CN106600503A - Data envelopment analysis-based expressway network preventive maintenance efficiency evaluation method - Google Patents
Data envelopment analysis-based expressway network preventive maintenance efficiency evaluation method Download PDFInfo
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Abstract
The invention discloses a data envelopment analysis-based expressway network preventive maintenance efficiency evaluation method. The method includes the following steps that: step 1, based on expressway network preventive maintenance historical data and expressway network maintenance technique evaluation, preventive maintenance schemes are summarized, and maintenance efficiency decision making units are determined; step 2, an expressway network preventive maintenance efficiency evaluation index system is built, input and output indexes are obtained and quantified; and step 3, the relative efficiency values of the expressway network preventive maintenance schemes are calculated and sorted based on data envelopment analysis, and the most effective preventive maintenance scheme can be obtained. According to the data envelopment analysis-based expressway network preventive maintenance efficiency evaluation method of the invention, the maintenance efficiency of different preventive maintenance schemes are evaluated based on an input-output systematic idea, various maintenance influence factors are comprehensively considered and are adopted as input indexes, and road surface use performance change values are adopted as output indexes; a variable returns to scale-based BCC model and a super-efficiency model are built, the relative efficiency values of the decision-making units are obtained; and the relative effectiveness of the expressway network asphalt pavement preventive maintenance schemes is evaluated.
Description
Technical field
The present invention relates to a kind of freeway network bituminous pavement preventive maintenance efficiency based on DEA is commented
Estimate method, belong to highway maintenance planning technology and management domain category, and in particular to a kind of road network preventive maintenance efficiency evaluation
Method.
Background technology
Highway in China construction at present is presented rapid development, just gradually from the stage based on construction to maintenance pipe
Step transition based on reason.How to distribute and use limited fund, make our road network be maintained at a preferable Pavement Performance
And service level, the focus that always Ge great administration sections and research worker pay close attention to.And the quality of pavement maintenance management strategy
Directly affect the input of fund and the improvement of Pavement Condition.To guarantee that the performance road that the limited fund for putting into can be maximum is imitated
Really, it is necessary and far reaching that road pavement maintenance management strategy carries out study on the efficiency.But it is right that most of researcher lays particular emphasis on
The cost benefit of maintenance measure is compared, and seldom has researcher deeply to comment the pavement maintenance management planning formulated in itself
Valency is analyzed.
Freeway network preventive maintenance is in itself a system sex chromosome mosaicism, because preventive maintenance quality is directly affected
Pavement Condition improvement, by traffic flow, Maintenance Machinery, conserves personnel, conserves fund, maintenance measure and temperature humidity
The each side combined influence such as condition.Efficiency evaluation is carried out using road network preventive maintenance scheme as decision package, to conserve traffic
Amount, maintenance work amount and maintenance fund as input pointer, each Pavement Condition sub-indicator changing value as output-index,
The effectiveness of energy road pavement economical analysis of highway maintenance planning is differentiated.And from whole freeway network preventive maintenance scheme
Maximally effective maintenance plan is evaluated, the evaluation index of selection science is needed, rational assessment models are built, using correctly commenting
Estimate method.
The outstanding feature of nonparametric DEA Method (DEA) is need not to assume input-output function relation, directly profit
Determine efficient frontier hyperplane with sample data, and then show that each decision package (DMU) relative efficiency and input redundancy and output are in debt
Specifying information.Thus, with respect to other appraisal procedures, DEA is more objective, scientific, meets freeway network preventative foster
The systematicness assessment of shield is required.
Therefore, design a kind of freeway network preventive maintenance efficiency evaluation method based on DEA be must
Want.
The content of the invention
It is preventative that the technical problem to be solved in the present invention is to provide a kind of freeway network based on DEA
Maintenance efficiency evaluation method, the appraisal procedure can determine maintenance effect from the preventive maintenance programme of freeway network
Rate highest scheme.
To solve the above problems, the technical solution adopted in the present invention is comprised the following steps：
A kind of expressway road network preventive maintenance efficiency evaluation method based on DEA, comprises the steps：
Step 1：Commented according to freeway network preventive maintenance historical data and road network maintenance technology situation
It is fixed, preventive maintenance scheme is concluded, it is determined that maintenance efficiency decision package；
Step 2：Freeway network preventive maintenance efficiency evaluation index system is built, is obtained and is quantified input and output and refer to
Mark；
Step 3：Calculating sequence is carried out to road network preventive maintenance scheme relative efficiency based on DEA, is drawn
Most effective preventive maintenance scheme.
