CN108647825A - Urban road construction sequence optimizing method based on traffic daily variation characteristics - Google Patents
Urban road construction sequence optimizing method based on traffic daily variation characteristics Download PDFInfo
- Publication number
- CN108647825A CN108647825A CN201810446757.1A CN201810446757A CN108647825A CN 108647825 A CN108647825 A CN 108647825A CN 201810446757 A CN201810446757 A CN 201810446757A CN 108647825 A CN108647825 A CN 108647825A
- Authority
- CN
- China
- Prior art keywords
- construction
- traffic
- days
- flow
- feasible solution
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
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"
-
- 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
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/08—Construction
Abstract
The invention discloses a kind of urban road construction sequence optimizing methods based on traffic daily variation characteristics, include the following steps：Step 1: becoming the parameter involved by Dynamic Traffic Assignment Model and genetic algorithm initialization day；Step 2: generating the initial feasible solution (sequence of construction) for meeting initial population quantitative requirement；Step 3: becoming traffic with every other day construction time is evolved into analytic process, using object function proposed by the present invention as fitness function, the fitness of feasible solution is calculated；Step 4: judging whether practical iterations meet the iterations requirement of setting, if it is satisfied, then generating optimal solution, stop calculating；If not satisfied, then entering step five；Step 5: generating new feasible solution, it is then back to step 3.The positive effect of the present invention is：The method of the present invention considers the daily variation characteristics of traffic, can describe construction period traffic flow by the evolutionary process of nonequilibrium state to equilibrium state, further improve computational accuracy, be more in line with truth.
Description
Technical field
The present invention relates to a kind of urban road construction sequence optimizing methods based on traffic daily variation characteristics.
Background technology
Research in relation to optimization of construction order can trace back in the 1990s, the researcher of early stage uses and managed by being lined up
Traffic delay caused by single construction area in road network is calculated by a series of analytical formulas derived, and with a certain construction
The minimum target of the sequentially corresponding total traffic delay of network, so that it is determined that the priority sequence of construction of construction area.If Fwa et al. is to one
The traffic delay that 3 construction teams complete caused by 10 road upkeep activities within it is calculated, and is calculated using based on heredity
The optimization method of method determines optimum construction sequence；Research object has been expanded to 100 road upkeeps by subsequent Muntasir
Activity and 6 construction teams, and construction period is extended to 1 week, still optimum construction sequence is calculated using genetic algorithm.So
And the section in these Research Hypothesis transportation networks is isolated, when calculating network traffic delay, not from transportation network
Influencing each other between level consideration traffic flow, such as the congestion of adjacent segments are spread.Therefore, it only calculates single road successively
The traffic delay of section can not assess construction influence caused by entire transportation network.
After 2000, start to be studied from the angle of network traffic flow in relation to the problem of optimization of construction order, consider
Distribution situation of the volume of traffic in transportation network.So far, these researchs are several small concern is primarily with construction period
When, all projects under construction the case where being completed within 24 hours.In these researchs, Chang et al. has been respectively adopted dynamic and has handed over
The reduction of fractions to a common denominator, which is matched and had entirely, calculates the traffie distribution under different sequences of construction during the peak hour completely without distribution method, and with
This obtains network overall travel time, so that it is determined that optimal sequence of construction.The scene that they apply is 2 construction teams among 1 day
The situation for completing 6 construction tasks, when problem is described, it is desirable that the construction periods of all construction areas must it is identical or
Construction team must have identical start and end time, however the construction task that different construction teams complete necessarily has certain difference
Different, this constraint is relatively low with actually degree of being consistent, and therefore, their research object has certain limitation.Also there is part research
Person directly calculates the total traffic delay of network using the microscopic traffic simulations such as PARAMICS, VISSIM tool, and uses one
A little heuritic approaches, such as genetic algorithm, ant group algorithm, to determine optimal sequence of construction.Their innovative point mainly carries
A kind of hybrid technology is gone out, i.e., has combined genetic algorithm and traffic simulation software, core is still to have entirely completely without distribution
Or UE traffic assignations, there is no the daily variation characteristics for considering traffic, if long-term optimization of construction order problem is also in this way,
Calculation amount will greatly increase.Tang and Chien determines the traffic transferring amount of time-varying using UE method of traffic assignment, and considers
The factors such as the working efficiency of the transport need of time-varying, variable maintenance cost and construction team to construction section length and sequence of construction into
Row optimization.The model that they are proposed takes into account construction area geometric shape, has accurately calculated a variety of expenses brought by construction
With incrementss, but since the research is directed to small-scale backroad network, this method being applicable in urban traffic network
Property need to be investigated.
