CN107958304A - It is a kind of to take into account performance improvement and the pavement preservation and renovation scheduling method of budget effectiveness - Google Patents
It is a kind of to take into account performance improvement and the pavement preservation and renovation scheduling method of budget effectiveness Download PDFInfo
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Abstract
Performance improvement and the pavement preservation and renovation scheduling method of budget effectiveness are taken into account the invention discloses a kind of, the equipment of the method includes the memory module of deposit map data information and into data processing module, established according to road network and two step of scheduling obtains result, can efficiently and comprehensive method for solving can significantly save the time, improve the work efficiency of manager, sound assurance is provided for further carry out of follow-up decision work, is safeguarded for selection that is scientific and reasonable and optimizing and provides foundation with renovation plan.
Description
Technical Field
The invention relates to the field of traffic, in particular to a pavement maintenance and renovation scheduling method.
Background
Road pavement maintenance and renovation are among the most expensive activities in the management of transportation infrastructure. The construction of the transportation infrastructure has a powerful propulsion effect on the development of the economy of China and is a powerful guarantee for the smooth performance of economic activities. However, as the amount of road construction increases, a large amount of already constructed road surfaces inevitably lose, and the problems of maintenance and renovation of the road surfaces are faced. The road section and the time of maintenance, how to plan the maintenance plan and the selected maintenance measures, etc. are all the problems that need to be considered by the manager.
The traffic students often construct and solve two types of models based on different mastered information and different targets, the roads are divided into different grades according to the road conditions, and maintenance plans of each grade of road surface every year are formulated. The first type is the budget planning problem. When the budget information is unknown, the road condition on the road network level or an independent road area level is ensured to meet the requirement, and the maintenance and renovation cost in the planning period is minimized. The calculation result can be used for a decision maker to determine the actual budget level. The second category, the budget allocation problem, minimizes the cost of use or maximizes the utility of maintenance and refurbishment without exceeding the budget after the budget information is known.
The existing double-target pavement maintenance and renovation model method is lack of a solution scheme capable of simultaneously ensuring solving efficiency and comprehensiveness. Currently, there are two representative types of solutions to this problem. The integer programming model can efficiently solve an accurate solution when the problem scale is not large, and the solution time is exponentially increased along with the expansion of the problem scale; the genetic algorithm widely used cannot ensure to obtain the optimal solution within a limited time due to the nature of the genetic algorithm, and the weighting method serving as another special genetic algorithm cannot ensure to obtain the complete pareto optimal solution. The scale of the problem of timing schedule maintenance and renovation of the dual-target pavement is often large, and the completeness of the solution has a large influence on the decision, so that a model and an algorithm which take efficiency and the accuracy of the solution into consideration should be designed.
Disclosure of Invention
The invention aims to overcome the problems and provides a pavement maintenance and renovation scheduling method which has performance improvement and budget effectiveness, and when a road maintenance and renovation plan is prepared, the method has the double goals of lowest cost and maximized performance, and can provide richer information for a manager to make a more reasonable decision.
The invention provides a pavement maintenance and renovation scheduling method considering performance improvement and budget utility, wherein the equipment of the method comprises a storage module for registering map data information and a data processing module, and the method is characterized by comprising the following steps:
firstly, road network establishment is carried out, functions and road surface conditions of all roads in an area are marked through a data processing module, the roads are divided into S types according to the functions, and then an in-area road set S = {1,2 \8230 =, S } and a road surface condition set I = {1,2 \8230;, I } are obtained;
secondly, the total length L of each road is counted by a data processing module in time sequence arrangement S Its planning period T, the most efficient but expensive maintenance and renovation measures M ∈ M = {1,2 \8230;, M }, the cost C incurred in the year T for the adoption of the measure M for the road of the class s of unit length smt And when the measure m is applied to the s-th road, the conversion rate P of the road surface condition from i to j is obtained sijm And a ratio X of s-class roads with road surface condition i of which the road surface condition of the measure m received at the t year is simt The proportion z of the road in the optimal condition during planning 1 And annual average maintenance and refurbishment costs z 2 Satisfy the relationship of
The initial constraint condition of the road surface condition is satisfied
The constraint condition of the road surface condition conversion relation satisfies
The constraint condition of budget satisfies
Wherein, B t Is the upper budget available in the t year;
the constraint condition of the optimal pavement proportion requirement meets
Wherein X * The road surface is the requirement of the lowest proportion of the road surfaces under the conditions of 1 and the like in a road network;
the constraint condition of the feasible interval of the decision variable is satisfied
The data processing modules respectively have z 1 、z 2 And obtaining a time sequence arrangement result for the objective function.