Further, freeway network bituminous pavement preventive maintenance scheme is divided into four classes：I classes are conserved, the maintenance of II classes,
Group III is conserved and the maintenance of IV classes.
Further, the I class maintenance includes mist sealing, reducing agent sealing, and the maintenance of II class includes micro-surface area, opens general envelope
Layer, crushed stone sealing, III class maintenance includes ultrathin overlay, and the maintenance of IV class includes hot-mixed asphaltic concrete cover, milling outrigger location,
Including SMA, AC-13, AC-16, OGFC-10.
Further, the input and output index described in step 2 includes：
(1) volume of traffic X is conserved1:For the annual average daily traffic in Expressway Implementing preventive maintenance measure section, unit
It is pcu/d；
(2) maintenance work amount X2:For Expressway Implementing preventive maintenance section total kilometrage,M is at a high speed
Highway maintenance section sum；LiIt is that preventive maintenance mileage is implemented in the i-th section；
(3) maintenance costs X3:X3=X31+X32+X33+X34, X31- administrative expenditure；X32- maintenance measure cost price,N- maintenance measure species, Ci- maintenance measure unit price；Si- section maintenance area；X33- maintenance labour cost；
X34- Maintenance Machinery takes；Maintenance costs unit is ten thousand yuan；
(4) output index Y1:Y1=PCI-PCI0, PCI- sections are implemented road surface deterioration extent after preventive maintenance measure and are referred to
Number, PCI0Pavement distress before the maintenance of-section, PCI- presses current highway condition state standard JTG H 20-
2007 perform；
(5) output index Y2,Y3,Y4,Y5:Y2=RQI-RQI0；Y3=RDI-RDI0；Y4=SRI-SRI0；Y5=PSSI-
PSSI0, calculating principle is with method with output index Y1。
Further, step 3 specifically includes following steps：
(1) model is set up：
Evaluation model adopts the BCC model variable based on returns to scale of input orientation, and physical planning formula is as follows：
In formula：θ is decision package efficiency value；θ*For efficiency optimization value；ε is the non-Archimedes's dimensionless for introducing；For input and output slack variable；N is decision package sum；M, s are Input and Output Indexes number；xij, yrjRepresent jth
I-th, the r input and output values of individual decision package；λjFor each decision package desired value weight；
(2) preventive maintenance scheme Effective judgement：
Above-mentioned model is solved, optimal solution is drawn；Work as θ*=1, decision package relative efficiency, conversely, relative nullity, if lax
VariableAll it is 0, is then strong relative efficiency decision package, conversely, is weak relative efficiency decision package；
(3) preventive maintenance scheme effectiveness sequence：
First relative nullity decision package is according to efficiency optimization value θ*Size carries out trap queuing；Again by phase in BCC models
Invalid decision package is rejected from reference set, the new super-efficiency model of component is ranked up again to relative efficiency decision package,
Relative nullity decision package is come after relative efficiency decision package；
(4) above-mentioned super-efficiency model is solved, draws optimal solution θ of the model*, it is to refer to other because being evaluated DMU efficiency
What the forward position that DMU is constituted drew, its efficiency value is generally higher than 1；
(5) according to the relative efficiency size for solving, the relative effectiveness ranking results of New Appraisement unit collection are obtained.
Further, it is described again to reject relative nullity decision package in BCC models from reference set, the new super effect of component
Rate model, specifically includes the step of be ranked up again to relative efficiency decision package：
Relative nullity decision package in above-mentioned BCC models is rejected from reference set, for relative efficiency decision package
Build new super-efficiency model:
Minθ*
λ≥0；I=1,2 ..., m；γ=1,2 ..., q；J=1,2 ..., n (j ≠ k)
In formula：θ*For decision package efficiency value；N is decision package sum；M, s are Input and Output Indexes quantity；xij, yrjTable
Show i-th, the r input and output values of j-th decision package；λjFor each decision package desired value weight, wherein, Input and Output Indexes with
The BCC models are consistent.