However, in practical situation, it is dozens of days that urban road has many construction periods on the net, even hundreds of days
Construction area, current few researchs are paid close attention to this kind of optimization of construction order as unit of day and in the case of construction period is longer and are asked
Topic.The researchs such as Zheng are the case where construction period are some months, and propose the progress UE traffic assignations as unit of month,
Method to calculate traffic delay under different sequences of construction, this method consider individual cost and government cost to obtain simultaneously
Optimal sequence of construction, the comparison considered from influence factor are comprehensive.But when studying constructing for a long time, using the moon as traffic point
There is some shortcomingss for the research carried out with unit.First, there is limitation in research object, in practice and not all construction area
Construction period be all the moon integral multiple, non-integral multiple construction period this method can not be handled.Importantly, this
Method thinks that the distribution of the traffic within the construction period single moon is constantly in equilibrium state, and actually start in new construction or
Person's project under construction was completed in later a period of time, and the flow distribution many places on network are masked in nonequilibrium state, this method
The day that flow distribution converts between nonequilibrium state and equilibrium state becomes process, and compared with truth, error is larger.Lee is for the first time
The daily variation characteristics for considering traffic distribution, embed the method for Used in Dynamic Traffic Assignment to determine optimal alternative road using VISSIM
Diameter, and the traffic delay on network is calculated, so that it is determined that optimum construction sequence.But in the daily variation characteristics for considering traffic distribution
When, author is to change behavior to the path of road user by the form of questionnaire to be investigated, to obtain the roads Ji Tiannei
Traffic transferring ratio between diameter.There is also certain deficiencies for this research method.First, method workload by inquiry
Huge, it requires sample size reasonable, and the selection of sample will have enough representativenesses, due to transfer ratio between different paths
The difference of example, this method are difficult to determine the size of transfer ratio authentic and validly.Secondly, the network model that this method is considered
It encloses and applicability is limited, the magnitude of traffic flow variation being relatively suitble on analysis localized network, when network size is larger, for construction
The influence of area over the entire network cannot carry out Accurate Analysis, especially when have in network multiple construction areas there are when situation will
It can become sufficiently complex.Recently, Gong et al. also studies long-term optimization of construction order problem, and proposes a base
At the beginning of determining each construction area construction in the Bi-level Programming Models of genetic algorithm.Although they are come as unit of day
Calculate whole network on all travelers total trip be delayed, but the daily magnitude of traffic flow be still distributed by UE it is calculated,
There is no the behavioral characteristics day by day for considering traffic flow on network, and there is no essence is different from aforementioned research.This Authors of Science Articles and institute
Research team consider the bounded rationality behavior of traveler in daily traffic environment, it is proposed that based on accumulation prospect theory
The long-term optimization of construction order model of urban road of UE traffic assignations under (Cumulative Prospect Theory) frame, and
The influence factors such as quantity of construction team are analyzed in reference point and network to traveler.Although the paper is as unit of day
Traffic delay caused by bounded rationality traveler in constructing for a long time is calculated, but the calculating of the volume of traffic is still based on special
UE states, do not account for traffic flow evolution daily variation characteristics, therefore, research need further to go deep into it is perfect.
Other than the studies above, in order to assess the traffic delay caused by construction, more specially it is developed needle
To the business optimization software of road construction sequential optimization, due to these softwares be from where construction area street or local traffic
Network level carries out impact analysis, and using fairly simple, the traffic department of several state government of the U.S. is all asked for sequence of construction
Topic has developed the optimization analysis tool based on tables of data.Although these softwares are more convenient when using, due to only from construction
Project level or local street level rough estimate where area adversely affect caused by construction, not from the entire network of communication lines
Network layers surface analysis traffic delay, to carry out the optimization of construction order of multiple construction areas on network.Such as QuickZone and STEAM
(Surface Transportation Efficiency Analysis Model), which all only simply has evaluated on section, to be had
Without the traffic delay under two scenes in the presence of construction area, consideration is not other caused by traffic congestion is spread closes on path
On traffic delay.In addition, also Maryland State Software, Oregon Software, Oklahoma
Also all there is above-mentioned shortcoming in Software, Ohio Software, SMITE etc. similar software, these softwares.In order to
Traffic impact analysis is solved only from single item perspective rather than this defect of whole network angle, the traffic administration in the U.S. and section
The worker of grinding develops a kind of entitled " construction area influence and Policy evaluation tool (Work zone Impacts and
Strategies Evaluation, WISE) " software, can from transportation network level carry out optimization of construction order, but its
The daily variation characteristics of construction period traffic flow are not accounted in matter yet.