Further, in the scheduling step, a parameter method is used to obtain the scheduling result according to the following steps:
first, initializing, the data processing module converts the target function into
Wherein, w 1 、w 2 The weights of performance and cost in this utility function, respectively; k is a radical of max Is the upper limit of the iteration times; w is a 1 ＝1-ε、w 2 (= ε or w) 1 ＝ε，w 2 1-epsilon is an initial weight coefficient assignment, and epsilon is a small enough number which satisfies that epsilon is more than or equal to 0 and less than or equal to 1; in the case of k =1, the data processing module introduces the parameter w = (w) 1 ,w 2 ) Obtaining the result (x) 1 ，x 2 )；
Second step, parameter generation, new weight parameter w = (w) 1 ,w 2 ) Satisfy the requirement of
WhereinThe data processing module then compares the result (x) 1 ，x 2 ) Deleting from the first-in first-out form;
thirdly, checking results, and substituting the new weight w into the initialization step by the data processing module to calculate to obtain a new optimal solution x;
the fourth step, if x = x 1 Or x = x 2 Terminating the step; otherwise, the neighboring solution (x) 1 ，x)(x，x 2 ) Storing the solution into a form, storing the adjacent pareto optimal solution in the form to be used for subsequent interval segmentation work, and updating k = k +1 until k>k max Or terminates when the form is empty.
Further, since the function has been transformed into the classical linear programming problem, the result (x) obtained by the following steps is obtained by the simplex method as follows 1 ，x 2 )：
In a first step, the data processing module obtains an initial feasible basis B = (p) 1 ,p 2 ,…p m ) Calculating the initial base feasible solutionCurrent value of objective functionAnd all the number of tests
Second, the data processing module checks all the check numbers σ j J =1,2, \8230n, if all the test numbers σ j If the current base is more than or equal to 0, the current base is the optimal solution, and iteration is stopped;
if it isLet σ be k ＝max{σ j |σ j >, 0}, when B is -1 p k When the solution is less than or equal to 0, no optimal solution exists, and iteration is stopped; when B is present -1 p k >, 0 seasonBy x k In place of x r Obtaining a new base, obtaining a feasible solution and a judgment number of the new initial base, and executing the step again;
data processing module reinitialize w 1 ＝ε，w 2 = 1-epsilon, obtainedPerforming steps i and ii;
the data processing module will obtain the result (x) 1 ，x 2 ) Storing the first-in first-out list in the storage module and repeating the step.
Drawings
FIG. 1 is a flow chart of the present invention;
fig. 2 shows a road condition transformation matrix according to various measures of the invention.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the technical scheme is further explained below by combining the figures.
As shown in the figure, the road surface with improved performance and budget utilityThe maintenance and renovation scheduling method, the road category S only comprises one type. The road condition I is divided into two levels of 1,2, wherein the level 1 is better than the level 2, and the proportion of the level 1 is 70 percent and the proportion of the level 2 is 30 percent respectively. Planning year is 1 year, budget B 1 =90 minimum requirement X for proportion of road surface in condition of 1 or the like in road network * =90%. The maintenance measures are divided into 1 renovation and 2 maintenance. The road condition conversion matrix under different measures is shown in table 1.
X 11 +X 12 ＝0.7 (10)
X 21 +X 22 ＝0.3 (11)
100X 11 +100X 12 ≤90 (12)
1X 11 +0.8X 12 +0.9X 21 ≥0.9 (13)
0≤X 11 ≤1 (14)
0≤X 12 ≤1 (15)
0≤X 21 ≤1 (16)
0≤X 22 ≤1 (17)
The first iteration:
step 1: an initial solution. Setting an upper limit k of iteration times max And (5). When w is 1 ＝1，w 2 =0, having z 1 = (0.95,90). When w is 1 ＝0，w 2 =1, has z 2 = (0.90,65). Will (z) 1 ,z 2 ) The neighboring solution form is stored.
And 2, step: and generating new parameters. a is a 1 ＝65-90＝-25，a 2 0.95-0.90=0.05. New w 1 ＝1.002，w 2 ＝-0.002。
And 3, step 3: and (5) generating and checking a solution. Will be new w 1 ＝1.002，w 2 Substituting the model with = -0.002 to obtain z 3 ＝z 1 = (0.95,90), there are no other pareto optimal solutions in the interval, and (z) will be 1 ,z 2 ) Moving out adjacent statement list。
And 4, step 4: criteria for termination of the calculation: the neighboring solution form is empty, all pareto optimal solutions have been found, and the computation terminates.