The positive beneficial effect of the present invention：
The freeway network preventive maintenance efficiency evaluation method based on DEA of the present invention, is at a high speed
The planning effectiveness of the preventive maintenance measure of highway network is estimated.Relative efficiency with input-output as interpretational criteria,
Consider the volume of traffic, maintenance work amount and maintenance fund etc. put into the impact that each sub-indicator of Pavement Performance in Distress improves,
Its evaluation result is more objective deep.
Have an advantageous effect in that：The present invention proposes a kind of to freeway network preventive maintenance scheme efficiency of the practice
The completely new approach of assessment, it is than traditional maintenance measure benefit-cost-ratio appraisal procedure more comprehensively, more objective；Can be right using the method
The preventive maintenance scheme of freeway network carries out effectiveness sequence, is management decision-maker it is determined that during final maintenance plan,
Scientific and effective foundation is provided；The relative nullity analysis of causes can be also carried out to each maintenance plan, proposes to improve.
Description of the drawings
Fig. 1 schemes in detail for the road network preventive maintenance efficiency evaluation flow process of the embodiment of the present invention；
Fig. 2 is the road network preventive maintenance efficiency evaluation index system figure of the embodiment of the present invention.
Specific embodiment
The present invention is expanded on further with reference to embodiments, but is not intended to limit present invention.
Based on the expressway road network preventive maintenance efficiency evaluation method of DEA, implementation steps are included (see figure
1)：
(1) according to freeway network preventive maintenance historical data and road network maintenance technology status assessment, prevention is concluded
Property maintenance plan, it is determined that maintenance efficiency decision package (DMU)：
With Guangdong, inside the province freeway network carries out preventive maintenance scheme efficiency evaluation to the present invention as example.Guangdong Province is high
Fast highway network is crisscross, considers easy availability and target validity of data etc., and the valid data for finally gathering have
158254.(wherein micro-surface area 50320；Mist sealing 19667；Ultra-thin wearing layer 15835；SMA covers 2398；AC-
13 covers 1960 and AC-16 covers 60072 etc.) it is related to Guangdong and has been carried out preventive maintenance measure within 2015 inside the province
15 highway amounts to 1706.3km bituminous pavings.Concrete express highway section maintenance situation is as shown in table 1：
The performance data collection section of table 1 and correspondence preventive maintenance measure
(2) freeway network preventive maintenance efficiency evaluation index system is built, obtains and quantify input and output index
(see Fig. 2)：
With regard to quantification of targets principle and step in foundation description, each input and output desired values of DMU are obtained.Final data is tied
Fruit is shown in Table 2：
The each Input and Output Indexes values of the DMU of table 2
(3) freeway network maintenance relative efficiency is calculated：
DEA requires that all Input and Output Indexes are that positive number and input pointer growth can not cause output-index to reduce.To with
Basic data is processed in upper second step, and " inverse of multiplication process " is carried out to the input pointer volume of traffic, is taken each initial value and is fallen
Number.Show that last efficiency evaluation result is as shown in table 3 using DEAP2.1 computed in software：
The each decision package of table 3 conserves efficiency evaluation value
(4) relative nullity decision package trap queuing and relative efficiency decision package are reevaluated：
Known by table 3, DMU2, DMU3, DMU6, DMU12, DMU14 relative efficiencies, remaining decision package relative nullity.Relatively
The efficiency value θ that invalid unit is tried to achieve according to BCC models*Size, carries out trap queuing, i.e. DMU4>DMU13>DMU5>DMU11>
DMU10>DMU7>DMU15>DMU1>DMU8>DMU9.Relative efficiency decision package carries out efficiency value by building super-efficiency model
Calculate and sort, concrete result of calculation is as shown in table 4：
The relative efficiency unit of table 4 runs the result of calculation of super-efficiency model
Known by table 4, the efficiency value that relative efficiency unit is calculated by super-efficiency model>1, it is right according to result of calculation
Relative efficiency unit carries out again trap queuing：DMU14>DMU6>DM U12>DMU3>DMU2.
(5) interpretation of result：
A. the last ranking results of freeway network maintenance efficiency are：DMU14>DMU6>DMU12>DMU3>DMU2>DMU4>
DMU13>DMU5>DMU11>DMU10>DMU7>DMU15>DMU1>DMU8>DMU9；
B.15 bar implements the highway of preventive maintenance measure, and maintenance efficiency value is illustrated by prevention all more than 0.7
Property maintenance, Pavement Condition is obtained certain improvement；
C. the efficiency value of decision package 9 is minimum, illustrates to take off regular senior middle school's speed maintenance efficiency minimum.Other highways are compared, takes off general
The average daily traffic volume circulation of high speed is maximum, illustrates that the volume of traffic upgrades certain inhibitory action to conserving operational efficiency；
D. decision package 7,10,15 to implement maintenance measures be all micro-surface area, and wherein DMU10 efficiency values are higher, description selection
Preventive maintenance measure need to determine with reference to the link counting, maintenance costs etc.；
E. decision package 2,3,6,12,14 relative other units effectively, illustrates to implement the intensity by force such as SMA, AC-13, AC-16
Maintenance measure can more lift section maintenance efficiency.
The present invention does not limit to above-mentioned embodiment, and those skilled in the art can accordingly make various changes, but any and sheet
Invention equivalent or similar change should be covered within the scope of the invention as claimed.
Claims (6)
1. a kind of expressway road network preventive maintenance efficiency evaluation method based on DEA, it is characterised in that include
Following steps：
Step 1：According to freeway network preventive maintenance historical data and road network maintenance technology status assessment, conclude preventative
Maintenance plan, it is determined that maintenance efficiency decision package；
Step 2：Freeway network preventive maintenance efficiency evaluation index system is built, input and output index is obtained and quantify；
Step 3：Calculating sequence is carried out to road network preventive maintenance scheme relative efficiency based on DEA, is drawn and most have
Effect preventive maintenance scheme.
2. the expressway road network preventive maintenance efficiency evaluation method based on DEA according to claim 1,
It is characterized in that：Freeway network bituminous pavement preventive maintenance scheme is divided into four classes：I classes are conserved, the maintenance of II classes, Group III
Maintenance and the maintenance of IV classes.
3. the expressway road network preventive maintenance efficiency evaluation method based on DEA according to claim 2,
Characterized in that, the I class maintenance includes mist sealing, reducing agent sealing, the maintenance of II class includes micro-surface area, opens general sealing, rubble
Sealing, III class maintenance includes ultrathin overlay, and the maintenance of IV class includes hot-mixed asphaltic concrete cover, milling outrigger location, including
SMA、AC-13、AC-16、OGFC-10。
4. a kind of expressway road network preventive maintenance efficiency evaluation side based on DEA according to claim 1
Method, it is characterised in that the input and output index described in step 2 includes：
(1) volume of traffic X is conserved1:For the annual average daily traffic in Expressway Implementing preventive maintenance measure section, unit is
pcu/d；
(2) maintenance work amount X2:For Expressway Implementing preventive maintenance section total kilometrage,M is highway
Maintenance section sum；LiIt is that preventive maintenance mileage is implemented in the i-th section；
(3) maintenance costs X3:X3=X31+X32+X33+X34, X31- administrative expenditure；X32- maintenance measure cost price,N- maintenance measure species, Ci- maintenance measure unit price；Si- section maintenance area；X33- maintenance labour cost；
X34- Maintenance Machinery takes；Maintenance costs unit is ten thousand yuan；
(4) output index Y1:Y1=PCI-PCI0, Pavement distress after the enforcement preventive maintenance measure of PCI- sections,
PCI0Pavement distress before the maintenance of-section, PCI- presses current highway condition state standard JTG H 20-2007
Perform；
(5) output index Y2,Y3,Y4,Y5:Y2=RQI-RQI0；Y3=RDI-RDI0；Y4=SRI-SRI0；Y5=PSSI-PSSI0,
Calculating principle is with method with output index Y1。
5. a kind of expressway road network preventive maintenance efficiency evaluation side based on DEA according to claim 1
Method, it is characterised in that step 3 specifically includes following steps：
(1) model is set up：
Evaluation model adopts the BCC model variable based on returns to scale of input orientation, and physical planning formula is as follows：
In formula：θ is decision package efficiency value；θ*For efficiency optimization value；ε is the non-Archimedes's dimensionless for introducing；
For input and output slack variable；N is decision package sum；M, s are Input and Output Indexes number；xij, yrjRepresent j-th decision-making
I-th, the r input and output values of unit；λjFor each decision package desired value weight；
(2) preventive maintenance scheme Effective judgement：
Above-mentioned model is solved, optimal solution is drawn；Work as θ*=1, decision package relative efficiency, conversely, relative nullity, if slack variableAll it is 0, is then strong relative efficiency decision package, conversely, is weak relative efficiency decision package；
(3) preventive maintenance scheme effectiveness sequence：
First relative nullity decision package is according to efficiency optimization value θ*Size carries out trap queuing；Again by relative nullity in BCC models
Decision package is rejected from reference set, the new super-efficiency model of component, relative efficiency decision package is ranked up again, with respect to nothing
Effect decision package is come after relative efficiency decision package；
(4) above-mentioned super-efficiency model is solved, draws optimal solution θ of the model*, it is with reference to other DMU structures because being evaluated DMU efficiency
Into forward position show that its efficiency value is generally higher than 1；
(5) according to the relative efficiency size for solving, the relative effectiveness ranking results of New Appraisement unit collection are obtained.