Invention content
In order to overcome the disadvantages mentioned above of the prior art, the present invention to propose a kind of urban road based on traffic daily variation characteristics
Optimization of construction order method becomes method of traffic assignment to obtain friendship daily on road network when carrying out optimization of construction order using day
Flux.This method can describe the Day-to-day variability feature of construction background lower network traffic flow, and more truly reflection construction starts
Gradual evolutionary process of the flow from nonequilibrium state to equilibrium state at the end of or.And on this basis, it calculates by construction infection
Network total impedance incrementss in the entire period are come by comparing the size of different sequence of construction lower network total impedance incrementss
Assess the superiority-inferiority of sequence of construction.
The technical solution adopted by the present invention to solve the technical problems is：A kind of urban road based on traffic daily variation characteristics
Optimization of construction order method, includes the following steps：
Step 1: becoming the parameter involved by Dynamic Traffic Assignment Model and genetic algorithm initialization day；
Step 2: generating the initial feasible solution (sequence of construction) for meeting initial population quantitative requirement；
Step 3: becoming traffic with every other day construction time is evolved into analytic process, it is to adapt to object function proposed by the present invention
Function is spent, the fitness of feasible solution is calculated；
Step 4: judging whether practical iterations meet the iterations requirement of setting, if it is satisfied, then generating optimal
Solution stops calculating；If not satisfied, then entering step five；
Step 5: generating new feasible solution, it is then back to step 3.
Compared with prior art, the positive effect of the present invention is：
The method of the present invention considers the daily variation characteristics of traffic, can describe construction period traffic flow by nonequilibrium state to balance
State evolution process can further increase computational accuracy, be more in line with truth.
Description of the drawings
Examples of the present invention will be described by way of reference to the accompanying drawings, wherein：
Fig. 1 is the construction stage to illustrate schematic diagram；
Fig. 2 is chromosome structure schematic diagram.
Specific implementation mode
Present invention assumes that the ability to work of all construction teams is all identical, and a construction team can only simultaneously apply one
It constructs in work area.In network G, influence of the road closed construction to traffic can be divided into two stages：First, being in the construction time
Between directly affect the stage, second is that indirect influence stage after the completion of construction.In the construction process, the presence in road construction area
Cause the traffic capacity to decline, increases so as to cause network traffic impedance, the increase phenomenon of this traffic impedance is deposited by construction area
What is directly contributed.Therefore, this influence is known as directly affecting for construction by the present invention.After construction is completed, although
There is no a presence of construction area, but there is still a need for the regular hours can be only achieved equilibrium state, during this period, network traffic for traffic distribution
Impedance is still changing, and this influence is not directly resulted in by construction, and the present invention is referred to as the indirect influence constructed.
The present invention considers the sum of the impedance of above-mentioned two stage generation, and with network total impedance incrementss caused by construction
For the object function of model, the flow in model on all sections, which meets, becomes traffic evolution rule day, to always applying for sequence of construction
Also there is certain limitation in the work period.Accordingly, it is considered to which the urban road construction sequential optimization model of traffic daily variation characteristics is as follows：
S.T.
Wherein, P (j) indicates network total impedance incrementss caused by sequence of construction j；I indicates i-th of construction stage；tiTable
Show the t days in i-th of construction stage；TiFor the construction period of i-th of construction stage；TD indicates longest construction period；E is to apply
Reach number of days required when equilibrium state after the completion of work；Link flow vector when for the t days in i-th of construction stage；
Link flow vector, works as t when for the t-1 days in i-th of construction stageiWhen=1,For (i-1)-th (i>1, as i=1,Indicate the link flow vector before construction starts) link flow vector in the construction stage when last day；It is i-th
The t days link flow direction vectors in construction stage are calculated according to the distribution of the traffic capacity of corresponding construction stage；x0Expression is applied
Link flow vector before work starts；C () is link proportion vector, is calculated using Bureau of Public Road's function；dr,sIndicate OD
To r, the transport need between s is fixed value；It indicates in i-th of construction stage at the t days, connects OD to r, between s
The flow of path k；Indicate that connection OD is to r before construction starts, the flow of path k between s；It indicates if section a is even
OD is met to r, on the path k between s, otherwise value 1 is 0.