After 1 iteration, z is obtained 1 ＝(0.95,90)，z 2 = (0.90,65) i.e. in this case the pareto optimal solution present in the interval is the value of the two extreme cases.
The method can be used for rapidly determining the pareto optimal solution in the interval, obtaining a comprehensive solution set, ensuring the solving speed and providing comprehensive and rapid reference information for a manager so as to make a decision.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are given by way of illustration of the principles of the present invention, and that various changes and modifications may be made without departing from the spirit and scope of the invention as defined by the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (3)
1. A pavement maintenance and renovation scheduling method with performance improvement and budget utility, the device of the method comprises a storage module for storing map data information and a data processing module, and the method is characterized by comprising the following steps:
1) Establishing a road network, marking functions and road surface conditions of all roads in an area through a data processing module, classifying the functions into S types according to the functions, and then obtaining an intra-area road set S = {1,2.., S } and a road surface condition set I = {1,2.., I };
2) Time sequence arrangement, data processing module counts total length L of each type of road S It is associated with a planning period T, the most efficient but expensive maintenance and renovation measures M e M ∈ M = {1,2.., M }, the cost C incurred in the year T for taking the measure M for a road of unit length s class smt And when the measure m is applied to the s-th road, the conversion rate P of the road surface condition from i to j is converted sijm And a proportion X of s-class roads with a road surface condition i of which the road surface condition of the measure m is accepted at the time of t year simt The proportion z of the road in the optimal condition during the planning period 1 And annual average maintenance and refurbishment costs z 2 Satisfy the relationship of
The initial constraint condition of the road surface condition is satisfied
The constraint condition of the road surface condition conversion relation satisfies
The budget constraint condition is satisfied
Wherein, B t Is the upper budget available in the t year;
the constraint condition of the optimal pavement proportion requirement meets
Wherein X * The road surface is the requirement of the lowest proportion of the road surfaces under the conditions of 1 and the like in a road network;
the constraint condition of the feasible interval of the decision variable is satisfied
Data processing modules respectively using z 1 、z 2 And obtaining a time sequence arrangement result for the objective function.
2. The method of claim 1, wherein the scheduling step comprises the step of obtaining the scheduling result, and comprises:
a) Initialization, the data processing module converts the objective function into
Wherein, w 1 、w 2 Performance and cost weights, respectively; k is a radical of max Is the upper limit of the iteration times; w is a 1 ＝1-ε、w 2 = ε or w 1 ＝ε，w 2 1-epsilon is an initial weight coefficient assignment, and epsilon is a small enough number which satisfies that epsilon is more than or equal to 0 and less than or equal to 1; in the case of k =1, the data processing module introduces the parameter w = (w) 1 ,w 2 ) Obtaining the result (x) 1 ，x 2 )；
b) Parameter generation, new weight parameter w = (w) 1 ,w 2 ) Satisfy the requirement of
WhereinThe data processing module then compares the result (x) 1 ，x 2 ) Deleting from the first-in first-out form;
c) Checking the result, and substituting the new weight w into the initialization step by the data processing module for calculation to obtain a new optimal solution x;
d) If x = x 1 Or x = x 2 Terminating the step; otherwise, the neighboring solution (x) 1 ，x)(x，x 2 ) Storing the form, and updating k = k +1 until k>k max Or terminates when the form is empty.
3. The method of claim 2, wherein the data processing module obtains the result (x) by performing the following steps 1 ，x 2 )：
i) The data processing module obtains an initial feasible basis B = (p) 1 ,p 2 ,...p m ) Calculating the initial base feasible solutionCurrent value of objective functionAnd all check numbers σ j ,j＝1,2,...,n,
ii) the data processing module checks all the check numbers σ j J =1, 2.. Ang., n, if all the test numbers σ j If the current base is more than or equal to 0, the current base is the optimal solution, and the iteration is stopped;
if it isLet σ be k ＝max{σ j |σ j >, 0}, when B is -1 p k When the solution is less than or equal to 0, no optimal solution exists, and iteration is stopped; when B is present -1 p k >, 0 seasonBy x k In place of x r Obtaining a new base, obtaining a feasible solution and a judgment number of the new initial base, and re-executing the step;
data processing module reinitialize w 1 ＝ε，w 2 = 1-epsilon, obtainedPerforming steps i and ii;
the data processing module will obtain the result (x) 1 ，x 2 ) Storing the first-in first-out list in the memory module and repeating the steps.
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