6. a kind of expressway road network preventive maintenance efficiency evaluation side based on DEA according to claim 5
Method, it is characterised in that described again to reject relative nullity decision package in BCC models from reference set, the new super efficiency of component
Model, specifically includes the step of be ranked up again to relative efficiency decision package：
Relative nullity decision package in above-mentioned BCC models is rejected from reference set, is built for relative efficiency decision package
New super-efficiency model:
Min θ*
λ≥0；I=1,2 ..., m；γ=1,2 ..., q；J=1,2 ..., n (j ≠ k)
In formula：θ*For decision package efficiency value；N is decision package sum；M, s are Input and Output Indexes quantity；xij, yrjRepresent the
I-th, the r input and output values of j decision package；λjFor each decision package desired value weight, wherein, Input and Output Indexes with it is described
BCC models are consistent.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108446924A (en) * | 2018-02-09 | 2018-08-24 | 中公高科养护科技股份有限公司 | A kind of predictor method and system of maintenance of surface expense |
| CN112330516A (en) * | 2020-11-03 | 2021-02-05 | 交通运输部科学研究院 | Method and device for generating road surface maintenance plan |
| CN112951378A (en) * | 2021-03-05 | 2021-06-11 | 中国科学院心理研究所 | Method for automatically recommending psychological consultants for visitors |
| CN115271565A (en) * | 2022-09-29 | 2022-11-01 | 中南大学 | DEA-based method, device and equipment for evaluating highway pavement maintenance measures |
| CN117557122A (en) * | 2024-01-11 | 2024-02-13 | 山东路科公路信息咨询有限公司 | Highway maintenance decision analysis method and system based on data relation graph technology |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103606266A (en) * | 2013-06-28 | 2014-02-26 | 长沙理工大学 | Road network traffic improvement scheme efficiency assessment method based on data envelopment analysis |
-
2016
- 2016-11-04 CN CN201610962794.9A patent/CN106600503A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103606266A (en) * | 2013-06-28 | 2014-02-26 | 长沙理工大学 | Road network traffic improvement scheme efficiency assessment method based on data envelopment analysis |
Non-Patent Citations (1)
| Title |
|---|
| 王朝辉等: "基于时段的沥青路面预防性养护时机与对策一体优化研究", 《中国公路学报》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108446924A (en) * | 2018-02-09 | 2018-08-24 | 中公高科养护科技股份有限公司 | A kind of predictor method and system of maintenance of surface expense |
| CN112330516A (en) * | 2020-11-03 | 2021-02-05 | 交通运输部科学研究院 | Method and device for generating road surface maintenance plan |
| CN112330516B (en) * | 2020-11-03 | 2023-08-01 | 交科院检测技术（北京）有限公司 | Method and device for generating highway pavement maintenance plan |
| CN112951378A (en) * | 2021-03-05 | 2021-06-11 | 中国科学院心理研究所 | Method for automatically recommending psychological consultants for visitors |
| CN112951378B (en) * | 2021-03-05 | 2023-11-21 | 中国科学院心理研究所 | Method for automatically recommending psychological consultants for visitor |
| CN115271565A (en) * | 2022-09-29 | 2022-11-01 | 中南大学 | DEA-based method, device and equipment for evaluating highway pavement maintenance measures |
| CN117557122A (en) * | 2024-01-11 | 2024-02-13 | 山东路科公路信息咨询有限公司 | Highway maintenance decision analysis method and system based on data relation graph technology |
| CN117557122B (en) * | 2024-01-11 | 2024-03-22 | 山东路科公路信息咨询有限公司 | Highway maintenance decision analysis method and system based on data relation graph technology |
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