Object function (1) in this model consists of two parts, first part indicate construction caused by direct impedance and
Connect the size of impedance；Second part indicates that generated network total impedance, the difference of the two are in the same time without under construction background
For the network total impedance incrementss caused by construction.(2) are constrained to indicate to become traffic evolution condition, tool day under construction infection background
Body can refer to formula (10)-(12) and calculate；What constraint (3) was expressed is the limitation to total construction period under a certain sequence of construction；About
The meaning that beam (4)-(9) indicate is similar with classical UE models constraint, and expression is that link flow, path flow and traffic need to
Relationship between asking.
The day that He et al. is proposed, which becomes Dynamic Traffic Assignment Model, to be indicated by formula (10).
xt+1=xt+α·(yt+1-xt) (10)
In formula, α (0<α≤1) it is step-length；xtLink flow vector when being the t days；xt+1Section stream when being the t+1 days
Amount vector；yt+1The vector of link flow change direction when decide the t+1 days is solved by formula (11).
minλc(xt)'yt+1+(1-λ)D(xt,yt+1) (11)
In formula, λ is positive scale parameter, and 0<λ<1；c(xt) it is link proportion vector；D(xt,yt+1) it is current road segment stream
Measure vector xtWith target flow vector yt+1Distance.
To current road segment flow vector xtWith target flow vector yt+1Distance formula (12) is used when being calculated.
In formula, a indicates certain a road section；L indicates section set；Indicate the flow of section a at the t days；It indicates to determine
The directional flow of section a changes in flow rate at the t+1 days；ca(w) impedance function for indicating section a, using Bureau of Public Road
Function is calculated.
It should be noted that in the model of the present invention, if front and back two days construction stages do not change, c (xt)
For the t days actual link proportion vectors；If front and back two days construction stages change, c (xt) be the t days flows under
Corresponding link proportion vector under one construction stage background.
The first half of formula (11) is a linear programming problem, i.e. the feelings in a determining link proportion vector distribution
Under condition, keep the total impedance of whole network minimum.Substantially, which is exactly that find every one impedance between OD pairs minimum
Path, and all transport needs are assigned on shortest path, this with to have entirely completely without Dynamic Traffic Assignment Model be of equal value.Become from day
For on traffic characteristics, traveler is always intended to select the path trip of impedance minimum, but in practice since each OD is to it
Between optimal path may be not unique, if only using the magnitude of traffic flow on shortest path as target flow without being controlled, meeting
Day change traffic evolutionary process is set not meet very much reality.When pursuing shortest path, due to factors such as living habit, personal likes,
Traveler is reluctant to make some changes for being no advantage to oneself, even if the traffic capacity in some sections changes, he
Can also select in whole path that most of and oneself is accustomed to identical section and changes the trip of fraction section, to reduce
The fluctuation of flow.Therefore, the latter half of formula (11) has meant that the selection custom characteristic of traveler.
Herein, " construction stage " indicate road passage capability state, i.e., when have in Traffic Net new construction appoint
Business start or at the end of, construction by the current generation is transferred to next stage.One " construction stage " start or at the end of road
The traffic capacity distribution of section can change, and change so as to cause traffic impedance on road network is made.As shown in Figure 1, being applied at 3
When crew completes 4 construction tasks, according to the sequence of construction given in figure, it may appear that 5 construction stages.It can significantly see
Go out, the boundary before and after these construction stages, there are existing construction tasks to terminate on network, new construction task starts shows
As.Here by taking construction stage 1 and construction stage 2 as an example, why there is the phenomenon that being changed from construction stage 1 to the construction stage 2,
It is because the task of construction area 1 has been completed, the traffic capacity decline phenomenon caused by road closed has obtained extensive herein
Multiple, this changes the distribution of the traffic capacity in whole network.In addition the construction stage 5 in figure has been not present on network and has applied
Work phenomenon, here in order to be consistent with above-mentioned definition, also as a stage of construction.
