CN110751453B - Method and system for identifying and resolving capacity bottleneck of railway channel - Google Patents
Method and system for identifying and resolving capacity bottleneck of railway channel Download PDFInfo
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Abstract
The invention provides a method for identifying and resolving the bottleneck of railway channel capacity, which adopts a mode of combining model construction and simulation, realizes bottleneck identification and resolution by utilizing big data, indicates the optimization direction of a simulation model by solving the mathematical model, and further overcomes the defect of insufficient refinement degree of a solution scheme solved by the mathematical model through a simulation experiment.
Description
Technical Field
The invention relates to the field of railway transportation organization, in particular to a method and a system for identifying and resolving railway channel capacity bottlenecks.
Background
The utilization of the transportation capacity of the railway channel has the characteristic of dynamic and instantaneous behavior, and the dispatching cannot be carried out, and the system is ineffective in time. The direct influence brought by the unreasonable utilization of the channel capacity is a bottleneck effect, so that a certain point or section in a line becomes a weak link of a road network, the overall capacity and the operation level of the channel are limited, and the passenger and freight demand of certain stations in the road network cannot be honored.
The transport capacity is the sum of the maximum transport volume which can be completed by the railway system by fully utilizing the prior art equipment under the given equipment condition and personnel condition in unit time. The railway transportation capacity depends not only on the arrangement number and mutual configuration structure of the fixed equipment, but also on the space-time configuration of the movable equipment, and also on the mutual adaptation of the fixed equipment and the movable equipment, including two concepts of passing capacity and conveying capacity.
The transportation capacity bottleneck refers to that the transit capacities calculated according to fixed equipment such as an interval, a station, a locomotive, water supply and power supply equipment and the like are possibly different, wherein the equipment with the weakest capacity limits the capacity of the whole section, and the capacity is the final transit capacity of the section. Not only by capacity, but also in the entire transport system, the weakest link in transport capacity always has a decisive limiting effect on transport capacity or a so-called "bottleneck" effect. On the railway trunk line with important transportation status, the utilization of the passing capacity of the transportation restriction position or the bottleneck section is often the key for ensuring smooth transportation and relating to global transportation. In these parts or sections, the balanced transportation needs to be carefully organized through careful planning and planning, and on the premise of ensuring a certain transportation quality requirement, the transportation fluctuation is reduced as much as possible, and the passing capacity is used to the maximum extent.
Therefore, comprehensive consideration of bottleneck identification and resolution is an important way for railway transportation capacity utilization and enhancement when a railway transportation capacity utilization scheme is prepared. However, the defects of the bottleneck identification and resolution technology of the existing railway channel capacity utilization optimization are mainly reflected in two aspects: (1) in the prior art, in order to solve the bottleneck identification and resolution problem, a mathematical model or a simulation method is generally adopted to carry out alone, while a pure mathematical model is difficult to express the constraint conditions of the complex train operation organization process in reality, the refinement degree of the scheme is deficient, and a single simulation model without mathematical model solution guide lacks the target directivity and is deficient in the solution efficiency; (2) the system research of bottleneck identification and elimination is lacked, the prior art generally proposes a 'resolution' scheme after identifying the 'bottleneck', but the 'resolution' scheme has less correlation research with the 'bottleneck' which can be caused newly.
Disclosure of Invention
The embodiment of the invention provides a method and a system for identifying and resolving a railway channel capacity bottleneck, which are used for solving the technical problem that a bottleneck resolving scheme in the prior art is difficult to reflect the real situation of railway transportation production, so that a result with higher feasibility and practical use value cannot be obtained.
In order to achieve the purpose, the invention adopts the following technical scheme.
A method for railroad track capacity bottleneck identification and resolution, comprising:
acquiring basic data, preprocessing the basic data, and analyzing and identifying the preprocessed basic data to obtain bottleneck point parameters;
establishing a mathematical model based on the bottleneck point parameters to obtain a channel capacity alternative operation scheme set;
carrying out simulation operation on the channel capacity alternative operation scheme set;
adjusting a channel capacity alternative operation scheme set based on the result of the simulation operation to obtain an optimal operation scheme;
and comparing and analyzing the optimal operation scheme with the actual operation data, and obtaining a railway channel capacity bottleneck identification and resolution scheme according to the comparison and analysis result.
Preferably, the acquiring and preprocessing the basic data comprises:
calibrating missing values in the basic data;
processing outliers in the underlying data;
and completing and converting the basic data, and inputting the basic data into an application subsystem for analyzing and identifying the preprocessed basic data.
Preferably, the application subsystem comprises:
the data layer is used for the connection management of the database;
the logic layer is used for storing and reading the preprocessed basic data and performing operation processing on the preprocessed basic data;
and the interaction layer is used for displaying the operation processing result of the output logic layer.
Preferably, the performing, by the logic layer, operation processing on the preprocessed basic data includes:
formula is calculated by average minimum interval time method
Calculating to obtain a train theoretical interval passing capacity value, wherein N is the interval passing capacity, T is the effective interval passing time,
is flatAre all separated by a minimum time interval,
the necessary average buffer time;
and comparing the actual train passing number of the interval with the theoretical interval passing capacity of the train to obtain the capacity utilization rate of the interval.
Preferably, the interaction layer displays and outputs the capacity utilization rate of the interval through capacity utilization thermodynamic diagrams.
Preferably, establishing a mathematical model based on the bottleneck point parameters, and obtaining the channel capacity alternative operation scheme set comprises:
establishing a mathematical model by taking the maximum traffic on the line as a target I
Wherein z is 1 Is an objective function;
establishing a mathematical model by taking the minimum change of a train organization scheme as a target II
Wherein z is 2 Is an objective function;
for the target function z 1 And z 2 Normalization is carried out, and a mathematical model Max z is obtained through conversion 3 ＝λ 1 z 1 -λ 2 z 2 Wherein λ is 1 、λ 2 The weight coefficients between the targets I, II, respectively.
Preferably, the simulation operation on the channel capability alternative operation scheme set comprises the following sub-steps:
initializing a simulation target state;
running a simulation clock;
when the next event moment becomes the current event moment, judging whether the real-time state of the simulation target meets a preset execution condition, if so, executing the simulation event of the real-time state of the simulation target, and if not, repeatedly executing the sub-step;
judging whether the real-time state of the simulation target after the execution of the simulation event meets the simulation end condition, if so, outputting a simulation operation result and ending the simulation operation, and if not, returning to the third substep.
Preferably, the simulation target state includes a train state, a line operation state, and a locomotive state.
In a second aspect, the present invention provides a system for identifying and resolving a capability bottleneck of a railroad channel, comprising:
the data processing and analyzing subsystem is used for acquiring basic data and preprocessing the basic data to acquire bottleneck point parameters;
the model analysis subsystem is used for establishing a mathematical model based on the bottleneck point parameters to obtain a channel capacity alternative operation scheme set;
the simulation analysis subsystem is used for carrying out simulation operation on the channel capacity alternative operation scheme set; adjusting a channel capacity alternative operation scheme set based on the simulation operation result to obtain an optimal operation scheme; and comparing and analyzing the optimal operation scheme with the actual operation data, and obtaining a railway channel capacity bottleneck identification and resolution scheme according to the comparison and analysis result.
Preferably, the data processing and analyzing subsystem comprises an application subsystem, and the data processing and analyzing subsystem is further configured to:
calibrating missing values in the basic data;
processing outliers in the underlying data;
and completing and converting the basic data, and recording the basic data into the application subsystem.
According to the technical scheme provided by the embodiment of the invention, the method and the system for identifying and resolving the bottleneck of the railway channel capacity adopt a mode of combining model construction and simulation, realize the identification and resolution of the bottleneck by means of a big data analysis technology, indicate the optimization direction of a simulation model by solving a mathematical model, and further overcome the defect of insufficient refinement degree of the solution of the mathematical model by a simulation experiment.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a logic diagram of a method for identifying and resolving a railway channel capacity bottleneck according to the present invention;
FIG. 2 is a flowchart of an embodiment of a method for identifying and resolving a bottleneck of a railway access capacity according to the present invention;
FIG. 3 is a logic diagram of data analysis and processing of a method for identifying and resolving a bottleneck of railway access capability according to the present invention;
FIG. 4 is a first capability utilization thermodynamic diagram of a method for identifying and resolving a capability bottleneck of a railroad track according to the present invention;
FIG. 5 is a second capability utilization thermodynamic diagram of a method for identifying and resolving a bottleneck of a railroad channel capability provided by the present invention;
FIG. 6 is a schematic diagram of a train operation simulation of a method for identifying and resolving a railway channel capacity bottleneck provided by the invention;
FIG. 7 is a flowchart of an embodiment of simulation operations of a method for identifying and resolving a bottleneck of a railway channel capability according to the present invention;
FIG. 8 is a flow chart of a main program for simulating station operation of the method for identifying and resolving the bottleneck of railway passage capacity provided by the invention;
fig. 9 is a flow chart of a station-stopping through train operation simulation program of the method for identifying and resolving the railway passage capacity bottleneck provided by the invention;
FIG. 10 is a logic block diagram of a system for railroad channel capability bottleneck identification and resolution provided by the present invention;
FIG. 11 is a block flow diagram of a system for identification and resolution of a railroad access capability bottleneck according to the present invention;
fig. 12 is a schematic diagram of a visual output mode of a simulation analysis subsystem of the system for identifying and resolving the railway channel capacity bottleneck provided by the invention.
