high-speed rail travel path and whether the section has the conditions of starting and final destination train equipment;

the high-speed rail train candidate starting path determining module is used for combining the calculated passenger flow volume distribution of the high-speed rail travel path, and selecting a path between the candidate starting station and the candidate final destination station determined in the step S2 as a high-speed rail train candidate starting path;

the high-speed railway train candidate path running number optimizing model construction module is used for constructing a high-speed railway train candidate path running number optimizing model by taking running number of each high-speed railway train candidate running path organization as a decision variable, taking the minimum running cost of the high-speed railway train as an optimizing target and taking interval running train capacity limit and passenger flow conveying capacity limit as constraint conditions;

The model solving module is used for designing the decoding of the number scheme of the train candidate routes and designing the operation strategies of selection, intersection and variation, and solving the optimized model of the number of the train candidate routes by adopting a genetic algorithm to obtain an optimal solution, wherein the chromosome code corresponding to the optimal solution is the train route of the high-speed railway

Based on the same inventive concept, a third aspect of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed, implements the method of the first aspect.

Based on the same inventive concept, a fourth aspect of the present invention provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, said processor implementing the method according to the first aspect when executing said program.

Compared with the prior art, the invention has the following advantages and beneficial technical effects:

the invention discloses a high-speed railway train running path optimization method based on path distribution passenger flows, which comprises the steps of firstly calculating the passenger flow distribution of the high-speed railway running paths based on the distribution passenger flow of each running path on a given high-speed railway network, screening station sets of which part is possible to be a train starting station and a station ending station from all high-speed railway stations according to the starting and ending passenger flow distribution of station connection intervals, simultaneously selecting part of reasonable paths from the inter-station paths according to the running path passenger flow distribution as a train candidate running path set, generating the paths of the high-speed railway running paths possible to run the train according to the passenger flow running paths on the basis of distributing and obtaining each OD passenger flow running path set by distributing a passenger flow path network, and finally constructing a high-speed railway train candidate running path quantity optimization model and solving by adopting a genetic algorithm to obtain an optimal path planning scheme: the length of the chromosome is the number of trains running. The method has the advantages of strong operability, high calculation speed and the like, and the high-speed train running path obtained through optimization by the method can reduce the transfer of long-distance passengers to the greatest extent, save the travel mileage of the passengers and realize the high-speed train running path and the high-speed train running path to be matched. Meanwhile, the method can also obtain the number of the trains running on each train running path, so that the number of the trains running on each line section is ensured to meet the requirements of the section train running capacity and the passenger flow conveying capacity, and the train running cost is saved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic flow chart of a method for optimizing a running path of a high-speed rail train based on path allocation passenger flow, which is provided by an embodiment of the invention.

Detailed Description

The invention aims to provide a high-speed railway train running path optimization method based on path distribution passenger flow, the running path of the high-speed railway train and the corresponding running quantity thereof obtained through optimization by the method can be in high consistency with the passenger running path, the passenger running transfer is reduced to the greatest extent, the passenger running mileage is shortened, and meanwhile, the running efficiency of the high-speed railway train is improved.

In order to achieve the above object, the present invention needs to solve the following key technologies:

(1) High-speed rail network passenger flow distribution: the "on-stream driving" is the most basic principle of organizing and driving a high-speed rail train, and because there may be two or more travel paths of OD passenger flows under the networked operation condition of the high-speed rail, the "flow" should not be limited to OD passenger flows only, but should be travel path passenger flows covering path information. Under the limit of the passenger flow conveying capacity of a high-speed railway line section, the demand of each OD traveling passenger flow is distributed to a plurality of traveling paths among the ODs according to a certain principle, and the formation of the traveling path passenger flow is the first key technology to be solved by the invention.

(2) Train candidate originating and terminating selection: according to the distribution of the initial and final arrival passenger flows of the station connection interval, a station set of which part is possibly the initial and final arrival of the train is screened out from all the high-speed railway stations, and meanwhile, according to the passenger flow distribution of the travel path, a part of reasonable paths are selected from the paths among the stations to serve as a train candidate travel path set, so that the second key technology to be solved by the invention is realized;

(3) Optimizing a train candidate path: on the basis of distributing the passenger flow path network and obtaining each OD passenger flow travel path set, a path of possible driving of the train of the high-speed railway is generated according to the passenger flow travel paths. On the basis of a given train candidate running path set, the running number of each candidate train path is optimally calculated by combining the passenger flow volume of each passenger flow running path in the passenger flow running path set.