The solution procedure of urban road construction sequential optimization model is as follows：
(1) it initializes.The step mainly determines the parameter become day involved by Dynamic Traffic Assignment Model and genetic algorithm.I.e. really
The geometry topological structure of road, the traffic capacity, free running time, OD are determined to quantity and corresponding transport need, construction position
It sets, iteration step length, related coefficient, initial population quantity, iterations, crossover probability and mutation probability etc..
(2) initial feasible solution (sequence of construction) is generated.Algorithm is used based on natural number coding mode of inheritance to each construction
Area numbers respectively, and uses 0 as the line of demarcation of different construction team's tasks.Copy Evolution in biology, the present invention is with one
Chromosome indicates that a feasible solution, Fig. 2 give chromosome structure when Liang Ge construction teams undertake several construction tasks
Figure.In this step, the initial feasible solution number for meeting initial population quantitative requirement should be generated.
(3) fitness of feasible solution is calculated.It determines the corresponding construction stage situation of each feasible solution in population, and uses day
Become Dynamic Traffic Assignment Model (10)-(12) and calculates the corresponding day change volume of traffic of each feasible solution, it is total to further obtain network
Impedance incrementss.The numerical value meaning of this model objective function is the size adversely affected by construction, and target function value is bigger
Illustrate to adversely affect caused by construction it is bigger, be genetic to follow-on probability just answer it is smaller.But according to genetic algorithm
Rule of iteration, higher its of fitness are genetic to that follow-on possibility is bigger, and therefore, the fitness function of this model takes target letter
Several inverses, i.e. 1/P (j).
(4) convergence judges.Judge whether practical iterations meet the iterations requirement of setting, if it is satisfied, then
Optimal solution is generated, stops calculating；If not satisfied, continuing in next step.
(5) new feasible solution is generated.According to calculated fitness in step (3), using the method for the ratio of adaptation selection
Determine the individual in next-generation population, the individual inheritance for keeping fitness higher is bigger to follow-on chance.Meanwhile in order to subtract
Minor issue converges to the possibility of locally optimal solution, rational probability should be used to carry out part the individual that parent generates and reflect formula friendship
Fork reverses the operations such as variation, and the individual in filial generation is made to constantly update, to increase the diversity of solution.After generating new feasible solution,
Return to step (3).
Claims (6)
1. a kind of urban road construction sequence optimizing method based on traffic daily variation characteristics, it is characterised in that：Include the following steps：
Step 1: becoming the parameter involved by Dynamic Traffic Assignment Model and genetic algorithm initialization day；
Step 2: generating the initial feasible solution for meeting initial population quantitative requirement；
Step 3: calculating the fitness of feasible solution；
Step 4: judge whether practical iterations meet the iterations requirement of setting, if it is satisfied, then optimal solution is generated,
Stop calculating；If not satisfied, then entering step five；
Step 5: generating new feasible solution, it is then back to step 3.
2. the urban road construction sequence optimizing method according to claim 1 based on traffic daily variation characteristics, feature exist
In：The parameter includes the geometry topological structure of road, the traffic capacity, free running time, OD to quantity and corresponding traffic
Demand, construction zone position, iteration step length, related coefficient, initial population quantity, iterations, crossover probability and mutation probability.
3. the urban road construction sequence optimizing method according to claim 2 based on traffic daily variation characteristics, feature exist
In：When generating initial feasible solution, each construction area is numbered respectively using based on natural number coding mode of inheritance, and is made with 0
For the line of demarcation of different construction team's tasks, a feasible solution is indicated with item chromosome.
4. the urban road construction sequence optimizing method according to claim 3 based on traffic daily variation characteristics, feature exist
In：The method of fitness that feasible solution is calculated described in step 3 is：Determine the corresponding construction stage feelings of each feasible solution in population
Condition, and the corresponding day change volume of traffic of each feasible solution is calculated using Dynamic Traffic Assignment Model is become day, it further obtains network and always hinders
Anti- incrementss take the inverse of object function as fitness function.
