WO2014041438A1 - Calculation and estimation of line capacity for high speed railway - Google Patents
Calculation and estimation of line capacity for high speed railway Download PDFInfo
- Publication number
- WO2014041438A1 WO2014041438A1 PCT/IB2013/050039 IB2013050039W WO2014041438A1 WO 2014041438 A1 WO2014041438 A1 WO 2014041438A1 IB 2013050039 W IB2013050039 W IB 2013050039W WO 2014041438 A1 WO2014041438 A1 WO 2014041438A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- trains
- stop
- line
- minutes
- line capacity
- Prior art date
Links
- 238000004364 calculation method Methods 0.000 title claims abstract description 27
- 238000000034 method Methods 0.000 claims abstract description 23
- 230000003993 interaction Effects 0.000 claims abstract description 10
- 238000005096 rolling process Methods 0.000 claims abstract description 9
- 238000005457 optimization Methods 0.000 claims abstract description 8
- 230000008901 benefit Effects 0.000 claims abstract description 6
- 238000013209 evaluation strategy Methods 0.000 claims abstract description 6
- 238000011156 evaluation Methods 0.000 claims description 5
- 238000003820 Medium-pressure liquid chromatography Methods 0.000 claims 3
- 230000006870 function Effects 0.000 description 14
- FTNRXHIYUXAZFP-JNHRZEBYSA-N (2S,3R,4R,5R,6S)-2-[(2R,3R,4S,5S,6R)-4-hydroxy-6-(hydroxymethyl)-5-[(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]oxy-2-[[(1S,2S,4S,8S,9S,12S,13R,16S)-7,9,13-trimethyl-6-[(3R)-3-methyl-4-[(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]oxybutyl]-5-oxapentacyclo[10.8.0.02,9.04,8.013,18]icosa-6,18-dien-16-yl]oxy]oxan-3-yl]oxy-6-methyloxane-3,4,5-triol Chemical compound C[C@H](CCC1=C(C)[C@H]2[C@H](C[C@H]3[C@@H]4CC=C5C[C@H](CC[C@]5(C)[C@H]4CC[C@]23C)O[C@@H]2O[C@H](CO)[C@@H](O[C@@H]3O[C@H](CO)[C@@H](O)[C@H](O)[C@H]3O)[C@H](O)[C@H]2O[C@@H]2O[C@@H](C)[C@H](O)[C@@H](O)[C@H]2O)O1)CO[C@@H]1O[C@H](CO)[C@@H](O)[C@H](O)[C@H]1O FTNRXHIYUXAZFP-JNHRZEBYSA-N 0.000 description 4
- 238000001637 plasma atomic emission spectroscopy Methods 0.000 description 4
- 229920000110 poly(aryl ether sulfone) Polymers 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 230000008520 organization Effects 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 238000011144 upstream manufacturing Methods 0.000 description 2
- 102100029777 Eukaryotic translation initiation factor 3 subunit M Human genes 0.000 description 1
- 102100036738 Guanine nucleotide-binding protein subunit alpha-11 Human genes 0.000 description 1
- 101001012700 Homo sapiens Eukaryotic translation initiation factor 3 subunit M Proteins 0.000 description 1
- 101100283445 Homo sapiens GNA11 gene Proteins 0.000 description 1
- 101001094026 Synechocystis sp. (strain PCC 6803 / Kazusa) Phasin PhaP Proteins 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- 230000002776 aggregation Effects 0.000 description 1
- 238000004220 aggregation Methods 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000005094 computer simulation Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 230000035772 mutation Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000008685 targeting Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
- B61L27/10—Operations, e.g. scheduling or time tables
- B61L27/12—Preparing schedules
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
-
- G06Q50/40—
Abstract
According to the characteristics of the higher class of the trains and the higher request of the punctuality of the high speed railway, based on UIC406, this invention 'Calculation and Estimation of Line Capacity for High Speed Railway' dedicated by Ph.D Jiamin Zhang takes the number of trains, the average speed, the stability and the heterogeneity as the core elements for the calculation & estimation of line capacity. This invention constructs the trains at line 'train service-demand intension set' (t@l— TSDIS) and proposes the time needed to complete t@l— TSDIS as the new criteria to measure the line capacity. Under the known number of trains, seeking the optimized values for the heterogeneity, the average speed, the stability satisfied with the balance relationship of the line capacity and taking the Pareto optimum as the object. Considering both the trains service level and benefit of the railway operation, this invention builds the multi-objective (minimize the heterogeneity, maximize the reliability, minimize the running time) Mathematical Program for Line Capacity (MPLC), and it proposes the rolling optimization solution method oriented by the problem of the MPLC multi-objective model with constraints (combination of the improved PAES (Pareto Archived Evaluation Strategy) & interaction method) (Fig. 3, Fig. 4). This invention also illustrates the application of the invented model & its solution to the case of the calculation & estimation of Beijing— Shanghai high speed railway line capacity.
Description
This invention dedicated by Ph.D Jiamin Zhang
belongs to the technical field of application of railway transportation,
targeting at calculation & estimation of line capacity for high speed
railway. This invention can also be used as the reference of the evaluation
& adjustment of the trains operation order.
The main factors influenced the railway capacity
include the layout of the infrastructure, the timetable and the external
interference. The external interference is dynamic. Under the condition of the
given infrastructure layout, the controllable factors of the railway capacity
lies in the timetable. In China, the definition and calculation of the passage
capacity of the line section mainly starts from the parallel train diagram,
then calculate the passage capacity of the line section of the non-parallel
train diagram based on the former one, using the co-efficient method and
computer simulation etc. But the operational condition of the high speed
railway and the improved existing line have changed according to Yajing
ZHAGN(2010) & Peng Zhao (2009 ). Robert Burdett & Erhan Kozan (2004)
summarized the research of the capacity calculation of the line/network. Olov
Lindfeldt (2010) proposed the calculation method of the line capacity based on
the variable timetable, but it didn't give the optimized criteria of the
evaluation. UIC406 regards the number of the trains, the average speed, the
heterogeneity and the stability as the core elements for the capacity usage.
Landex,A.& Schittenhelm,B. (2008) illustrated the balanced relationship as
the Fig. 1. Jiamin Zhang (2011) analyzed the comprehensive balance of train
operation plan for the high speed railway under mixed traffic condition.
Compared with their counterparts internationally,
many changes of the high speed railway lines in China have taken place such as
their long distance and time of trains operation beyond some common aspects
such as the passenger dedicated, the higher class of the trains and the higher
request of the punctuality. So the traditional method of calculation of line
capacity oriented by the fully usage of the railway facility couldn't be adapt
to the high speed railway totally. This invention constructs the trains at line
'train service-demand intension set' (t@l-TSDIS) and proposes the time needed
to complete t@l-TSDIS as the new criteria to measure the line capacity. Under
the known number of trains, seeking the optimized values for the heterogeneity,
the average speed, the stability satisfied with the balance relationship of the
line capacity described by Fig. 1 and taking the Pareto optimum as the object.
Considering both the trains service level and benefit of the railway operation,
this invention builds the multi-objective (minimize the heterogeneity, maximize
the reliability, minimize the running time) Mathematical Program for Line
Capacity (MPLC), and it proposes the rolling optimization solution method
oriented by the problem of the MPLC multi-objective model with constraints
(combination of the improved PAES (Pareto Archived Evaluation Strategy) &
interaction method). This invention also illustrates the application of the
invented model & its solution to the case of the calculation &
estimation of Beijing—Shanghai high speed railway line capacity.
1.Definition of t@l—TSDIS
According to the characteristics of the passenger
demand of the high speed railway, the time period is divided into the morning
high peak, the plateau, the evening high peak and the comprehensive maintenance
period. The formula
can be used to
define the number of the trains in each period, where di
p is the passenger demand within the time period, Ci is
the given train capacity corresponding to its type ¡,
is the type i train's loaded factor satisfied a
certain service level.
In China the high speed railway line is
double—track with double directions. It operates the trains in the way of
single -direction with double tracks in the normal conditions. In the abnormal
situation, it allows to run the trains in the reversed direction. The capacity
calculation must be based on a certain mode of transportation organization,
that is it should research the calculation and evaluation of the capacity under
the given mode of transportation organization. In China, the railway line
connects many directions of the passenger transportation network, which demands
the uniform train operation scheme for the original line and the crossing lines
and involves the plenty of stations and passenger OD pairs. The train flow
patterns are different decided by the type of the trains, the star–end point,
the train route, the stop pattern and the passing/waiting relationship, so it
should make the train service strategy according to the type of the period
passenger demand and determine the concreter train flow pattern.
(1) Usage Strategy of Line Section within time
Period
1) Trains' Running Time in the Line Section
The trains' running time is the critical factors
of the capacity calculation and evaluation according to Olaf Br¨unger and Elias
Dahlhaus (2008) & Joern Pachl (2002). Let s denote the section connecting
the station s and station s+1. Let S denote the set of the sections and
. Let i and j denote the trains using the section. Let
Ns denote the set of trains using the section s and
Let ejs denote the moment that train j
entering the section j. Let ljs denote the train j leaving the
section j. According to the operational conditions of the high speed railway,
the constraints of the trains' running in the section are as following:
- the trains' running time in the section
For each train j in the section s, if let
r
js
t denote the minimum time when the train
runs at its free optimized speed, then
.
- the minimum dwelling time in the section
The operation of the trains in the station
includes its departure, arrival, return, go through without stop and go through
with stop. If let wjs
t denote the dwelling time of the
train j in the station s, then
.
- the minimum interval time
Let
If let aijs
t denote the minimum
interval time demanded by the train i and j entering the section, then
where M is the arbitrary big positive number which
ensure only when xijs=1 the constraint is effective.
- the consistency of xijs
Let
and
denote the first and the last
trains in the trains sequence running in the section respectively, then each
train in the train sequence has only one immediate forerunner (except the first
one
) that is
.
And it has only one immediate successor (except
the last one
) that is
Tijs Huisman & Richard J. Boucherie (2001)
proposed and improved the theorem of the trains' running time in the condition
of the mixed traffic flow as following:
R0=F0
Rn=max(Fn,
Rn-1–An)
Where Fn is the free running time in
the section without interference, Rn is the real running time from
its entering the line section to leaving the section, An is the
buffer time between train n and n-1. If E(An)>0, then
is a certain variable.
Based on these, this paper lets the first train
in the section run at its optimized free speed, that is
R0s=r0s
t, the other trains consider their
running time under the mutual influencing operational environment, that is
where Ajsis the buffer time between train
j–1 and j in the section s, the total running time of the whole trains trains
in the section s is
. For
Ajs=hjs-aijs
t, then
2) Trains' Heterogeneity Ssshr in the Section
Let the sum of the reciprocal of the minimum
interval time Ssshr denote the heterogeneity of the combination of
different types of trains in the section , that is
Where N is the number of the trains, hjs is
the minimum interval time between the train j and j-1, hjs =minimum
safety interval time + operation redundancy; hjs =
min(ejs–ej-1,s, lj,s–lj–1,s), the
bigger the Ssshr , the higher the heterogeneity. Michiel J, etc
(2006) analyzed the calculation formula for the heterogeneity of the
single-direction section in the double tracks. This paper calculates the
heterogeneity of the upstream/downstream line section respectively according to
the formula, then taking the half of the sum of the both as the heterogeneity
of the whole line section.
(2) Usage Strategy of the Station within Time
Period
The usage strategy of the station in the period
consider the rank of the station, the heterogeneity of the trains in the
station, the operation type in the station (departure, arrival, go through,
with or without the connection relationship for the trains), the platform for
the departure and arrival, the feasible arrival/through/departure timetable,
the priority for the trains' passing relationship, which is measured by the
trains' heterogeneity Ssahr in the station.
Let the sum of the reciprocal of the arrival
interval time denote the trains' heterogeneity in the station according to
Michiel J, etc (2006), that is
Where hjs
A is the time interval
between the arrival time of the train j and j-1 in the station, hjs
A =minimum safety interval time + operation redundancy, N is the
number of the trains, hjs A =
ejs+rjs–ej-1,s–rj–1,s. Under the
condition of the trains' homogeneity, Ssahr equals Ssshr.
Under the condition of the trains' heterogeneity, Ssahr is always
less than Ssshr. Michiel J, etc (2006) analyzed the calculation
formula for the heterogeneity of the arrival interval time of the
single-direction section in the double tracks. This invention calculates the
heterogeneity of the upstream/downstream station respectively according to the
formula, then taking the half of the sum of the both as the heterogeneity of
the whole station. Qiyuan Peng (2004) proposed and analyzed the passing
relationship such as the simple passing, passing the plenty of trains, one
train passed by many trains, complex passing. This invention takes the simple
passing mode. The operation mode (departure, arrival, go through, with or
without the trains' connection) in the station is determined based on the match
relationship between the trains type and the station type. The other elements
such as the time period, the number of trains, the estimated time dwelling in
the station, the platform of the arrival and departure, the feasible
arrival/through/departure timetable, the priority of passing relationship of
the trains and the estimation of the possible delay in the station are set
according to the t@l—TSDIS.
2. Construction of the Model
Under the condition of the fixed infrastructure,
the capacity under a certain service quality is the reflection of the level of
the transportation organization. Based on what mentioned above, this invention
measures the service quality of the transportation from the aspect of the
reliability, the heterogeneity and the service time, then calculates and
evaluates the line capacity.
(1) the Heterogeneity
Steven Harrod (2009) analyzed the affect of the
trains' heterogeneity on the railway network. Both Ssshr and
Ssahr can reflect the heterogeneity of train schedule and predict
the change of the reliability. What is reflected by Ssshr is the
situation of the whole section, while what is reflected by Ssahr is
the arrival situation from the section to the station. The minimization of
Ssshr or Ssahr means the equalization of the time
interval and decreases the possibility of the delay. When the trains with
higher homogeneity for its rational type density, the value of Ssshr
and Ssahr can be ideal. According to these, taking the weighted
average sum of Ssshr and Ssahr as the measurement of the
trains' heterogeneity in the whole line, that is
H=aSsshr+bSsahr where a+b=1 and 0<a<1, 0<b<1.
Both the minimum interval time hi and the minimum arrival interval
time hi
A must satisfy the train operation control system
and constraint of minimum safety interval demanded by the singal system at
first, and ensure a certain redundant operation time, that is hi
=safety interval time + operational redundant time, hi
A
=safety interval time + operational redundant time. If let
hty(i-1),ty(i) denote the minimum safety interval time between the
type of the train i and j calculated by the simulation model using the
quasi–moving block mode, then it must satisfy with that hi is greater than or
equal to hty(i-1),ty(i) and hi
A is greater
than or equal to hty(i-1),ty(i).
(2)the Reliability
The reliability of the network capacity in the
railway system is directly related to the effective usage capacity of the whole
network system according to Zhonglin Lei (2006). The maximization of the
reliability is the essence for the improvement of the effective usage capacity.
From the angel of the operational planning, the factor that is most directly
related to the reliability is the interval time of the trains' operation.
The analysis based on the probability function
belongs to the ex–ante analysis, but the determination of the probability
function of the trains' movement timetable demands a large number of real
operational data. On the other hand, the reliability can be improved by the
rational trains' interval time. So taking the average weighted interval time as
the measurement of the reliability, let hjs denote the interval
time between the train j and its predecessor j–1 in the section s ,
aijs
t denote the minimum interval time between the train
j and its predecessor j–1 in the section s , then the greater the distance
Pjs=hjs–aijs
t between
hjs and aijs
t , the greater the possibility of
the absorption of the delay and the higher the reliability of the trains'
operation. The reliability of the whole line can be defined as
(3) Time Needed to Complete the Set
t@l—TSDIS
According to the analysis of the usage strategy
of the section and station, the running time of the trains in the set t@l—TSDIS
on the whole lines would be as :
(13)
In summary, the Mathematical Program for Line
Capacity ( MPLC) under certain service quality can be defined as:
OBJ:
S.T.
3. Solution of the MPLC Model
(1)Basic Ideas for the Solution of the MPLC
Model Oriented by the Problem
1)
Settlement of the
Multi–objectives
The solution for the settlement of the
multi–objective can be attributed as the method of classification, the utility,
the objective planning, Pareto and the interaction. It adopts the combination
of Pareto Archived Evolution Strategy (PAES) and the interaction method as the
settlement strategy in this invention.
2) Settlement of the Constraints
The settlement of the 0–1 integer constraints:
For the multi–stage line system consisted of a series of sections and stations
based on a certain topology, regarding the section as the processing facility
and the station as the buffer store, it takes the strategy of just—in—case,
that is it takes the 0–1 integer constraints as the problem of constraints
satisfied and optimizes it in the way of rolling motion based on the trains
service strategy, the usage strategy of the station and the section.
The settlement of the constraints of the
consecutive real number: the optimization of the multi-objective with the
constraints can be attributed as the method of the static penalty function, the
dynamic penalty function, the self–adapt penalty function. It takes the
fuzzy—logic penalty function based on the theory of the fuzzy—logic in this
paper.
(2)Concrete Procedure of the Solution for
MPLC Oriented by the Problem
1)Standardization of the Objective
Function
According to
the settlement of the
standardization (minimization) of the objective function are as following:
Then the vector of the optimized objectives is
min {H'line, P'line, R'line}.
(2)Settlement of the 0–1 Integer
Constraints
Leishan Zhou (1994) applied the dynamic system
theory of the discrete event to research the adjustment of the trains'
operation plan in the way of rolling motion. Jiamin Zhang (2011) analyzed the
timetable structure, it adopts the strategy of just–in–case based on the mode
of the periods of equilibrium for the multi–stage line system composed of a
series of sections and stations in a certain topology in this invention,
regarding the station as the buffer store and the section as the processing
facility, that is it takes the interactive rolling optimization for the 0–1
integer constraints based on the trains service strategy, the usage strategy of
the station and the section which is illustrated asFig. 2.
(3) Settlement of the Constraints of the
Consecutive Real Number
It standardizes the constraints of the
consecutive real number in the form that gj(x) is greater than or
equal to 0;
According to the theory of the fuzzy set, this
paper uses the fuzzy-logic penalty function to tackle the traditional
constraints of the real number as g1(v), g2(v),
g3(v), g4(v) and g5(v). Let
tvidenote the conflict degree of the solution v to the constraint ¡,
and
Zi denote the
ith unfeasible endurable threshold value. Introducing the concept of
the fuzzy—logic, let yv be the fuzzy penalty function of the
solution v. According to the definition of the fuzzy, it divides the whole
searching space into the following 10 zones:
Zone 1:
belonging to the feasible zone,
where the item of the penalty is yv=0;
Zone i, i=2~9:
belonging to the penalty zone,
where the item of penalty is yv=i;
Zone 10 ：
belonging to the refusal zone,
where the item of penalty is yv=100.
It sets the endurable threshold value of each
zone in this paper as: 0.001, 0.01, 0.02, 0.5, 1.0, 5.0, 10.0, 15.0, 25.0, 35.
So for any solution v, according to the fuzzy penalty function, the
multi–objective F1=H'line,
F2=P'line, F3= R'line and the
transformed multi–objective vector without the constraints is as:
{F'1, F'2, F'3} and F'1
=F1+yv ( i=1,2,3 ), where F'i representing a
status of the solution, yv representing the violate degree of the
solution in the unfeasible field, and Fi representing the distance
between the solution and the Pareto frontier.
So it completes the settlement of the
constraints of the real number, the method of the fuzzy—logic penalty function
turns the multi–objective planning problem with the constraints into its
counterparts without the constraints as min{F'1, F'2,
F'3}.
(4) tackle the multi–objective optimized
problem using the Pareto Archived Evolution Strategy & interaction
method
Bade on the three steps mentioned above, it
tackles the transformed MFLC multi–objective problem to evaluate and calculate
in the mode of rolling optimization, taking the station—section (that is the
station and the section adjacent to the station in the direction of the trains'
operation) as a unit, and dealing each unit with the Pareto (1+1) Archived
Evolution Strategy (PAES)& interaction method.
PAES has the sound evolution character and
convergence speed, which is composed of alternative solution generator, the
acceptance function for the alternative solution and the archive list for the
non–denominated solution. According to the characteristics of the model MPLC,
this invention adopts the improved (1+1)—PAES archive strategy and its basic
flow is illustrated as Fig. 3.
1)generation of the original solution
Regarding the trains in t@l—TSDIS as the trains
group which has the characteristics of the concurrency and randomness, it takes
the strategy of just–in–case to generate an original solution. The solution
takes the code of the real number, defining the representation of the solution
as following:
For each train j in each section sec:
vsec–j={xijs, (ejs, ljs),
hjs, hjs
A};
For all of the trains in each section sec:
vsec= {vsec–0, vsec–1, vsec–2, …,
vsec–Ns};
For the whole line composed by the stion (stion
denoting the number of the sections in the line) sections: v={v0,
v1, v2, …, vstion}.
It maintains the current Pareto optimized
solution in the improved (1+1)—PAES archive strategy, and decides the
acceptance and refusal of the current solution as well as selecting one
solution from the updated archive list to produce a mutation solution in each
iteration according to the violation situation of each constraint and the
optimized degree of the current objective values.
2) improved update strategy of the (1+1)–PAES
archive list and the acceptance logic of the current solution
As for the calculation of the fitness, according
to the present research, the strategy for the determination of the fitness
value of the multi–objective evolutionary algorithm can be classified as that
based on the aggregation, the standard and the Pareto denominating
relationship. PAES evaluation function evaluates the individuals based on the
denominating relationship. The improved (1+1)—PAES in this paper also adopts
the determination of the fitness value based on the denominating relationship
(counting the number of the individuals in the population denominating the
individual of the alternative solution. Let Oi denote the number of
a certain individual denominated by the population, taking the reciprocal of
Oi as the fitness of the individual i).
It designs the archive list of each
station-section unit as the two parts of the objective space and the solution
space in this paper. The objective space is designed as the 5x3 matrix with
five rows and three columns, where each column represents the three objective
values as the heterogeneity, the reliability and the operation time. According
to the time of entering/leaving the section, the solution space is designed as
the matrix of 5×2Ns
up in the upstream and
5×2Ns
down in the downstream, where Ns
up is the number of the trains in the upstream section s,
Ns down is the number of trains in the downstream section
s.
The update of the archive list and the
acceptance of the current solution is based on the fitness value, which
compares the fitness value of the current solution with each member of the
archive list. According to the denominating relationship, if the fitness value
of the current solution is less than that of all of the members of the archive
list, then it's refused; else if it is greater than that of all of the members
of the archive list, then the denominated members of the archive list are
deleted and adds the current solution into the archive list; else if it is
greater than parts of that of the members of the archive list, then the current
solution replaces the denominated members to the biggest degree. If the archive
list isn't full and still possible to be optimized, then the individual in the
archive list with the biggest fitness value is selected and mutated to a new
current solution. If the archive list is full and all of the violation values
of the constraints are less than or equal to the minimum threshold, then the
solution in the archive list with the biggest violation value is selected and
mutated to a new current solution, else it stops the update of the archive
list. The improved (1+1) —Pareto archive update and acceptance logic of the
current solution is illustrated as Fig. 4.
According to the characteristics of the higher
class of the trains and the higher request of the punctuality of the high speed
railway, this invention taking the number of trains, the average speed, the
stability and the heterogeneity as the core elements for the calculation &
estimation of line capacity. This invention constructs the trains at line
'train service–demand intension set' (t@l—TSDIS) and proposes the time needed
to complete t@l—TSDIS as the new criteria to measure the line capacity. Under
the known number of trains, seeking the optimized values for the heterogeneity,
the average speed, the stability satisfied with the balance relationship of the
line capacity described by Fig. 1 and taking the Pareto optimum as the object.
Considering both the trains service level and benefit of the railway operation,
this invention builds the multi–objective (minimize the heterogeneity, maximize
the reliability, minimize the running time) Mathematical Program for Line
Capacity (MPLC), and it proposes the rolling optimization solution method
oriented by the problem of the MPLC multi–objective model with constraints
(combination of the improved PAES (Pareto Archived Evaluation Strategy) &
interaction method) (Fig. 2, Fig. 3, Fig. 4). This invention also illustrates
the application of the invented model & its solution to the case of the
calculation & estimation of Beijing-Shanghai high speed railway line
capacity.
The calculation and estimation of the line
capacity in this invention is under the condition of the known number of the
trains, according to the balanced relationship of the capacity shown in Fig. 1,
it defines the line's trains service–demand intension set t@l—TSDIS and seeks
the Pareto optimized values for the heterogeneity, the reliability and the
operation time which satisfy the Fig. 1 . According to the relation between the
speed and the time, the optimized speed of the trains can be achieved from the
optimized operation time under the Pareto optimized status. For the existence
of the interference, the trains' operation would like to deviate from the
timetable, the heterogeneity can be taken as the standard to evaluate the order
of the trains' operation and the reference to adjust the trains' real
operation. Moreover, the results of the model can give the interval time of the
trains in the station—section unit and the moment that the trains'
entering/leaving the station—section unit. The type of the international high
speed railway lines can be classified as intercity, corridor and the end of the
network, the methodology (the MPLC model and its solution) for the calculation
and estimation of the line capacity proposed in this invention can be applied
to each type of the lines.
Please refer all of the figures mentioned to the
Drawings section.
According to the characteristics of the higher
class of the trains and the higher request of the punctuality of the high speed
railway, this invention taking the number of trains, the average speed, the
stability and the heterogeneity as the core elements for the calculation &
estimation of line capacity. This invention constructs the trains at line
'train service–demand intension set' (t@l—TSDIS) and proposes the time needed
to complete t@l—TSDIS as the new criteria to measure the line capacity. Under
the known number of trains, seeking the optimized values for the heterogeneity,
the average speed, the stability satisfied with the balance relationship of the
line capacity described by Fig. 1 and taking the Pareto optimum as the object.
Considering both the trains service level and benefit of the railway operation,
this invention builds the multi–objective (minimize the heterogeneity, maximize
the reliability, minimize the running time) Mathematical Program for Line
Capacity (MPLC), and it proposes the rolling optimization solution method
oriented by the problem of the MPLC multi–objective model with constraints
(combination of the improved PAES (Pareto Archived Evaluation Strategy) &
interaction method) (Fig. 2, Fig. 3, Fig. 4) . This invention also illustrates
the application of the invented model & its solution to the case of the
calculation & estimation of Beijing-Shanghai high speed railway line
capacity.
According to the characteristics of the higher
class of the trains and the higher request of the punctuality of the high speed
railway, this invention taking the number of trains, the average speed, the
stability and the heterogeneity as the core elements for the calculation &
estimation of line capacity. This invention constructs the trains at line
'train service–demand intension set' (t@l—TSDIS) and proposes the time needed
to complete t@l—TSDIS as the new criteria to measure the line capacity. Under
the known number of trains, seeking the optimized values for the heterogeneity,
the average speed, the stability satisfied with the balance relationship of the
line capacity described by Fig. 1 and taking the Pareto optimum as the object.
Considering both the trains service level and benefit of the railway operation,
this invention builds the multi–objective (minimize the heterogeneity, maximize
the reliability, minimize the running time) Mathematical Program for Line
Capacity (MPLC), and it proposes the rolling optimization solution method
oriented by the problem of the MPLC multi–objective model with constraints
(combination of the improved PAES (Pareto Archived Evaluation Strategy) &
interaction method) (Fig. 2, Fig. 3, Fig. 4). This invention also illustrates
the application of the invented model & its solution to the case of the
calculation & estimation of Beijing-Shanghai high speed railway line
capacity.
The high speed railway line Beijing—Shanghai
connects two critical economical zones in China, which satisfies the mixed
traffic condition with the on-line and off-line operation for the crossing
trains with the speed of 300km/h and 250km/h. It takes three sorts of operation
mode: non-stop, stop only at the station in the provincial city, stop staggered
along the line. According to the trains' speed, stop pattern,
origin-destination, the trains in t@l—TSDIS can be classified into six ranks as
the illustration of Table 1.
| Rank of trains | Trains' speed | Stop pattern | origin—destination (this line/crossing line) |
| First class | 300km/h | Non-stop | this line |
| Second class | 300km/h | stop only at the station in the provincial city | this line |
| Third class | 300km/h | stop staggered in the medium stations along the line | this line |
| Fourth class | 250km/h | stop staggered in the medium stations along the line | this line |
| Fifth class | 250km/h | stop staggered in the medium stations along the line | crossing line |
| Sixth class | 200km/h | stop staggered in the medium stations along the line | crossing line |
Compiling the task list t@s—TSDIS according to
the set of the trains service–demand intention in a certain high peak of the
Beijing—Shanghai high speed railway line, which is illustrated as Table 2.
| Number of trains | Type of trains | origin—destination | Stations passing by(according to the direction of the trains operation) and type and time of dwelling at the station | Class of trains |
| G1 | This line, 300km/h, non-stop | BJN–SHHQ | BJN (stop, 2 minutes) | First class |
| G2 | this line, 300km/h, non-stop | SHHQ–BJN | BJN (stop, 2 minutes) | First class |
| G3 | This line, 300km/h, stop only at the station in the provincial city | BJN–SHHQ | JNX (stop, 2 minutes) , NJN(stop, 2 minutes) | Second class |
| G4 | This line, 300km/h, stop only at the station in the provincial city | SHHQ–BJN | NJN(stop, 2 minutes), JNX (stop, 2 minutes) | Second class |
| GA01 | This line, 300km/h, stop staggered in the medium stations along the line | BJN–SHHQ | LF(stop, 2 minutes), TJN(stop, 2 minutes), DZD(stop, 2 minutes), JNX(stop, 2 minutes), XZD(stop, 2 minutes), BBN(passing by through), NJN(stop, 2 minutes), ZJN(stop, 2 minutes), WXD(stop, 2 minutes), KSN(passing by through) | Third class |
| GA02 | This line, 300km/h, stop staggered in the medium stations along the line | SHHQ–BJN | KSN(stop, 2 minutes) , WXD(passing by through), ZJN(passing by through), NJN(stop, 2 minutes), BBN(stop, 2 minutes), XZD(stop, 2 minutes), JNX(stop, 2 minutes), DZD(stop, 2 minutes), TJN(passing by through), LF(passing by through) | Third class |
| GA03 | This line,300km/h, stop staggered in the medium stations along the line | BJN–SHHQ | CZX(stop,1 minute) 、 JNX(stop, 3 minutes) , TA(passing by through) , XZD(passing by through), BBN(stop, 3 minutes), NJN(stop, 2 minutes), CZB(stop, 1 minute), SZB(passing by through), KSN(stop, 2 minutes) | Third class |
| GA04 | This line, 300km/h, stop staggered in the medium stations along the line | SHHQ–BJN | KSN(passing by through), SZB(stop, 2 minutes), CZB(stop, 1 minute), NJN(stop, 2 minutes), BBN(passing by through), XZD(stop, 3 minutes), TA(stop, 2 minutes), JNX(stop, 2 minutes), CZX(passing by through) | Third class |
| GA05 | This line, 300km/h, stop staggered in the medium stations along the line | BJN–SHHQ | LF(passing by through) , JNX(stop, 2 minutes), TA(stop, 2 minutes), ZZ(passing by through) , XZD(stop, 2 minutes) ,BBN(passing by through), CZ(stop, 2 minutes), NJN(stop, 3minutes), WXD(passing by through), SZB(stop, 2 minutes) | Third class |
| GA06 | This line, 300km/h, stop staggered in the medium stations along the line | SHHQ–BJN | SZB(passing by through), WXD(stop, 2 minutes), NJN(stop, 2 minutes), CZ(passing by through), BBN(stop, 2 minutes), XZD(stop, 2 minutes), ZZ(stop, 1 minute), TA(passing by through), JNX(stop, 2 minutes), LF(stop, 2 minutes) | Third class |
| GA07 | This line, 300km/h, stop staggered in the medium stations along the line | BJN–SHHQ | TJN(passing by through), CZX(stop, 1 minute), DZD(stop, 1 minute), JNX(stop, 2 minutes), TA(passing by through), XZD(stop, 3 minutes), SZD(passing by through), NJN(stop, 3 minutes), CZB(passing by through), WXD(stop, 2 minutes), SZB(passing by through) | Third class |
| GA08 | This line, 300km/h, stop staggered in the medium stations along the line | SHHQ–BJN | SZB(stop, 2 minutes) , WXD(passing by through), CZB(stop, 2 minutes), NJN(stop, 2 minutes), SZD(stop, 1 minute), XZD(stop, 2 minutes), TA(stop, 2 minutes), JNX(passing by through), DZD(passing by through), CZX(passing by through), TJN(stop, 2 minutes) | Third class |
| GA09 | This line, 300km/h, stop staggered in the medium stations along the line | BJN–SHHQ | LF(stop, 2 minutes), JNX(stop, 2 minutes), TA(stop, 2 minutes), BBN(passing by through), CZ(stop, 2 minutes), NJN(stop, 2 minutes), DYB(passing by through), CZB(stop, 2 minutes), SZB(stop, 2 minutes), KSN(passing by through) | Third class |
| GA10 | This line, 300km/h, stop staggered in the medium stations along the line | SHHQ–BJN | KSN(stop, 1 minute), SZB(passing by through), CZB(passing by through), DYB(stop, 1 minute), NJN(stop, 2 minutes), CZ(passing by through), BBN(stop, 2 minutes), TA(stop, 2 minutes), JNX(stop, 2 minutes), LF(stop, 2 minutes) | Third class |
| GA11 | This line, 300km/h, stop staggered in the medium stations along the line | BJN–SHHQ | TJN(passing by through), CZX(stop, 2 minutes), JNX(stop, 2 minutes), TZD(stop, 2 minutes), XZD(passing by through), BBN(stop, 9 minutes), NJN(stop, 2 minutes), ZJN(stop, 2 minutes), WXD(passing by through) | Third class |
| GA12 | This line, 300km/h, stop staggered in the medium stations along the line | SHHQ–BJN | WXD(stop, 2 minutes), ZJN(stop, 2 minutes), NJN(stop, 2 minutes), BBN(passing by through), XZD(stop, 2 minutes), TZD(passing by through), JNX(stop, 2 minutes), CZX(stop, 2 minutes), TJN(stop, 2 minutes) | Third class |
| GA13 | This line, 300km/h, stop staggered in the medium stations along the line | BJN–SHHQ | JNX(stop, 2 minutes) , TA(stop, 2 minutes), XZD(stop, 2 minutes), CA(passing by through) , NJN(stop, 2 minutes), DYB(stop, 2 minutes), WXD(stop, 1 minute), SZB(passing by through) | Third class |
| GA14 | This line, 300km/h, stop staggered in the medium stations along the line | SHHQ–BJN | SZB(stop, 2 minutes), WXD(passing by through), DYB(stop, 2 minutes), NJN(stop, 2 minutes), CZ(stop, 2 minutes), XZD(passing by through), TA(stop, 2 minutes), JNX(stop, 2 minutes) | Third class |
| GA15 | This line, 300km/h, stop staggered in the medium stations along the line | BJN–SHHQ | CZX(passing by through), DZD(stop, 2 minutes), NX(stop, 2 minutes), QFD(passing by through), TZD(stop, 2 minutes), CZ(stop, 2 minutes), NJN(stop, 2 minutes), ZJN(stop, 2 minutes), WXD(stop, 1 minute), SZB(passing by through) | Third class |
| GA16 | This line, 300km/h, stop staggered in the medium stations along the line | SHHQ–BJN | SZB(stop, 2 minutes), WXD(stop, 3 minutes) , ZJN(passing by through), NJN(stop, 2 minutes), CZ(passing by through), TZD(passing by through), QFD(stop, 2 minutes), JNX(stop, 3 minutes), DZD(passing by through), CZX(stop, 2 minutes) | Third class |
| GA17 | This line, 300km/h, stop staggered in the medium stations along the line | BJN–SHHQ | TJN(stop, 2 minutes), JNX(stop, 2 minutes) ,TA(passing by through) ,ZZ(stop, 2 minutes), XZD(stop,8minutes), BBN(passing by through), NJN(stop, 2 minutes), WXD(passing by through), SZB(stop, 2 minutes), KSN(passing by through) | Third class |
| GA18 | This line, 300km/h, stop staggered in the medium stations along the line | SHHQ–BJN | KSN(stop, 2 minutes) , SZB(passing by through), WXD(stop, 2 minutes), NJN(stop, 2 minutes), BBN(stop, 2 minutes), XZD(passing by through), ZZ(passing by through), TA(stop, 8 minutes), JNX(stop, 2 minutes), TJN(passing by through) | Third class |
| GB01 | This line, 250km/h, stop staggered in the medium stations along the line | BJN–SHHQ | LF(stop, 2 minutes), JNX(stop, 2 minutes) , QFD(passing by through), TZD(stop, 1minute), XZD(passing by through), SZD(stop, 2 minutes), NJN(stop, 2 minutes), ZJN(stop, 1minute), WXD(passing by through), KSN(stop, 2 minutes) | Fourth class |
| GB02 | This line, 250km/h, stop staggered in the medium stations along the line | SHHQ–BJN | KSN(stop, 1minute), WXD(stop, 2 minutes), ZJN(passing by through), NJN(stop, 2 minutes), SZD(passing by through), XZD(stop, 3 minutes), TZD(passing by through), QFD(stop, 2 minutes), JNX(stop, 2 minutes), LF(passing by through) | Fourth class |
| GB03 | This line, 250km/h, stop staggered in the medium stations along the line | BJN–SHHQ | LF(passing by through) , TJN(passing by through), DZD(stop, 2 minutes), JNX(stop, 3 minutes), QFD(stop, 2 minutes), XZD(stop, 1minute), CZ(passing by through), NJN (stop, 2 minutes), DYB(stop, 2 minutes), CZB(passing by through) | Fourth class |
| GB04 | This line, 250km/h, stop staggered in the medium stations along the line | SHHQ–BJN | CZB(stop, 2 minutes), DYB(passing by through), NJN(stop, 2 minutes), CZ(stop, 1minute), XZD(stop, 2 minutes), QFD(passing by through), JNX(stop, 2 minutes), DZD(passing by through), TJN(stop, 2 minutes), LF(stop, 2 minutes) | Fourth class |
| GC01 | Crossing line, 250km/h, off line at SHHQ station | BJN—HZ | DZD(stop, 3 minutes) , JNX(stop, 2 minutes) , TZD(passing by through), ZZ(passing by through), XZD(stop,5 minutes), NJN(stop, 3 minutes), CZB(passing by through), WXD(stop, 2 minutes), SZB(passing by through), SSHQ(stop, 4 minutes, then off line) | Five class |
| GC02 | Crossing line, 250km/h , on line at SHHQ station | HZ—BJN | SSHQ(stop, 3 minutes, then on line), SZB(stop, 2 minutes), WXD(passing by through), CZB(stop, 2 minutes), NJN(stop, 2 minutes), XZD(stop, 2 minutes), TZD(stop, 2 minutes), JNX(stop, 2 minutes), DZD(stop, 2 minutes) | Five class |
| D01 | Crossing line, 200km/h, on line at JN station, off line at XZD station | QD—ZZ | JN(on line, stop, 6 minutes), TA(stop, 1minute), QFD(stop, 3 minutes), TZD(stop, 2 minutes), ZZ(stop, 9 minutes), XZD(stop, 9 minutes, then off line) | Six class |
| D02 | Crossing line, 200km/h, on line at XZD station, off line at JN station | ZZ—QD | XZD(stop, 21 minutes, then on line), ZZ(stop,7 minutes), TZD(passing by through), QFD(stop, 23 minutes), TA(passing by through) , JN(stop, 6 minutes, then off line) | Six class |
According to the solution of the MPLC model (Fig.
2, Fig. 3, Fig. 4), using the computer language C# to compile the Console
program, the objective values such as the heterogeneity, the reliability and
the operation time for the completion of the task list t@l—TSDIS for the
station—section unit and the whole high speed railway line of the
Bejing—Shanghai are illustrated as the Table 3.
| no | station–section | heter (st) | reli (st) | rt (st) | heter (pv) | reli (pv) | rt (pv) |
| 0 | bjn-lf | 0.952027236 | 0.005302227 | 0.996896338 | 19.84516129 | 187.6 | 321.2 |
| 1 | lf-tjn | 0.950672198 | 0.005159959 | 0.99745028 | 19.27254329 | 188.8 | 391.2 |
| 2 | tjn-czx | 0.950930202 | 0.005038291 | 0.997915451 | 19.37913431 | 197.48 | 478.72 |
| 3 | czx-dzd | 0.950669079 | 0.004909662 | 0.998300822 | 19.27126149 | 202.68 | 587.52 |
| 4 | dzd-jnx | 0.949183991 | 0.00475466 | 0.998005903 | 18.67883766 | 209.32 | 500.48 |
| 5 | jnx-ta | 0.95126714 | 0.003888025 | 0.996164468 | 19.52003508 | 256.2 | 259.72 |
| 6 | ta-qfd | 0.949318911 | 0.003825555 | 0.997673553 | 18.73122574 | 260.4 | 428.84 |
| 7 | qfd-tzd | 0.947413447 | 0.003664346 | 0.997052234 | 18 | 271.9 | 338.24 |
| 8 | tz-zz | 0.946315687 | 0.003547357 | 0.995422084 | 17.62741544 | 280.9 | 217.44 |
| 9 | zz-xzd | 0.945413937 | 0.003422313 | 0.997378905 | 17.31969437 | 291.2 | 380.52 |
| 10 | xzd-szd | 0.940972988 | 0.004204507 | 0.997678522 | 15.94139633 | 236.84 | 429.76 |
| 11 | szd-bbn | 0.941377206 | 0.004133598 | 0.997618367 | 16.05821119 | 240.92 | 418.88 |
| 12 | bbn-dy | 0.939501388 | 0.004067025 | 0.99654362 | 15.52930496 | 244.88 | 288.32 |
| 13 | dy-cz | 0.939348934 | 0.004040078 | 0.997043869 | 15.48775624 | 246.52 | 337.28 |
| 14 | cz-njn | 0.938710806 | 0.004005768 | 0.996830026 | 15.31608991 | 248.64 | 314.46 |
| 15 | njn-zjn | 0.938161434 | 0.003948823 | 0.997296274 | 15 | 252 | 369 |
| 16 | zjn-dyb | 0.939328271 | 0.003861004 | 0.99270073 | 15.48214121 | 258 | 136 |
| 17 | dyb-czb | 0.938767115 | 0.003865182 | 0.994288325 | 15.33109394 | 257.72 | 174.08 |
| 18 | czb-wxd | 0.9383585 | 0.003910527 | 0.996785393 | 15.22283697 | 254.72 | 310.08 |
| 19 | wxd-szb | 0.936915756 | 0.003817377 | 0.9929795 | 14.85181878 | 260.96 | 141.44 |
| 20 | szb-ksn | 0.936816854 | 0.003806334 | 0.994288325 | 14.8270055 | 261.72 | 174.08 |
| 21 | ksn-sshq | 0.937591385 | 0.003812719 | 0.9956221 | 15.02342874 | 261.28 | 227.42 |
| Sum of line | 20.75906246 | 0.090985337 | 21.92193509 | 371.7163924 | 5370.68 | 7224.68 | |
| Average of line | 0.94359374 | 0.004135697 | 0.996451595 | 16.896199 | 244.1 | 328.394 | |
notion: heter—heterogeneity, reliability—reli,
rt—runnint time, st—standard value, pv—practical value.
So, using the time needed to complete the task
list t@l—TSDIS of the line as the standard to measure the capacity, the
optimized capacity of the Beijing—Shanghai high speed railway line is 7224.68
minutes, with which the objective value of heterogeneity is 371.7163924, the
reliability is 5370.68, while the values of the heterogeneity and the
reliability mean the achieved level of the trains' service quality for the
realization of the capacity.
Claims (1)
- Characteristics of This Invention & Claims for Protection1. Characteristics of This Invention(1) According to the characteristics of the higher class of the trains and the higher request of the punctuality of the high speed railway, based on UIC406, this invention 'Calculation and Estimation of Line Capacity for High Speed Railway' dedicated by Ph.D Jiamin Zhang takes the number of trains, the average speed, the stability and the heterogeneity as the core elements for the calculation & estimation of line capacity. This invention constructs the trains at line 'train service-demand intension set' (t@l—TSDIS) and proposes the time needed to complete t@l—TSDIS as the new criteria to measure the line capacity. Under the known number of trains, seeking the optimized values for the heterogeneity, the average speed, the stability satisfied with the balance relationship of the line capacity described by Fig. 1 and taking the Pareto optimum as the object. Considering both the trains service level and benefit of the railway operation, this invention builds the multi-objective (minimize the heterogeneity, maximize the reliability, minimize the running time) Mathematical Program for Line Capacity (MPLC), and it proposes the rolling optimization solution method oriented by the problem of the MPLC multi-objective model with constraints (combination of the improved PAES (Pareto Archived Evaluation Strategy) & interaction method) (Fig. 2, Fig. 3, Fig. 4). This invention also illustrates the application of the invented model & its solution to the case of the calculation & estimation of Beijing—Shanghai high speed railway line capacity (Table 2, Table 3).(2) According to what mentioned above in (1), the calculation and evaluation of the line capacity in this invention is under the condition of the known number of the trains, according to the balanced relationship of the capacity shown in Fig. 1, it defines the line's trains service–demand intension set t@l—TSDIS and seeks the Pareto optimized values for the heterogeneity, the reliability and the operation time which satisfy the Fig. 1. According to the relation between the speed and the time, the optimized speed of the trains can be achieved from the optimized operation time under the Pareto optimized status. For the existence of the interference, the trains' operation would like to deviate from the timetable, the heterogeneity can be taken as the standard to evaluate the order of the trains' operation and the reference to adjust the trains' real operation. Moreover, the results of the model can give the interval time of the trains in the station-section unit and the moment that the trains' entering/leaving the station-section unit.(3) The type of the international high speed railway can be classified as intercity, corridor and the end of the network, the methodology (the MPLC model and its solution) (Fig. 2, Fig. 3, Fig. 4) for the calculation and estimation of the line capacity proposed in this invention can be applied to each type of the lines.2. Claims for Protection(1) Rights for Signature,(2) Rights for Occupancy,(3) Rights for Patents,(4) Rights for Usage and Disposition,(5) Rights for Indispensible Rewards,(6) Rights for Sale and Transfer of the Usage.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201220470286.6 | 2012-09-17 | ||
| CN201220470286 | 2012-09-17 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2014041438A1 true WO2014041438A1 (en) | 2014-03-20 |
Family
ID=50277708
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/IB2013/050039 WO2014041438A1 (en) | 2012-09-17 | 2013-01-03 | Calculation and estimation of line capacity for high speed railway |
Country Status (1)
| Country | Link |
|---|---|
| WO (1) | WO2014041438A1 (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107168965A (en) * | 2016-03-07 | 2017-09-15 | 阿里巴巴集团控股有限公司 | Feature Engineering strategy determines method and device |
| CN111324853A (en) * | 2020-03-09 | 2020-06-23 | 西南交通大学 | Method and system for calculating passing capacity of channel type high-speed railway |
| CN111882216A (en) * | 2020-07-28 | 2020-11-03 | 北京交通大学 | Inter-city railway transportation capacity calculation method based on average minimum interval time |
| CN112085269A (en) * | 2020-09-04 | 2020-12-15 | 深圳技术大学 | Dynamic optimization analysis system for operation organization under railway interconnection background |
| CN114707284A (en) * | 2021-10-09 | 2022-07-05 | 北京交通大学 | High-speed railway section passing capacity simulation calculation system |
| CN115432037A (en) * | 2022-09-30 | 2022-12-06 | 同济大学 | Method and system for calculating maximum passing capacity of high-speed rail interval |
| CN116485286A (en) * | 2023-06-21 | 2023-07-25 | 中铁第四勘察设计院集团有限公司 | Regional passenger dedicated line planning and evaluation method and system based on analytic hierarchy process |
| CN117150630A (en) * | 2023-10-26 | 2023-12-01 | 中铁建大桥工程局集团第三工程有限公司 | Stability evaluation method for oversized-section subway station based on analytic hierarchy process |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102129522A (en) * | 2011-03-17 | 2011-07-20 | 北京交通大学 | Method for quickly identifying and eliminating transportation capacity bottleneck of high-speed railway |
-
2013
- 2013-01-03 WO PCT/IB2013/050039 patent/WO2014041438A1/en active Application Filing
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102129522A (en) * | 2011-03-17 | 2011-07-20 | 北京交通大学 | Method for quickly identifying and eliminating transportation capacity bottleneck of high-speed railway |
Non-Patent Citations (2)
| Title |
|---|
| ZHANG, JIAMIN ET AL.: "Comparison and Analysis of Calculation and Evaluation Strategy of Station Capacity for High Speed Railway.", CHINESE RAILWAYS, March 2011 (2011-03-01), pages 22 - 25 * |
| ZHANG, JIAMIN ET AL.: "Optimization on the Occupation Order for Trains on Tracks of the Railway Station.", JOURNAL OF TRANSPORTATION SYSTEMS ENGINEER AND INFORMATION TECHNOLOGY., vol. 11, no. 3, June 2011 (2011-06-01), pages 100 - 107 * |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107168965B (en) * | 2016-03-07 | 2021-01-12 | 阿里巴巴集团控股有限公司 | Feature engineering strategy determination method and device |
| CN107168965A (en) * | 2016-03-07 | 2017-09-15 | 阿里巴巴集团控股有限公司 | Feature Engineering strategy determines method and device |
| CN111324853A (en) * | 2020-03-09 | 2020-06-23 | 西南交通大学 | Method and system for calculating passing capacity of channel type high-speed railway |
| CN111882216B (en) * | 2020-07-28 | 2023-12-26 | 北京交通大学 | Inter-city railway transportation capacity calculation method based on average minimum interval time |
| CN111882216A (en) * | 2020-07-28 | 2020-11-03 | 北京交通大学 | Inter-city railway transportation capacity calculation method based on average minimum interval time |
| CN112085269A (en) * | 2020-09-04 | 2020-12-15 | 深圳技术大学 | Dynamic optimization analysis system for operation organization under railway interconnection background |
| CN114707284A (en) * | 2021-10-09 | 2022-07-05 | 北京交通大学 | High-speed railway section passing capacity simulation calculation system |
| CN114707284B (en) * | 2021-10-09 | 2024-04-09 | 北京交通大学 | High-speed railway section throughput simulation computing system |
| CN115432037A (en) * | 2022-09-30 | 2022-12-06 | 同济大学 | Method and system for calculating maximum passing capacity of high-speed rail interval |
| CN115432037B (en) * | 2022-09-30 | 2023-08-04 | 同济大学 | Method and system for calculating maximum passing capacity of high-speed rail section |
| CN116485286B (en) * | 2023-06-21 | 2023-10-03 | 中铁第四勘察设计院集团有限公司 | Regional passenger dedicated line planning and evaluation method and system based on analytic hierarchy process |
| CN116485286A (en) * | 2023-06-21 | 2023-07-25 | 中铁第四勘察设计院集团有限公司 | Regional passenger dedicated line planning and evaluation method and system based on analytic hierarchy process |
| CN117150630A (en) * | 2023-10-26 | 2023-12-01 | 中铁建大桥工程局集团第三工程有限公司 | Stability evaluation method for oversized-section subway station based on analytic hierarchy process |
| CN117150630B (en) * | 2023-10-26 | 2024-02-23 | 中铁建大桥工程局集团第三工程有限公司 | Stability evaluation method for oversized-section subway station based on analytic hierarchy process |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2014041438A1 (en) | Calculation and estimation of line capacity for high speed railway | |
| Gao et al. | Rescheduling a metro line in an over-crowded situation after disruptions | |
| Mo et al. | A flexible metro train scheduling approach to minimize energy cost and passenger waiting time | |
| Chen et al. | Two moments estimation of the delay on single-track rail lines with scheduled traffic | |
| Li et al. | A green train scheduling model and fuzzy multi-objective optimization algorithm | |
| Kraay et al. | Real-time scheduling of freight railroads | |
| Ghoseiri et al. | A multi-objective train scheduling model and solution | |
| Cheng | Hybrid simulation for resolving resource conflicts in train traffic rescheduling | |
| CN114312926B (en) | Method and system for optimizing operation adjustment scheme of urban rail transit train | |
| Lin et al. | Integrating traffic routing optimization and train formation plan using simulated annealing algorithm | |
| Zhang | Analysis on line capacity usage for China high speed railway with optimization approach | |
| Wang et al. | Optimization models for high-speed train unit routing problems | |
| Cao et al. | Optimal capacity allocation under random passenger demands in the high-speed rail network | |
| Wang et al. | Synchronized optimization for service scheduling, train parking and routing at high-speed rail maintenance depot | |
| Li et al. | Joint optimization of delay-recovery and energy-saving in a metro system: A case study from China | |
| Meng et al. | Trajectory optimization of autonomous agents with spatio-temporal constraints | |
| Wang et al. | A simulation-based metro train scheduling optimization incorporating multimodal coordination and flexible routing plans | |
| Hu et al. | Optimal design for urban mass transit network based on evolutionary algorithms | |
| Zhong et al. | Parallel optimization method of train scheduling and shunting at complex high‐speed railway stations | |
| Yang et al. | High-speed Train Timetabling Based on Reinforcement Learning | |
| Setyawan et al. | Multi-criteria Mathematical Model for Partial Double Track Railway Scheduling in Urban Rail Network | |
| Zhang et al. | Forecast and Model Establishment of Urban Rail—Transit Passenger Flow | |
| Jiang et al. | A connecting timetable rescheduling model for production and rail transportation with unexpected disruptions | |
| Li et al. | High-speed Railway Timetabling Model based on Transfer Optimization | |
| Zakharova et al. | Smart Transport as an Enhancement of the Urban Infrastructure |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 13837892 Country of ref document: EP Kind code of ref document: A1 |
|
| NENP | Non-entry into the national phase |
Ref country code: DE |
|
| 122 | Ep: pct application non-entry in european phase |
Ref document number: 13837892 Country of ref document: EP Kind code of ref document: A1 |