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of 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, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present 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.

Example 1

The embodiment of the invention provides a high-speed railway train running path optimization method based on path distribution passenger flow, which comprises the following steps:

s1: calculating the passenger flow distribution of the travel paths of the high-speed rail based on the allocated passenger flow of each travel path on the given high-speed rail network, wherein the passenger flow distribution of the travel paths of the high-speed rail comprises the passing passenger flow, the terminating passenger flow and the originating passenger flow in each section direction of each line of the high-speed rail;

s2: determining candidate starting stations and candidate final destination stations of the running of the high-speed rail train according to the calculated passenger flow distribution of the high-speed rail travel path and whether the section has the conditions of starting and final destination train equipment;

s3: combining the calculated passenger flow distribution of the high-speed rail travel path, and selecting a path between the candidate originating station and the candidate terminating station determined in the step S2 as a high-speed rail train candidate travel path;

s4: the method comprises the steps of constructing a high-speed train candidate route running number optimization model by taking running number of each high-speed train candidate running route organization as a decision variable, taking the minimum running cost of the high-speed train as an optimization target and taking interval running train capacity limit and passenger flow conveying capacity limit as constraint conditions;

s5: designing a decoding scheme of the number of the train candidate routes, designing an operation strategy of selection, intersection and variation, and solving a high-speed railway train candidate route start number optimization model by adopting a genetic algorithm to obtain an optimal solution, wherein the encoding of a chromosome corresponding to the optimal solution is the high-speed railway train start route, and the length of the chromosome is the start number.

Fig. 1 is a schematic flow chart of a method for optimizing a running path of a high-speed rail train based on path allocation passenger flow according to an embodiment of the present invention.

Specifically, the allocated passenger flow volume of each travel path on a given high-speed railway network refers to the OD passenger flow volume under the high-speed railway networked operation condition.

In one embodiment, in step S1, the calculation modes of the passing passenger flow volume, the terminating passenger flow volume and the originating passenger flow volume in each section direction of each line of the high-speed rail are as follows:

wherein ,is the section of the high-speed rail line, < >>For a passenger flow travel path set, < > for>A passenger flow travel path is shown,to select a passenger flow travel path->Is to travel passenger flow, is to be treated>The direction of the initial section and the direction of the final section of the passenger flow travel path are respectively +.>、/>、/>The sections of the high-speed railway lines are respectively +>Through traffic, terminating traffic, and originating traffic.

In one embodiment, step S2 includes:

for only one section being joinedStation->At this time->For the end station if its originating traffic satisfies +.>Then select it as a candidate originator; if its final passenger flow volume satisfies + ->Then select it as a candidate terminating station;

for joining only two intervalsAnd->Station->At this time- >For non-cross-point stations, if from section +.>Is +.>Terminating site->The difference between the end-to-end passenger flows of a train is greater than the minimum passenger flow required to travel an originating train, then it is determined as a candidate originating station:

if the slave sectionFinally get->Is equal to the end-to-end passenger flow volume and the slave interval->The difference in originating traffic is greater than the minimum traffic required to travel a train of terminating traffic, then it is determined to be a candidate terminating station:

wherein ,for train-officer->Minimum originating boarding rate required for starting originating trains for station organization, < >>For site->In section->Originating passenger flow in direction, +.>For +.>Terminating site->Is to the end of the passenger flow, ">For +.>Terminating site->Is to the end of the passenger flow, ">For site->In section->Originating traffic in the direction;

for stations joining three or more sectionsAt this time->For the fork point station, the total initial passenger flow and the total final passenger flow of the station are calculatedThe number of originating trains and terminating trains that need to be started to the station, and then calculating the station +.>From interval->After arriving at the station, the station is further divided into sections->The number of passing trains leaving, simultaneously ensuring that the end-to-end passenger flow volume of the former section is equal to the original passenger flow volume of the latter section when the passing trains serve two sections, and finally determining the station- >Whether it is a candidate originating station or a candidate terminating station.

Specifically, for different stations, it is determined whether the station is a candidate originating station or a candidate terminating station.

In one embodiment, for a station that links three or more intervalsDetermining the number of originating trains and the number of terminating trains required to be organized and running, and determining the station ∈ ->Whether it is a candidate originating station or a candidate terminating station specifically includes:

calculating the number of initial trains and the number of final trains required to be started at a station:

wherein ,representation ofSite->The total number of trains that need to be organized for the originating passenger flow trip, < >>Representing site->The total number of trains required to be organized for the final passenger flow trip, including final and passing trains, +>For train-officer->Minimum originating boarding rate required for a station organization to start an originating train;

constructing a linear programming model:

wherein ,for a set of all intervals, constraints of the linear programming model include:

1) Menstrual intervalAll passenger carrying capacity provided by the train to and from other sections is no higher than the sectionIs the final passenger flow volume of (1), i.e

wherein ,is interval of/>Is the final passenger flow volume;

2) Arriving via other intervals and arriving from intervals All passenger carrying capacity offered by the train at departure is not higher than the slave section +.>Originating passenger traffic, i.e

wherein ,for +.>Originating passenger traffic;

calculating the number of initial trains and the number of final trains required to be organized by solving a linear programming model:

wherein ,and->Respectively represent site->The number of initial trains and the number of final trains which are started are organized, and when the number is decimal, the number is an integer.

Specifically, the cross point station slave interval can be calculated by constructing a linear programming modelAfter arriving at the station, the station is further divided into sections->Number of passing trains leaving->. The model expects to schedule all originating, terminating traffic to be serviced by the trains, so selecting the number of passing trains that are maximally driven as the model optimization goal, while requiring that each train has equal terminating traffic to originating traffic that is serviced by the trains through the zones before and after (i.e., equal terminating traffic in the preceding zone and originating traffic in the following zone when the passing trains are servicing both zones), and if not, exceeding portions of originating traffic or terminating traffic considers that it is serviced by the originating train or terminating train, regardless of organization passing trains. Thus, constraints of the linear model can be obtained.

For stations joining three or more sections, if the calculated number of originating and terminating trains that the station needs to organize to start is a positive integer, it is indicated that the station can be the originating station or the terminating station.

It can be seen that the model constructed above is a typical linear programming model and has a smaller scale, so that a correlation solver, such as Cplex, lingo, etc., can be directly and rapidly solved.

In one embodiment, step S3 includes:

s301: initializing a set of train candidate paths；

S302: for any candidate originator-zoneCycling selection from a set of passenger travel pathsPassenger flow travel route as origin +.>If->Terminal interval-station belonging to the group->The passenger flow travel path is +.>Add to the collection->The method comprises the steps of carrying out a first treatment on the surface of the Otherwise, from->The terminal section of (a) station starts to find the nearest one belonging to the set +.>To add this route to +.>Wherein the candidate originator-zone represents a candidate to zone,representing a set of candidate starting station to station, terminal station to station,/>Representing a set of candidate intervals to the end station;

s303: deleting the repeated paths contained in the obtained train candidate path set, and taking the reserved paths as train candidate running paths;

S304: and judging whether the conditions of the originating and terminating train equipment are met or not for the candidate originating station and the candidate terminating station in the train candidate starting path, and deleting the candidate originating station or the candidate terminating station if the conditions are not met.

Specifically, the conditions of equipment for originating and terminating a candidate originating station and a candidate terminating station in a candidate train starting path mean that the originating station is a candidate originating station for a train and the originating section is a passenger flow originating section of the station; the ending station is a train candidate ending station, and the ending interval is a passenger flow ending interval of the station; at least one OD passenger flow travels entirely using the path.

In one embodiment, step S4 includes:

s401: selecting the number of running trains organized by the candidate running paths of each high-speed rail train as a model decision variable；

S402: selecting a model optimization target, and constructing a high-speed train candidate path running number optimization model:

wherein the first partFor the total operation mileage of the running train +.>Represents the average cost per kilometer of train operation, +.>For the path->Is a running mileage of (1); second part->Organizing costs for running trains, < >>The constraint conditions for representing the average cost for organizing a train and the optimization model of the running number of the candidate paths of the high-speed rail train comprise:

Constraint 1:

wherein ,representing the path->A person on the train to drive, +.>Representing the path->And section->If the association relation of (a) is intervalBelonging to the path->Then->The method comprises the steps of carrying out a first treatment on the surface of the Otherwise, go (L)>，/>For interval->Is a total trip amount of the vehicle;

constraint 2:

wherein ,for the line interval->Maximum number of trains running in the whole day operating time range,/-for>For train driving path->And line interval->If the line interval is +.>Belongs to the train driving path->1 if not, otherwise 0;

constraint 3:

(1) for non-cross point stations that join only one or two line intervals:

wherein ,、/>the starting interval and the ending interval of the path p;

(2) for a fork station that joins more than two line intervals:

from fork point stationThe number of the starting trains through each connection interval meets the following conditions:

terminating to fork station via each connection intervalThe number of final trains satisfies:

wherein ,for a given number of floating trains, < > a->And->Separate list site->It is necessary to organize the number of originating trains and the number of terminating trains that are in progress.