5. the urban road construction sequence optimizing method according to claim 4 based on traffic daily variation characteristics, feature exist
In：Become day Dynamic Traffic Assignment Model into：
xt+1=xt+α·(yt+1-xt)
In formula, α (0<α≤1) it is step-length；xtLink flow vector when being the t days；xt+1Link flow when being the t+1 days to
Amount；yt+1The vector of link flow change direction when being the t+1 days, is obtained by following equations：
minλc(xt)'yt+1+(1-λ)D(xt,yt+1)
In formula, λ is positive scale parameter, and 0<λ<1；c(xt) it is link proportion vector；D(xt,yt+1) be current road segment flow to
Measure xtWith target flow vector yt+1Distance, be calculated using following formula：
In formula, a indicates certain a road section；L indicates section set；Indicate the flow of section a at the t days；Expression determines t+1
It when section a changes in flow rate directional flow；ca(w) impedance function of section a is indicated.
6. the urban road construction sequence optimizing method according to claim 5 based on traffic daily variation characteristics, feature exist
In：Calculate network total impedance incrementss method be：
(1) object function of the urban road construction sequential optimization model based on traffic daily variation characteristics is determined：
(2) bound for objective function is determined：
Condition one,
Condition two,
Condition three,
Condition four,
Condition five,
Condition six,
Condition seven,
Condition eight,
Wherein, P (j) indicates network total impedance incrementss caused by sequence of construction j；I indicates i-th of construction stage；tiIndicate i-th
The t days in a construction stage；TiFor the construction period of i-th of construction stage；TD indicates longest construction period；E is to have constructed
Reach number of days required when equilibrium state after；Link flow vector when for the t days in i-th of construction stage；It is i-th
Link flow vector when the t-1 days in a construction stage；For the t days in i-th of construction stage link flow direction vectors；
x0Indicate that construction starts preceding link flow vector；C () is link proportion vector；dr,sOD is indicated to r, the traffic between s needs
It asks；It indicates in i-th of construction stage at the t days, connects OD to r, the flow of path k between s；Indicate that construction starts
Preceding connection OD is to r, the flow of path k between s；Indicate if section a in connection OD to r, on the path k between s, take
Value is 1, is otherwise 0.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810446757.1A CN108647825B (en) | 2018-05-11 | 2018-05-11 | Urban road construction sequence optimization method based on traffic daily variation characteristics |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810446757.1A CN108647825B (en) | 2018-05-11 | 2018-05-11 | Urban road construction sequence optimization method based on traffic daily variation characteristics |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108647825A true CN108647825A (en) | 2018-10-12 |
| CN108647825B CN108647825B (en) | 2022-01-28 |
Family
ID=63754587
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810446757.1A Active CN108647825B (en) | 2018-05-11 | 2018-05-11 | Urban road construction sequence optimization method based on traffic daily variation characteristics |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108647825B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110866654A (en) * | 2019-11-22 | 2020-03-06 | 深圳市综合交通设计研究院有限公司 | Construction scheme determination method, device and equipment considering traffic influence |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060253311A1 (en) * | 2005-05-09 | 2006-11-09 | Watao Yin | Maintenance event planning and scheduling for gas turbines |
| CN102750427A (en) * | 2012-07-23 | 2012-10-24 | 中国地质大学（武汉） | Urban traffic planning simulation method and system based on multi-agent activity model |
| CN103150913A (en) * | 2013-02-07 | 2013-06-12 | 东莞中国科学院云计算产业技术创新与育成中心 | Dynamic self-adapting traffic signal control apparatus and method |
| US20150073686A1 (en) * | 2013-09-09 | 2015-03-12 | International Business Machines Corporation | Traffic control agency deployment and signal optimization for event planning |
| CN105117800A (en) * | 2015-08-28 | 2015-12-02 | 国网天津市电力公司 | Method for optimizing power transmission and transformation project construction network plan on basis of genetic algorithm |
| CN107450426A (en) * | 2017-08-01 | 2017-12-08 | 中国建筑第八工程局有限公司 | Foundation pit construction deformable statistical analysis method and system |
-
2018