In the figure:
101. the data processing and analyzing subsystem 1011, the application subsystem 102, the model analyzing subsystem 103 and the simulation analyzing subsystem.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or coupled. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
For the convenience of understanding of the embodiments of the present invention, the following detailed description will be given by way of example with reference to the accompanying drawings, and the embodiments are not limited to the embodiments of the present invention.
Referring to fig. 1 and 2, the method for identifying and resolving the railway channel capacity bottleneck provided by the invention comprises the following steps:
acquiring basic data, preprocessing the basic data, and analyzing and identifying the preprocessed basic data to obtain bottleneck point parameters;
establishing a mathematical model based on the bottleneck point parameters, and solving the model to obtain a channel capacity alternative operation scheme set;
carrying out simulation operation on the channel capacity alternative operation scheme set, and outputting a result of the simulation operation;
adjusting a channel capacity alternative operation scheme set based on the simulation operation result to obtain an optimal operation scheme;
and comparing and analyzing the optimal operation scheme with the actual operation data, and comprehensively evaluating the advantages and disadvantages of the scheme according to the comparison and analysis result, so that the transportation capacity of the railway channel is fully excavated, the capacity bottleneck identification and resolution scheme of the railway channel is obtained, and the target of capacity utilization coordination and optimization is realized.
According to the method for identifying and resolving the bottleneck of the railway channel capacity, the bottleneck is identified and resolved by using big data in a mode of combining model construction and simulation, the direction of simulation model optimization is indicated by mathematical model solution, and the defect of insufficient refinement degree of a solution scheme of the mathematical model is further overcome by a simulation experiment.
Further, in some preferred embodiments, the data source of the basic data is to obtain the basic data from the TDCS data and the station operation data. The TDCS data is: the railway train dispatching and commanding system consists of information processing technology, intelligent software, network technology and modern computer technology, and is named TDCS for short. The TDCS system stores the core transportation scheduling command data in a Database (DB). In practical application, the TDCS application server, the dispatching station subsystem and the like are connected with the database, receive the dispatching data of the traveling crane in real time, format, process and recombine the data and store the data in the core database. Meanwhile, each query server and each terminal can query current data and historical information by connecting the query servers and the terminals with the database. Therefore, the TDCS accumulates a large amount of train operation data, and the data is large in scale, real and reliable and contains rich decision support information. The TDCS data is used for capacity utilization analysis, so that the method has the characteristics of accuracy and real time, and can dynamically reflect the capacity utilization conditions of special sections and special periods. By providing the capacity utilization analysis method based on TDCS data, the capacity utilization condition of the line is scientifically mastered, and a basis is provided for further planning decision and exploiting potential energy expansion.
After the basic data are obtained, importing the basic data into a database for preprocessing, wherein in the embodiments, the database can be an Oracle database; as shown in fig. 3, the way of preprocessing the basic data includes:
calibrating missing values in the basic data;
processing abnormal values in the basic data, wherein the processing process comprises identification, screening and the like;
and completing and converting the basic data, and inputting the basic data into an application subsystem for analyzing and identifying the preprocessed basic data.
Further, as shown in fig. 2 and 3, the application subsystem includes three levels:
the data layer is used for performing connection management on a database for preprocessing basic data;
the logic layer is used for storing and reading the preprocessed basic data and performing operation processing on the preprocessed basic data; the storage, reading and operation processes are not in sequence;
and the interaction layer is used for displaying and outputting the operation processing result of the logic layer.
In the embodiment provided by the invention, the analysis and identification of the preprocessed basic data comprise analysis, operation and identification; as an application example, the logic layer performing operation processing on the preprocessed basic data includes the following sub-steps:
formula is calculated by average minimum interval time method
Calculating to obtain a passing capacity value of a train theoretical interval;
wherein N is the interval passing capacity, T is the effective interval passing time,
in order to average out the minimum interval time,
the necessary average buffer time;
comparing the actual train passing number of the section with the train theoretical section passing capacity to obtain the capacity utilization rate of the section;
the capacity utilization rate is an important index for evaluating the bottleneck position of the railway channel, through mass data analysis, capacity utilization thermodynamic diagrams of all sections can be further made through an interaction layer and output, and corresponding bottleneck point parameters such as the bottleneck position and the like can be obtained through analysis of the thermodynamic diagrams.
Taking the national energy group covered with the god railway line as an example, the operation data on the line is analyzed by using the analysis framework, and the capacity utilization rate of each section is shown in fig. 4 and 5, and a section with insufficient transportation capacity can be easily seen from the figure. The required parameters and the capability bottleneck are obtained by integrating data processing analysis and combining the bottleneck identification technology, thereby laying the bottleneck resolution foundation.
It will be understood by those skilled in the art that the above-described arrangement of application subsystems is merely exemplary, and that other types of data analysis and computation applications that are currently available or that may later become available for performing the same function, such as those that may be used with embodiments of the present invention, are also intended to be included within the scope of the present invention and are hereby incorporated by reference.
In the embodiment provided by the invention, the channel capacity alternative operation scheme set is obtained as an important component under the technical framework system of the invention, and is of great importance in the aspect of generating the initial feasible scheme, so that the defect of the single simulation method lacking of directivity of the optimized direction is avoided. In the embodiment provided by the invention, the channel capacity alternative job scheme set is preferably generated by changing the weight proportion system and the important capacity parameter of the multi-objective function.
The applicant discovers that, through analyzing the mode of the railway transportation organization, the mode of the freight transportation organization is greatly different from the mode of the passenger transportation organization, so that mathematical planning models need to be respectively established according to the respective characteristics, but the model can be generalized to a type of network flow multi-target planning model with constraints no matter the freight transportation model or the passenger transportation model. In some preferred embodiments, dual targets are used to model:
taking the maximum traffic on the line as a target I (the traffic of freight is freight tonnage, and the traffic of passenger is transport passenger volume), establishing a mathematical model
Wherein z is 1 In order to be the objective function of the target,
standard load for small and medium sized rows of heavy haul railwaysVolume, wherein L is a set of loading stations, U is a set of unloading stations, K is a set of types of empty and heavy trains, 0 represents 5000 tons of trains, 1 represents 10000 tons of trains, T is a time interval dividing a day, and theta is equal to T = {1,2,3,4},
m represents the number of heavy trains of type k which are driven between i → j during the time period theta k The number of small marshalling columns for the empty and heavy train type K, where K is equal to K, m 0 ＝1,m 1 ＝2；
Because the cost of changing the current transportation organization mode on the line is higher globally, the invention does not optimize the transportation organization globally, but optimizes the current transportation organization mode locally under the condition of small difference with the real scheme as much as possible, thus taking the train transportation scheme with the largest similarity with the weekday, namely taking the minimum change of the train organization scheme as the target II, establishing a mathematical model
Wherein z is 2 The scheme has the minimum variation as an objective function, which can be understood as that the traffic loss cost is minimum after the train scheme is changed, and the cost coefficient is at the moment
Corresponding modifications are required to the unit of ten thousand tons,
the method is characterized in that the standard loading capacity of a small train in a heavy haul railway, L is a loading station set, U is an unloading station set, K is an empty and heavy train type set, 0 represents a 5000-ton train, 1 represents a 10000-ton train, T is a time interval dividing one day, theta belongs to T = {1,2,3,4},
represents the number of heavy trains of type k that are driven between i → j during the time period theta,
indicating that the period θ is spaced between i → jThe number of empty trains of the row k type,
represents the number of empty-weight trains driven by the original scheme i → j, m k Small marshalling column number of type K for empty and heavy train, where K is equal to K, m 0 ＝1,m 1 ＝2；
In the embodiment, the solver for solving the model is preferably a Lingo solver, but the Lingo solver cannot solve a multi-objective function, so that the objective function z is solved 1 And z 2 Normalizing, converting the multiple objective functions to obtain a mathematical model Max z of a single objective function by using the weight coefficient 3 ＝λ 1 z 1 -λ 2 z 2 Wherein λ is 1 、λ 2 The weight coefficients between the targets I and II are respectively, and the specific numerical values can be comprehensively determined according to the actual situation of the site by considering the bias between different targets. The alternative operation scheme set for obtaining the channel capacity obtained by solving the mathematical model mainly meets the following three types of constraints: network flow balance constraint; capacity maximum constraint; supply and demand balance constraints. On the basis of the established mathematical programming model, the weight coefficient lambda of the objective function is changed 1 、λ 2 And required capability parameter
(station capability constraint) and N ij (Interval capability constraints) the generation of the alternative set can be achieved. The final transportation scheme also needs to be further determined through simulated selection and feedback adjustment.
The applicant finds that the newly generated scheme is deficient in refinement degree, only the static bottleneck under the current capacity parameter condition is cleared up, and in reality, due to the complexity and changeability of the transportation organization process, the position of the bottleneck can be dynamically transferred along with the change of the transportation organization scheme along with the time, so that various complex constraints between stations need to be further refined through simulation experiments, continuous iterative optimization and feedback adjustment are carried out, and the comprehensive clearing up of the bottleneck is realized, so that the train running scheme for capacity coordination and utilization between stations is obtained.
The train operation process is that the path activity and control deduction of mobile equipment in the time-space domain of fixed facility equipment such as a road network, signals, a station route and the like are combined according to a train operation plan, and the simulation process is that the time and the place of occurrence of related elements are judged by tracking the train activity, so that the dynamic description of the train operation is realized. Therefore, the basis of the train operation organization simulation is necessarily the operation activity of the train, and the train operation is the foundation stone of the train operation organization simulation and is also the core of the capability utilization simulation. Fig. 6 shows the principle of the train operation process.
Based on the principle, the basic logic of the simulation operation is to import the line station information, the train basic attribute information, the station technical operation time and the scheme data, establish a data interface of external data and a simulation system, and realize the reading and writing of the data. The method is characterized in that a discrete event logic diagram of station operation is abstractly constructed and combined with programming language (such as java) for secondary development, so that dynamic tracking of a train, printout of corresponding information of the train, selection of a path and avoidance of conflict and output of related statistical data are realized.
In some preferred embodiments, the implementation process is that the simulation operation on the channel capability alternative operation scheme set includes the following sub-steps:
initializing a simulation target state;
running a simulation clock, which may be preset;
when the next event moment becomes the current event moment, judging whether the real-time state of the simulation target meets a preset execution condition, if so, executing the simulation event of the real-time state of the simulation target, and if not, repeatedly executing the sub-step;
and judging whether the real-time state of the simulation target after the execution of the simulation event meets the simulation ending condition, if so, outputting the simulation operation result and ending the simulation operation, and if not, returning to the third substep.
In the specific implementation process, the setting basis of the event is as follows: considering that the operation and operation organization of the train between the stations belongs to discrete events, a simulation system of a railway channel can be defined by using a discrete event system, and the discrete event system generally comprises entities, attributes, events, activities, processes, states and the like.
Further taking a discrete event as a starting point of the scheme feasibility simulation system, firstly establishing a calculation model for tracking operation of the multiple trains, and then establishing a simulation model by adopting an object-oriented programming language (such as java) to complete modeling of basic information such as a railway network and train operation attributes. The discrete events are abstracted into a computer system, the simulation level is microscopic simulation, the operation of the system is promoted by adopting an event step method, and the simulation strategy adopts a process interaction method.
As an exemplary embodiment of the simulation operation, as shown in fig. 7, the method includes the following steps:
issuing an instruction for starting simulation to the system, and starting simulation operation by the system;
setting the time proportion of the simulation clock and carrying out corresponding control to ensure that the simulation clock advances step by step according to the defined time proportion;
initializing real-time (current) states at the beginning of the simulation, in this example, real-time states including train real-time state, line real-time use state, locomotive real-time state;
with the forward advance of the simulation clock, when the current event time becomes the current event time, the event becomes an event qualified for execution at the current time point, on the basis, the system judges whether the real-time state of the simulation target meets the preset execution condition, namely whether the next event occurs, for example, a certain station performs departure operation, and when no feasible departure path exists, the train needs to wait for an idle path on a station track to trigger the departure operation; when the next event is triggered, the next state of the system needs to be updated, the next state of the train and the locomotive is recorded, and a traveling path is arranged for the train;
and after the event is executed, judging whether the real-time state of the simulation target meets the simulation ending condition by the system, wherein the ending condition can be set as the total simulation duration or the simulation experiment is ended according to the condition that a specific index is met, and if the ending condition is not met, continuously judging whether the real-time state of the simulation target meets the preset execution condition.
In a further detailed example, the description is made of a process in which a train is simulated in a computer system during the operation process of a station, and fig. 8 shows a main program flow chart of the simulation of the operation process of the station. The technical workflow of various trains at the station is abstracted into the logical relationship of discrete events, and the technical workflow of the trains at the station has both commonality and characteristics, and the workflow of the trains passing by the station is shown as a figure 9 (the following English names are all self-writing function names involved in the programming):
step1: and judging whether the station track can be occupied according to a station track selection table or function (Select _ fixedline) and the occupation state (line _ state, present _ time) of each station track.
Step2: whether the access is available is judged according to an access selection table or function (Select _ shortestpath _ arriveroute) and the access of each station and the occupation state (route _ state, present _ time)) of the corresponding enemy access. If not, performing Step3; if yes, step4 is performed.
Step3: judging whether all available tracks of the train event traverse, if so, delaying arrival of the train, and performing next train operation; if not, the traversed track is listed as the optional track, and the Step1 is returned.
Step4: determining the train entering route and the train stopping station track, calculating the departure time according to the stop time, changing the attributes of the route and the track into occupied ones, and changing the attributes of the route and the track until the estimated departure time of the train (after the operation is finished, the attributes of the train are changed, and the conditions are automatically changed into the train at the station according to the attributes of the train at the station).
The above are implementation processes of a simulation model, and during a simulation experiment, in an actual train running process, actual passing capacity of stations and sections is related to train running organization in the time period, so that passing capacity parameters of stations and sections set as fixed values are unreasonable, and various complex constraints of the stations and sections need to be further considered in a refined manner through a feedback adjustment experiment of the simulation. By analyzing the capability utilization condition among stations after simulation experiment, train delay condition after random interference, various speed indexes and the like to feed back and adjust the interval and station passing capability parameters and iteratively optimize the model parameters, the generated scheme can meet the practical requirements, so that the start-to-end point, the line-to-line running proportion and the running frequency of each time interval and the like of the train are reasonably arranged, and the aim of balanced and reasonable utilization of the capability among the intervals of each station is fulfilled.
It should be understood by those skilled in the art that the simulation calculation and programming examples are only for better illustrating the technical solutions of the embodiments of the present invention, and are not to be construed as limiting the embodiments of the present invention. Any method of determining a simulation based on the same bottleneck resolution principle is included within the scope of embodiments of the present invention.
The railroad track capacity utilization transportation scheme generated by the present embodiment is a targeted adjustment scheme with minimal differences from existing transportation schemes. The simulation system compares a newly generated transportation scheme with an actual operation diagram of a certain day as a basis, increases and decreases train operation lines on the existing transportation scheme, simulates the existing transportation scheme, finds out key factors influencing the bottleneck after simulation, adjusts the operation diagram and modifies the key trains influencing the bottleneck. Under the existing frame, increase the train according to the demand, relate to newly-increased operation line shop drawing and existing operation line adjustment. In the transportation peak period, the train operation diagram is compressed as much as possible, the adjustability of an ideal starting moment and an ideal starting moment of the newly added train is given, the operation line is paved and drawn to be the shortest path problem, a solving algorithm is embedded into a simulation model, and paving and drawing of the newly added train operation line can be realized under the condition that constraint conditions such as station intervals, occupied uniqueness and the like are met, so that simulation of a transportation scheme is realized.
In a second aspect, the present invention provides a system for performing the method described above, as shown in fig. 10 and 11, comprising:
the data processing and analyzing subsystem 101 is used for acquiring and preprocessing basic data, analyzing and identifying the preprocessed basic data and acquiring bottleneck point parameters;
the model analysis subsystem 102 is in communication connection with the data processing and analysis subsystem 101 and is used for establishing a mathematical model based on the bottleneck point parameters and obtaining a channel capacity alternative operation scheme set;
the simulation analysis subsystem 103 is in communication connection with the data processing analysis subsystem 101 and the model analysis subsystem 102 respectively, and is used for performing simulation operation on the channel capacity alternative operation scheme set; adjusting a channel capacity alternative operation scheme set based on the result of the simulation operation to obtain an optimal operation scheme; the optimal operation scheme is compared and analyzed with actual operation data, and the advantages and disadvantages of the scheme are comprehensively evaluated according to the comparison and analysis result, so that the transportation capacity of the railway channel is fully excavated, the capacity bottleneck identification and resolution scheme of the railway channel is obtained, and the target of capacity utilization coordination and optimization is realized;
in this embodiment, the simulation analysis subsystem 103 is further configured to output visually the working processes of the data processing and analysis subsystem 101 and the model analysis subsystem 102, and the simulation analysis processes and results, where the manner of visually outputting may be according to the prior art, for example, including data display, text table, chart (graph, histogram, etc.), and the like illustrated in fig. 12.
Further, in some preferred embodiments, the data processing and analysis subsystem 101 includes an application subsystem 1011, and the data processing and analysis subsystem 101 is further configured to:
calibrating missing values in the basic data;
processing outliers in the underlying data;
the basic data is supplemented and converted, and is input into the application subsystem 1011 for analyzing and identifying the preprocessed basic data.
Further, the application subsystem 1011 includes:
the data layer is used for the connection management of the database;
the logic layer is used for storing and reading the preprocessed basic data and performing operation processing on the preprocessed basic data;
and the interaction layer is used for displaying and outputting the operation processing result of the logic layer.
Further, in some preferred embodiments, model parsing subsystem 102 can implement:
establishing a mathematical model by taking the maximum traffic on the line as a target I
Wherein z is 1 Is an objective function;
establishing a mathematical model by taking the minimum change of a train organization scheme as a target II
Wherein z is 2 Is an objective function;
for the objective function z 1 And z 2 Normalization is carried out, and a mathematical model Max z is obtained through conversion 3 ＝λ 1 z 1 -λ 2 z 2 Wherein λ is 1 、λ 2 The weight coefficients between the targets I, II, respectively.
Further, in some preferred embodiments, the simulation analysis subsystem 103 can further implement:
initializing a simulation target state;
running a simulation clock;
when the next event moment becomes the current event moment, judging whether the real-time state of the simulation target meets a preset execution condition, if so, executing the simulation event of the real-time state of the simulation target, and if not, repeatedly executing the sub-step;
judging whether the real-time state of the simulation target after the execution of the simulation event meets the simulation end condition, if so, outputting a simulation operation result and ending the simulation operation, and if not, returning to the third substep.
In summary, the method and the system for identifying and resolving the railway channel capacity bottleneck provided by the invention have the following advantages:
(1) The dynamic evolution rule of the bottleneck can be mastered without being limited to static bottleneck resolution, so that the correctness of the result and the effectiveness of a resolution scheme are ensured;
(2) The parameters of the channel capacity alternative scheme set generation model are established on the basis of a large amount of historical operation data analysis, and the final scheme meets the practical requirement better;
(3) The scheme is refined, true and reliable, the solving efficiency is high, the balanced utilization and the coordinated optimization of the capacity are realized, and a new solution idea and technology are provided for solving the problem of the utilization of the channel capacity;
(4) The simulation and the output of the data acquisition, analysis, identification, processing and bottleneck resolution schemes are integrated in a system, so that intermediate links are reduced, and the data accuracy is high;
(5) The method can be applied to enterprises of current coal transportation heavy-load transportation channels or popularized and applied to main trunk channel networks of railways, and a complete scheme is provided for optimizing the utilization of railway channel capacity.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.
Claims (9)
1. A method for identifying and resolving a railway access capability bottleneck, comprising:
acquiring basic data, preprocessing the basic data, analyzing and identifying the preprocessed basic data to obtain bottleneck point parameters;
establishing a mathematical model based on the bottleneck point parameters to obtain a channel capacity alternative operation scheme set; the method specifically comprises the following steps:
establishing a mathematical model by taking the maximum traffic on the line as a target I
Wherein z is 1 In order to be the objective function, the target function,
the method is characterized in that the standard load capacity of a small train in a heavy haul railway is represented, L is a loading station set, U is an unloading station set, K is an empty and heavy train type set, T is a time interval division performed on one day, and theta belongs to T = {1,2,3,4},
m represents the number of heavy trains of type k which are driven between i → j during the time period theta k Small marshalling column number of type K for empty and heavy train, where K is equal to K, m 0 ＝1,m 1 ＝2；
Establishing a mathematical model by taking the minimum change of a train organization scheme as a target II
Wherein z is 2 In order to be the objective function, the target function,
and
respectively representing cost coefficients;
representing the number of empty trains of type k which are driven between i → j in the time interval theta;
representing the number of empty and heavy trains driven by the original scheme i → j;
for the target function z 1 And z 2 Normalization is carried out, and a mathematical model Max z is obtained through conversion 3 ＝λ 1 z 1 -λ 2 z 2 Wherein λ is 1 、λ 2 Respectively is the weight coefficient between the targets I and II;
carrying out simulation operation on the channel capacity alternative operation scheme set;
adjusting a channel capacity alternative operation scheme set based on the simulation operation result to obtain an optimal operation scheme;
and comparing and analyzing the optimal operation scheme with the actual operation data, and obtaining a railway channel capacity bottleneck identification and resolution scheme according to the result of the comparison and analysis.
2. The method of claim 1, wherein the obtaining and preprocessing the base data comprises:
calibrating missing values in the basic data;
processing outliers in the underlying data;
and completing and converting the basic data, and inputting the basic data into an application subsystem for analyzing and identifying the preprocessed basic data.
3. The method of claim 2, wherein the application subsystem comprises:
the data layer is used for the connection management of the database;
the logic layer is used for storing and reading the preprocessed basic data and performing operation processing on the preprocessed basic data;
and the interaction layer is used for displaying and outputting the operation processing result of the logic layer.
4. The method of claim 3, wherein the logic layer performing operation processing on the preprocessed base data comprises:
formula is calculated by average minimum interval time method
Calculating to obtain a train theoretical interval passing capacity value, wherein N is the interval passing capacity, T is the effective interval passing time,
in order to average the minimum interval time,
the necessary average buffer time;
and comparing the actual train passing number of the interval with the theoretical interval passing capacity of the train to obtain the capacity utilization rate of the interval.
5. The method of claim 4, further comprising displaying and outputting the capacity utilization rate of the interval by the interaction layer through capacity utilization thermodynamic diagrams.
6. The method of claim 1, wherein the simulating operation on the set of channel capability alternative job schemes comprises the sub-steps of:
initializing a simulation target state;
running a simulation clock;
when the next event moment becomes the current event moment, judging whether the real-time state of the simulation target meets a preset execution condition, if so, executing the simulation event of the real-time state of the simulation target, and if not, repeatedly executing the sub-step;
judging whether the real-time state of the simulation target after the execution of the simulation event meets the simulation end condition, if so, outputting a simulation operation result and ending the simulation operation, and if not, returning to the third substep.
7. The method of claim 6, wherein the simulated target states include train state, line of service state, locomotive state.
8. A system for railroad access capability bottleneck identification and resolution, comprising:
the data processing and analyzing subsystem is used for acquiring basic data and preprocessing the basic data to acquire bottleneck point parameters;
the model analysis subsystem is used for establishing a mathematical model based on the bottleneck point parameters to obtain a channel capacity alternative operation scheme set; the method specifically comprises the following steps:
establishing a mathematical model by taking the maximum traffic on the line as a target I
Wherein z is 1 In order to be the objective function, the target function,
the method is characterized in that the standard load capacity of small trains in a heavy haul railway, L is a loading station set, U is an unloading station set, K is an empty and heavy vehicle train type set, T is a time interval dividing one day, theta belongs to T = {1,2,3,4},
m represents the number of heavy trains of type k which are driven between i → j during the time period theta k The number of small marshalling columns for the empty and heavy train type K, where K is equal to K, m 0 ＝1,m 1 ＝2；
Establishing a mathematical model by taking the minimum change of a train organization scheme as a target II
Wherein z is 2 In order to be the objective function, the target function,
and
respectively representing cost coefficients;
representing the number of empty trains of which the time interval theta is between i → j and the type of k;
representing the number of empty and heavy trains driven by the original scheme i → j；
For the objective function z 1 And z 2 Normalization is carried out, and a mathematical model Max z is obtained through conversion 3 ＝λ 1 z 1 -λ 2 z 2 Wherein λ is 1 、λ 2 Respectively is the weight coefficient between the targets I and II;
the simulation analysis subsystem is used for carrying out simulation operation on the channel capacity alternative operation scheme set; adjusting a channel capacity alternative operation scheme set based on the simulation operation result to obtain an optimal operation scheme; and comparing and analyzing the optimal operation scheme with the actual operation data, and obtaining a railway channel capacity bottleneck identification and resolution scheme according to the result of the comparison and analysis.
9. The system of claim 8, wherein the data processing analysis subsystem comprises an application subsystem, the data processing analysis subsystem further configured to:
calibrating missing values in the basic data;
processing abnormal values in the basic data;
and completing and converting the basic data, and recording the basic data into the application subsystem.
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| CN111915221B (en) * | 2020-08-18 | 2021-04-09 | 北京交通大学 | Capability analysis method suitable for high-speed railway |
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