When the model optimization target is selected, the number of train operation is reduced as much as possible on the premise of ensuring the passenger flow trip in order to reduce the train operation cost. Considering that different running trains have different running distances, the corresponding running costs are different, and the total mileage of the minimum train path travel is taken as an optimization target for simplicity; meanwhile, in order to avoid organizing too many short distance trains and organizing long distance trains into a plurality of short distance trains to meet the travel demands of long distance passenger flows, the organizing cost of single trains is considered, so that the model optimization target can be obtained.

For the constraint condition of the model, the passenger flow conveying capacity of the train provided by the section is not lower than the passenger flow traveling capacity of the section, namely the passenger flow carrying capacity of all trains provided by the section in the direction of a certain section is not lower than the total traveling capacity of the section, and the constraint condition 1 is obtained by taking the section as the originating passenger flow or the terminating passenger flow of each OD (optical density) passing through the section.

The number of interval running trains is smaller than the line running capacity, namely the sum of passing, starting and ending trains running in a certain interval direction is necessarily smaller than the maximum number of trains in the interval direction, so that constraint condition 2 is obtained.

In order to avoid the disadvantage that a large number of short distance trains are used for meeting the requirement of long distance passenger flow travel, namely, long distance passenger flow needs to be transferred among a plurality of short distance trains to complete travel, the quantity of originating and terminating trains for station departure needs to be controlled in a constraint mode.

For non-cross-point stations (only one or two line intervals are engaged)

Terminating intervalIs the final passenger flow and the slave zone +.>The originating passenger flow can be originated from the channel section +.>Arrive, follow interval->The separated passing train serves to meet the traveling requirement of the two passenger flows, and compared with the way of respectively organizing a train to be ended and a train to be started, the passing interval is avoided >Arrive, follow interval->One transfer of exiting passing passenger flow. Thus, only the ending section +.>Is the final passenger flow->Not higher than the slave interval->Originating customer traffic->At this time, it is unnecessary to organize the ending section +.>Is terminated to the train. Similarly, as long as the interval is +.>Originating customer traffic->Not higher than the end-to-end interval->Is the final passenger flow->In this case, there is no need to organize the slave section +.>Originating train, thus gets the constraint of non-fork stations in constraint 3.

For fork station (connecting more than two line sections)

For cross point stations, the terminating intervalMay be organized to travel through the train with the originating traffic originating in a plurality of other intervals; likewise, section +.>The originating passenger flow may also be organized to travel through the train with the terminating passenger flow terminating in a plurality of other intervals. In addition, interzone trains in the up-down direction should not typically be organized into passing trains (if organized into trains, the passing trainsThe menstrual period +.>To a station and then from that section to leave the station, such passing trains are typically organized into a train of end-to-end trains and a train of originating trains). Thus, a fork station can be obtained first>The number of originating and terminating trains that need to be organized for a start-up And->. On the basis of this, let +_ from fork station>The number of trains launched through each splicing interval satisfies the formula of the fork station in constraint condition 3.

In one embodiment, step S5 includes:

s501: constructing a solution code of a candidate path starting train number scheme, wherein the code length is the number of candidate paths, each bit code corresponds to one candidate path, the codes are expressed by non-negative integers, and when a certain bit code is 0, the corresponding candidate path does not organize the starting train; otherwise, organizing and running trains with corresponding integer numbers;

s502: random generation according to designed coding schemeIndividual initial individuals added to the initial population +.>In which, if an unsatisfactory individual is produced, the individual is discarded from the re-random generation until +.>A plurality of initial individuals;

s503: selection operation: computing populationFitness of all individuals>Sequencing from big to small according to fitness, and calculating the individual +.>Selection probability of +.>And cumulative probability->As the probability that each individual in the population is selected into the next generation population:

randomly generating a random numberAnd select to satisfy->Is->This is repeated until a selection of +.>Individual individuals are used as individuals of the next generation population; wherein (1) >For individuals->，/>For individuals->Is adaptive to->Representing the sub-population->Selecting the fitness of the individual with the greatest fitness +.>For individuals->Is selected according to the selection probability of (1);

s504: crossover operation: randomly generating a random numberIf it is smaller than the set crossover probability +.>Then select two chromosomes +.>And->And (3) crossing:

wherein ,random numbers, 0-1 for +.>,/>Is chromosome->And->Crossing offspring chromosomes;

s505: mutation operation: randomly generating a random numberIf it is smaller than the set mutation probability +.>Randomly selecting the +.>The individual genes are used as mutation sites, and new gene values are randomly generated to replace the original gene values;

s506: returning to S503 for selection operation, cross operation and variation operation, if the population keeps the optimal value continuous generation unchanged or reaches the maximum iteration number, stopping the algorithm, and returning to the optimal chromosome; otherwise, the algorithm continues iterative optimization, wherein the optimal chromosome is the optimal solution of the genetic algorithm, the length of the chromosome is the number of candidate paths, and each bit code corresponds to one candidate path.

Specifically, if not, organizing the trains with corresponding integer numbers to be started refers to organizing the trains with the integer numbers of started when a certain bit is encoded into an integer a.

The optimal chromosome is the optimal solution of the genetic algorithm, and the running path and the running train quantity of the high-speed rail train can be obtained by decoding the chromosome. Chromosome decoding is: the chromosome length is the number of candidate paths, each bit code corresponds to one candidate path, and the codes are expressed by non-negative integers. When a certain bit code is 0, the corresponding candidate path does not organize a driving train; otherwise, the trains of corresponding integer numbers are organized.

In general, the optimization method for the high-speed rail train running path based on the path distribution passenger flow has the advantages of being strong in operability, high in calculation speed and the like, and the high-speed rail train running path obtained through optimization by the method can reduce long-distance passenger transfer to the greatest extent, save the passenger running mileage and achieve high coincidence of the high-speed rail train running path and the passenger running path. Meanwhile, the method can also obtain the number of the trains running on each train running path, so that the number of the trains running on each line section can meet the requirements of the section train running capacity and the passenger flow conveying capacity, and the train running cost is saved.

Example two

Based on the same inventive concept, the embodiment provides a high-speed railway train running path optimizing device based on path distribution passenger flow, which comprises:

The high-speed railway travel path passenger flow distribution calculation module is used for calculating high-speed railway travel path passenger flow distribution based on the distribution passenger flow of each travel path on a given high-speed railway network, wherein the high-speed railway travel path passenger flow distribution comprises the passing passenger flow, the ending passenger flow and the starting passenger flow in each section direction of each high-speed railway line;

the candidate starting station and final destination station determining module is used for determining candidate starting stations and candidate final destination stations for starting the high-speed rail train according to the calculated passenger flow volume distribution of the high-speed rail travel path and whether the section has the conditions of starting and final destination train equipment;

the high-speed rail train candidate starting path determining module is used for combining the calculated passenger flow volume distribution of the high-speed rail travel path, and selecting a path between the candidate starting station and the candidate final destination station determined in the step S2 as a high-speed rail train candidate starting path;

the high-speed railway train candidate path running number optimizing model construction module is used for constructing a high-speed railway train candidate path running number optimizing model by taking running number of each high-speed railway train candidate running path organization as a decision variable, taking the minimum running cost of the high-speed railway train as an optimizing target and taking interval running train capacity limit and passenger flow conveying capacity limit as constraint conditions;

The model solving module is used for designing a decoding code of a train candidate path running number scheme, designing an operation strategy of selection, intersection and variation, and adopting a genetic algorithm to solve a high-speed railway train candidate path running number optimizing model to obtain an optimal solution, wherein the code of a chromosome corresponding to the optimal solution is a high-speed railway train running path, and the length of the chromosome is the running train number.

Since the device described in the second embodiment of the present invention is a device for implementing the method for optimizing the running path of the high-speed rail train based on the path allocation passenger flow in the first embodiment of the present invention, based on the method described in the first embodiment of the present invention, a person skilled in the art can understand the specific structure and the deformation of the device, and thus the detailed description thereof is omitted herein. All devices used in the method of the first embodiment of the present invention are within the scope of the present invention.

Example III

Based on the same inventive concept, the present invention also provides a computer-readable storage medium having stored thereon a computer program which, when executed, implements the method as described in embodiment one.

Because the computer readable storage medium introduced in the third embodiment of the present invention is a computer readable storage medium used for implementing the method for optimizing the running path of the high-speed train based on the path allocation passenger flow in the first embodiment of the present invention, based on the method introduced in the first embodiment of the present invention, a person skilled in the art can understand the specific structure and the modification of the computer readable storage medium, and therefore, the description thereof is omitted herein. All computer readable storage media used in the method according to the first embodiment of the present invention are included in the scope of protection.

Example IV

Based on the same inventive concept, the present application also provides a computer device, including a storage, a processor, and a computer program stored on the storage and executable on the processor, where the processor implements the method in the first embodiment when executing the program.

Because the computer device described in the fourth embodiment of the present invention is a computer device used for implementing the method for optimizing the running path of the high-speed rail train based on the path allocation passenger flow in the first embodiment of the present invention, based on the method described in the first embodiment of the present invention, a person skilled in the art can understand the specific structure and the deformation of the computer device, and therefore, the details are not repeated here. All computer devices used in the method of the first embodiment of the present invention are within the scope of the present invention.

It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.

It will be apparent to those skilled in the art that various modifications and variations can be made to the embodiments of the present invention without departing from the spirit or scope of the embodiments of the invention. Thus, if such modifications and variations of the embodiments of the present invention fall within the scope of the claims and the equivalents thereof, the present invention is also intended to include such modifications and variations.

Claims (10)

1. The high-speed train running path optimization method based on the path distribution passenger flow is characterized by comprising the following steps of:

s1: calculating the passenger flow distribution of the travel paths of the high-speed rail based on the allocated passenger flow of each travel path on the given high-speed rail network, wherein the passenger flow distribution of the travel paths of the high-speed rail comprises the passing passenger flow, the terminating passenger flow and the originating passenger flow in each section direction of each line of the high-speed rail;

s2: determining candidate starting stations and candidate final destination stations of the running of the high-speed rail train according to the calculated passenger flow distribution of the high-speed rail travel path and whether the section has the conditions of starting and final destination train equipment;

s3: combining the calculated passenger flow distribution of the high-speed rail travel path, and selecting a path between the candidate originating station and the candidate terminating station determined in the step S2 as a high-speed rail train candidate travel path;

s4: the method comprises the steps of constructing a high-speed train candidate route running number optimization model by taking running number of each high-speed train candidate running route organization as a decision variable, taking the minimum running cost of the high-speed train as an optimization target and taking interval running train capacity limit and passenger flow conveying capacity limit as constraint conditions;

s5: designing a decoding scheme of the number of the train candidate routes, designing an operation strategy of selection, intersection and variation, and solving a high-speed railway train candidate route start number optimization model by adopting a genetic algorithm to obtain an optimal solution, wherein the encoding of a chromosome corresponding to the optimal solution is the high-speed railway train start route, and the length of the chromosome is the start number.

2. The method for optimizing the running path of a high-speed railway train based on the path allocation passenger flow according to claim 1, wherein in the step S1, the calculation modes of the passing passenger flow, the terminating passenger flow and the originating passenger flow in each section direction of each line of the high-speed railway are as follows:

wherein ,is the section of the high-speed rail line, < >>For a passenger flow travel path set, < > for>Representing a passenger flow travel path,/a>To select a passenger flow travel path->Is to travel passenger flow, is to be treated>The direction of the initial section and the direction of the final section of the passenger flow travel path are respectively +.>、/>、/>The sections of the high-speed railway lines are respectively +>Through traffic, terminating traffic, and originating traffic.

3. The high-speed railway train running path optimization method based on path allocation passenger flow as claimed in claim 1, wherein the step S2 comprises:

for only one section being joinedStation->At this time->For the end station if its originating traffic satisfies +.>Then select it as a candidate originator; if its final passenger flow volume satisfies + ->Then select it as a candidate terminating station;

for joining only two intervalsAnd->Station->At this time->For non-cross-point stations, if from section +.>Is +.>Terminating site- >The difference between the end-to-end passenger flows of a train is greater than the minimum passenger flow required to travel an originating train, then it is determined as a candidate originating station:

if the slave sectionFinally get->Is equal to the end-to-end passenger flow volume and the slave interval->The difference in originating traffic is greater than the minimum traffic required to travel a train of terminating traffic, then it is determined to be a candidate terminating station:

wherein ,for train-officer->Minimum originating boarding rate required for starting originating trains for station organization, < >>For site->In section->Originating passenger flow in direction, +.>For +.>Terminating site->Is to the end of the passenger flow, ">For +.>Terminating site->Is to the end of the passenger flow, ">For site->In section->Originating traffic in the direction;

for stations joining three or more sectionsAt this time->Is fork typeThe station calculates the number of the initial trains and the number of the final trains required to be started according to the total initial passenger flow and the total final passenger flow of the station, and then calculates the station ∈>From interval->After arriving at the station, the station is further divided into sections->The number of passing trains leaving, simultaneously ensuring that the end-to-end passenger flow volume of the former section is equal to the original passenger flow volume of the latter section when the passing trains serve two sections, and finally determining the station- >Whether it is a candidate originating station or a candidate terminating station.

4. A method for optimizing the running path of a high-speed railway train based on the distribution of passenger flows according to claim 3, wherein for stations joining three or more sectionsDetermining the number of originating trains and the number of terminating trains required to be organized and running, and determining the station ∈ ->Whether it is a candidate originating station or a candidate terminating station specifically includes:

calculating the number of initial trains and the number of final trains required to be started at a station:

wherein ,representing site->The total number of trains that need to be organized for the originating passenger flow trip, < >>Representing site->The total number of trains required to be organized for the final passenger flow trip, including final and passing trains, +>For train-officer->Minimum originating boarding rate required for a station organization to start an originating train;

constructing a linear programming model:

wherein ,for a set of all intervals, constraints of the linear programming model include:

1) Menstrual intervalAll passenger carrying capacities provided by trains arriving and departing from other sections are not higher than the section +.>Is the final passenger flow volume of (1), i.e

wherein ,for interval->Is the final passenger flow volume;

2) Arriving via other intervals and arriving from intervalsAll passenger carrying capacity offered by the train at departure is not higher than the slave section +. >Originating passenger traffic, i.e

wherein ,for +.>Originating passenger traffic;

calculating the number of initial trains and the number of final trains required to be organized by solving a linear programming model:

wherein ,and->Respectively represent site->The number of initial trains and the number of final trains which are started are organized, and when the number is decimal, the number is an integer.

5. The high-speed railway train running path optimization method based on path allocation passenger flow as claimed in claim 1, wherein the step S3 comprises:

s301: initializing a set of train candidate paths；

S302: for any candidate originator-zoneCirculating to select +.>Passenger flow travel route as origin +.>If->Terminal interval-station belonging to the group->The passenger flow travel path is +.>Add to the collection->The method comprises the steps of carrying out a first treatment on the surface of the Otherwise, from->The terminal section of (a) station starts to find the nearest one belonging to the set +.>To add this route to +.>Wherein the candidate originator-zone represents a candidate to zone,/>Representing a set of candidate starting station to station, terminal station to station,/>Representing a set of candidate intervals to the end station;

S303: deleting the repeated paths contained in the obtained train candidate path set, and taking the reserved paths as train candidate running paths;

s304: and judging whether the conditions of the originating and terminating train equipment are met or not for the candidate originating station and the candidate terminating station in the train candidate starting path, and deleting the candidate originating station or the candidate terminating station if the conditions are not met.

6. The high-speed railway train operation path optimization method based on path allocation passenger flow as claimed in claim 1, wherein the step S4 comprises:

s401: selecting the number of running trains organized by the candidate running paths of each high-speed rail train as a model decision variable；

S402: selecting a model optimization target, and constructing a high-speed train candidate path running number optimization model:

wherein the first partFor the total operation mileage of the running train +.>Represents the average cost per kilometer of train operation, +.>For the path->Is a running mileage of (1); second part->Organizing costs for running trains, < >>The constraint conditions for representing the average cost for organizing a train and the optimization model of the running number of the candidate paths of the high-speed rail train comprise:

constraint 1:

wherein ,representing the path->A person on the train to drive, +.>Representing the path- >And section->If the association relation of (1) is interval->Belonging to the path->Then->The method comprises the steps of carrying out a first treatment on the surface of the Otherwise, go (L)>，/>For interval->Is a total trip amount of the vehicle;

constraint 2:

wherein ,for the line interval->Maximum number of trains running in the whole day operating time range,/-for>For driving trainsPath->And line interval->If the line interval is +.>Belongs to the train driving path->1 if not, otherwise 0;

constraint 3:

(1) for non-cross point stations that join only one or two line intervals:

wherein ,、/>the starting interval and the ending interval of the path p;

(2) for a fork station that joins more than two line intervals:

from fork point stationThe number of the starting trains through each connection interval meets the following conditions:

terminating to fork station via each connection intervalThe number of final trains satisfies:

wherein ,for a given number of floating trains, < > a->And->Separate list site->It is necessary to organize the number of originating trains and the number of terminating trains that are in progress.

7. The high-speed railway train operation path optimization method based on path allocation passenger flow as claimed in claim 1, wherein the step S5 comprises:

s501: constructing a solution code of a candidate path starting train number scheme, wherein the code length is the number of candidate paths, each bit code corresponds to one candidate path, the codes are expressed by non-negative integers, and when a certain bit code is 0, the corresponding candidate path does not organize the starting train; otherwise, organizing and running trains with corresponding integer numbers;

S502: random generation according to designed coding schemeIndividual initial individuals added to the initial population +.>In which, if an unsatisfactory individual is produced, the individual is discarded from the re-random generation until +.>A plurality of initial individuals;

s503: selection operation: computing populationFitness of all individuals>Sequencing from big to small according to fitness, and calculating the individual +.>Selection probability of +.>And cumulative probability->As the probability that each individual in the population is selected into the next generation population:

randomly generating a random numberAnd select to satisfy->Is->Repeating this until the selection is obtainedIndividual individuals are used as individuals of the next generation population; wherein (1)>For individuals->，/>For individuals->Is adaptive to->Representing the sub-population->Selecting the fitness of the individual with the greatest fitness +.>For individuals->Is selected according to the selection probability of (1);

s504: crossover operation: randomly generating a random numberIf it is smaller than the set crossover probability +.>Then select two chromosomes +.>And->And (3) crossing:

wherein ,random numbers, 0-1 for +.>, />Is chromosome->And->Crossing offspring chromosomes;

s505: mutation operation: randomly generating a random numberIf it is smaller than the set mutation probability +. >Randomly selecting the +.>The individual genes are used as mutation sites, and new gene values are randomly generated to replace the original gene values;

s506: returning to S503 for selection operation, cross operation and variation operation, if the population keeps the optimal value continuous generation unchanged or reaches the maximum iteration number, stopping the algorithm, and returning to the optimal chromosome; otherwise, the algorithm continues iterative optimization, wherein the optimal chromosome is the optimal solution of the genetic algorithm, the length of the chromosome is the number of candidate paths, and each bit code corresponds to one candidate path.

8. High-speed railway train running path optimizing device based on route distribution passenger flow, characterized by comprising:

the high-speed railway travel path passenger flow distribution calculation module is used for calculating high-speed railway travel path passenger flow distribution based on the distribution passenger flow of each travel path on a given high-speed railway network, wherein the high-speed railway travel path passenger flow distribution comprises the passing passenger flow, the ending passenger flow and the starting passenger flow in each section direction of each high-speed railway line;

the candidate starting station and final destination station determining module is used for determining candidate starting stations and candidate final destination stations for starting the high-speed rail train according to the calculated passenger flow volume distribution of the high-speed rail travel path and whether the section has the conditions of starting and final destination train equipment;

The high-speed rail train candidate starting path determining module is used for combining the calculated passenger flow volume distribution of the high-speed rail travel path, and selecting a path between the candidate starting station and the candidate final destination station determined in the step S2 as a high-speed rail train candidate starting path;

the high-speed railway train candidate path running number optimizing model construction module is used for constructing a high-speed railway train candidate path running number optimizing model by taking running number of each high-speed railway train candidate running path organization as a decision variable, taking the minimum running cost of the high-speed railway train as an optimizing target and taking interval running train capacity limit and passenger flow conveying capacity limit as constraint conditions;

the model solving module is used for designing a decoding code of a train candidate path running number scheme, designing an operation strategy of selection, intersection and variation, and adopting a genetic algorithm to solve a high-speed railway train candidate path running number optimizing model to obtain an optimal solution, wherein the code of a chromosome corresponding to the optimal solution is a high-speed railway train running path, and the length of the chromosome is the running train number.

9. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when executed, implements the method according to any one of claims 1 to 7.

10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any of claims 1 to 7 when the program is executed by the processor.