- 2018-05-11 CN CN201810446757.1A patent/CN108647825B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060253311A1 (en) * | 2005-05-09 | 2006-11-09 | Watao Yin | Maintenance event planning and scheduling for gas turbines |
| CN102750427A (en) * | 2012-07-23 | 2012-10-24 | 中国地质大学（武汉） | Urban traffic planning simulation method and system based on multi-agent activity model |
| CN103150913A (en) * | 2013-02-07 | 2013-06-12 | 东莞中国科学院云计算产业技术创新与育成中心 | Dynamic self-adapting traffic signal control apparatus and method |
| US20150073686A1 (en) * | 2013-09-09 | 2015-03-12 | International Business Machines Corporation | Traffic control agency deployment and signal optimization for event planning |
| CN105117800A (en) * | 2015-08-28 | 2015-12-02 | 国网天津市电力公司 | Method for optimizing power transmission and transformation project construction network plan on basis of genetic algorithm |
| CN107450426A (en) * | 2017-08-01 | 2017-12-08 | 中国建筑第八工程局有限公司 | Foundation pit construction deformable statistical analysis method and system |
Non-Patent Citations (5)
| Title |
|---|
| LANSHANHAN等: "On a link-based day-to-day traffic assignment model", 《TRANSPORTATION RESEARCH PART B: METHODOLOGICAL》 * |
| XIAOZHENGHE等: "Link-based Day-to-day Traffic Assignment Model", 《TRANSPORTATION RESEARCH PART B: METHODOLOGICAL》 * |
| 刘建国等: "地铁区间隧道盖挖逆筑法设计施工方案研究", 《四川建筑》 * |
| 祝俪菱等: "考虑有限理性和认知更新的日变交通分配模型", 《北京交通大学学报》 * |
| 陈玲娟等: "交通事故持续期内行程时间的可靠性研究", 《西南交通大学学报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110866654A (en) * | 2019-11-22 | 2020-03-06 | 深圳市综合交通设计研究院有限公司 | Construction scheme determination method, device and equipment considering traffic influence |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108647825B (en) | 2022-01-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Li et al. | Prediction for tourism flow based on LSTM neural network | |
| Owais et al. | Complete hierarchical multi-objective genetic algorithm for transit network design problem | |
| Chen et al. | Vehicle routing problem of contactless joint distribution service during COVID-19 pandemic | |
| Maier et al. | Ant colony optimization for design of water distribution systems | |
| Lei | A Pareto archive particle swarm optimization for multi-objective job shop scheduling | |
| De Corte et al. | Optimisation of gravity-fed water distribution network design: A critical review | |
| Lima et al. | A mixed load capacitated rural school bus routing problem with heterogeneous fleet: Algorithms for the Brazilian context | |
| Mokhtari et al. | Integration of efficient multi-objective ant-colony and a heuristic method to solve a novel multi-objective mixed load school bus routing model | |
| An et al. | Robust transit network design with stochastic demand considering development density | |
| Miandoabchi et al. | Time-dependent discrete road network design with both tactical and strategic decisions | |
| CN110097218B (en) | Unmanned commodity distribution method and system in time-varying environment | |
| Varia et al. | Application of genetic algorithms for joint optimization of signal setting parameters and dynamic traffic assignment for the real network data | |
| Ambrule et al. | Use of artificial neural network for pre design cost estimation of building projects | |
| Gardner et al. | Robust pricing of transportation networks under uncertain demand | |
| de Araujo Lima et al. | A hybrid approach based on genetic algorithm and nearest neighbor heuristic for solving the capacitated vehicle routing problem | |
| El-Din et al. | Airline passenger forecasting in Egypt (domestic and international) | |
| CN108647825A (en) | Urban road construction sequence optimizing method based on traffic daily variation characteristics | |
| Yaldi et al. | Forecasting origin-destination matrices by using neural network approach: A comparison of testing performance between back propagation, variable learning rate and levenberg-marquardt algorithms | |
| Hajibabaei et al. | Pareto-optimal design of water distribution networks: an improved graph theory-based approach | |
| Köksalan et al. | An evolutionary approach to generalized biobjective traveling salesperson problem | |
| Duell et al. | Implications of volatility in day-to-day travel flow and road capacity on traffic network design projects | |
| Haas et al. | A parsimonious heuristic for the discrete network design problem | |
| Ma et al. | Integrating logistic regression with ant colony optimization for smart urban growth modelling | |
| CN110457012A (en) | Multiple attribute decision making (MADM) software for sustainable transport network design | |
| Yang et al. | Multi-Objective Distribution Model and Algorithm for Online Shopping Express Logistics. |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |