KR20100076374A - Decision-making method for selecting cost-effective optimal retrofit method based on uncertainty - Google Patents

Abstract

PURPOSE: A decision-making method for selecting cost-effective optimal retrofit method based on uncertainty is provided to support optimal decision making in consideration of quantitative cost efficiency when making a decision related to selection of the best retrofit method. CONSTITUTION: Relative economic efficiency is evaluated in consideration of uncertainty about an alternative satisfying absolute economic efficiency(S102). Relative performance considering uncertainty about the alternative is evaluated(S104). Cost efficiency considering uncertainty using the evaluated relative profitability and relative performance is evaluated(S105). A decision-making factor for qualitative evaluation is drawn(S107). A quantitative decision-making factor and a quantitative decision-making factor are determined(S108).

Description

Decision-making method for selecting cost-effective optimal retrofit method based on uncertainty}

The present invention relates to a decision-making method for selecting a reinforcement method, and more particularly, in a decision-making method related to selecting an optimal reinforcement method for maintenance of a social infrastructure, cost-effective reinforcement method based on uncertainty. It is about the decision-making method of selecting the.

In the period of high growth after the 1970s, the construction itself was the main concern, but after the mid-1990s, the interest and recognition of the maintenance of infrastructure was collapsed due to the collapse of bridges and other multi-use structures during construction or public use. This was uplifted.

Since then, many efforts and developments have been made for the safe and rational maintenance of infrastructures. Recently, maintenance has been based on pre-established strategies that go beyond the measures of problems that may occur in the maintenance of infrastructures. Efforts are underway.

As one of these studies, Korean Patent Application No. 2006-30899 (filed April 05, 2006) discloses an invention entitled "Method for Establishing Optimal Maintenance Strategy for Infrastructure Based on Life Cycle Performance and Cost". Is disclosed.

In the case of bridges among social infrastructures, the present invention provides a reliability index and state by selecting a deterioration factor for each member and a reinforcing reinforcement alternative for the corresponding deterioration factor determined through statistical analysis of the maintenance history of similar bridges when the bridge information is given. Life cycle performance evaluation step of estimating performance change over time by introducing an index; A life cycle cost estimation step of estimating user costs through a regression model developed for estimating bridge information and road user costs, and performing analysis for estimating maintenance cost information for each member from the bridge maintenance history; And optimally maintain the optimal tradeoff solution automatically using the goodness-of-fit function of the genetic algorithm to resolve conflicting multi-purpose combination optimization problems between the life-cycle performance and cost using the results of the life-cycle performance evaluation stage and the life-cycle cost assessment stage. By including the management scenario generation step, it is possible to provide the annual optimal maintenance scenario automatically or at the system level as well as the absence level according to the manager's constraints.

However, these methods are intended to establish a maintenance strategy for a specific period in the future, and are not intended to establish a maintenance strategy at this time. In addition, the process is very complicated for beginners who are not experts, takes a lot of time to analyze, and requires a dedicated interpretation program for analysis. Therefore, front-line practitioners such as the Ministry of Land, Transport and Maritime Affairs and local national road management offices There is a problem that it is difficult to apply. In addition, the method proposed in the patent considers only performance and cost in order to establish an optimal maintenance strategy, but in practice there are a number of cases other than such cases, there is a problem that the practitioner is less efficient for everyday use.

In addition, the weight determination or weighted product evaluation through analytical stratification is a general decision-making technique, but the determination of the grade of each decision factor is made qualitatively, and the probabilistic exists in estimating the cost and performance of alternatives. There is a problem that the reliability is poor because it does not reflect the characteristics.

The technical problem to be solved by the present invention to solve the above problems, in the decision-making related to the selection of the optimal reinforcement method for the maintenance of the infrastructure infrastructure, taking into account the uncertainty of the rating of each alternative to the decision factor (Rank It is to provide a decision-making method for quantitatively evaluating).

Another technical problem to be achieved by the present invention is to provide a decision-making method by which a maintenance subject can reasonably select a reinforcement method by quantitative decision making and comprehensive decision-making when making a decision regarding the selection of a reinforcing method of a maintenance subject. It is to.

As a means for achieving the above-described technical problem, the decision-making method for selecting a cost-effective reinforcement method based on the uncertainty according to the present invention, a) as a quantitative indicator, relative economic feasibility considering the uncertainty of the alternative that satisfies absolute economics Evaluating; b) as a quantitative indicator, assessing relative performance taking into account uncertainty for alternatives that meet absolute economics; c) evaluating cost effectiveness taking into account uncertainty using the evaluated relative economics and relative performance; d) deriving decision factors for performing a qualitative assessment other than the quantitative indicators; e) determining weights of the quantitative decision factor and qualitative decision factor using analytical stratification; And f) calculating a weighted average value of each alternative using a weighted average method, and using the weighted average value as an indicator of decision making, wherein the decision is based on a quantitative decision based on a quantitative performance evaluation result and the quantitative performance evaluation. It is characterized by the comprehensive decision making of the results and qualitative evaluation results.

In this case, the quantitative decision making is performed by generating a relative economic index and a performance index probabilistically through a simulation technique for alternatives satisfying absolute economic feasibility, and then calculating the cost effectiveness of the reinforcement method using the cost-effectiveness of each alternative. By calculating the probability of exceeding the mean value of all alternatives, it can be used as a basis for decision making.

Here, the absolute economic feasibility is estimated by comparing the estimated cost of each alternative with the allocated budget, and the probability analysis of the absolute economic feasibility assumes a normal distribution of the reinforcement construction cost for each reinforcement method and maintains the alternatives evaluated by the maintenance subject. The probability of exceeding the maintenance budget is calculated using the degree of uncertainty in the management cost.

Here, the relative economics of step a) is the sum of direct costs, indirect costs and user costs, and an alternative may be a reinforcement method.

In this case, the probability evaluation of the relative economic efficiency of step a) may be evaluated by comparing each alternative (reinforcement method) with the overall average for the alternatives satisfying the constraints on the budget.

Here, the relative performance in consideration of the uncertainty of step b) can be evaluated through whether the infrastructure which has improved performance through the reinforcement method can maintain the performance in the long term and whether the reinforcement method itself exhibits the target performance.

Here, the cost efficiency of step c) may be calculated based on the ratio of relative performance and relative economics in consideration of uncertainty.

In this case, the cost efficiency grade of step c) may be calculated by comparing the average cost effectiveness of the alternatives satisfying the absolute economic analysis with the cost efficiency of each alternative.

According to the present invention, in the decision related to the selection of the optimal reinforcement method for the maintenance of the infrastructure, it is possible to support the optimal decision making in consideration of quantitative cost efficiency.

According to the present invention, the maintenance subject may reasonably select the reinforcement method by quantitative decision making and comprehensive decision making when making a decision regarding the selection of the reinforcing method of the maintenance subject.

According to the present invention, it is possible to reduce the maintenance budget in the long term by selecting the optimal reinforcement method under a given environment at the time of decision-making related to the reinforcement work of the maintenance subject.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art may easily implement the present invention. As those skilled in the art would realize, the described embodiments may be modified in various different ways, all without departing from the spirit or scope of the present invention.

First, the decision making method related to selecting an optimal reinforcing method according to an embodiment of the present invention is largely composed of two steps, that is, a quantitative decision making process and a comprehensive decision making process.

The first quantitative decision-making method uses stochastic estimates of the relative economics (sum of direct and user costs) and the performance of the alternatives (reinforcement) for alternatives that satisfy absolute economics. After calculating the cost effectiveness of the reinforcement method, it is the process of calculating the probability that the cost efficiency of each alternative exceeds the average value of all alternatives and using this as the basis for decision making.

The second comprehensive decision-making is based on the Analytic Hierarchy Process, where qualitative decision-making factors such as social, aesthetic and political factors are in addition to quantitative decision-making factors (cost-efficiency). A weighted product is determined by multiplying each of the weights by the rank of the qualitative decision factor determined by the maintenance agent and the respective weights, summing the weighted product values for each alternative, and then evaluating the alternatives using these values. It is a process.

In other words, the decision-making method for selecting a cost-effective reinforcement method based on uncertainty according to an embodiment of the present invention analyzes the relative economics, relative performance, and relative cost-efficiency of the reinforcement method by a quantitative evaluation method in consideration of uncertainty, In addition, when additional qualitative decision factors exist, weights are determined by analytical stratification to induce comprehensive judgment, and then decision is made by combining qualitative and quantitative evaluation results.

1 is a schematic configuration diagram of a system for performing a decision method for selecting a cost-effective reinforcement method based on uncertainty according to an embodiment of the present invention.

Referring to FIG. 1, an upper system including a decision-making method for selecting an uncertainty-based cost-effective reinforcement method according to an embodiment of the present invention is an asset management system 100, and an asset management strategy establishment system 110 and a doctor's decision. And a decision system 120 and a database 130, wherein the decision system 120 includes a cost efficiency evaluator 121, a qualitative performance evaluator 122, and a method selection unit 123. May be, but is not limited to. Here, the database 130 may include a facility performance history database 131, a reinforcement effect DB 132, a reinforcement cost DB 133, and a facility asset management DB 134.

The data collected through the inspection and diagnosis of the social infrastructure 200, for example, the first to Nth bridges 201, 202, and 203 may be stored in the facility performance history database 131 in the database 130. In addition, the asset management strategy establishment system 110 in the asset management system 100 establishes an asset management strategy (reinforcement priority) based on the data in the database 130, and the reinforcement work is performed in the decision system 120. Decision-making such as optimal reinforcement method, reinforcement method, and reinforcement company decision is performed for necessary facilities. The user (maintenance agent) of decision system 120 requests statistical data on the performance and cost of the alternative from the databases 132 and 133 for the cost effectiveness assessment 121 of the alternative, thereby quantifying the alternative. Phosphorus evaluation is possible. After that, if there is a qualitative performance evaluation factor, the qualitative performance evaluation 122 is performed, and after performing the method selection 123, the maintenance subject according to the analysis result of the decision system 120 is performed. Manage the social infrastructure 200.

The decision system 120 according to an embodiment of the present invention performs a decision method for selecting a cost-effective optimal reinforcement method in consideration of uncertainty due to the maintenance of a social infrastructure. Specifically, 1) as a quantitative indicator. Assess the relative economics of uncertainty for alternatives that meet absolute economics, and 2) assess the relative performance of uncertainty for alternatives that satisfy absolute economics, and 3) the relative economics and relative Performance is used to assess cost effectiveness taking into account uncertainties, 4) to derive decision factors that need to be evaluated qualitatively rather than quantitative indicators, and 5) to use quantitative decision factors and qualitative decision making using analytical stratification. 6) Weighted average of each alternative is calculated by using weighted average method. In this case, the decision is made by combining the quantitative performance evaluation results with the qualitative evaluation results. In this case, the quantitative decision factor and the qualitative decision factor may be adjusted according to the decision of the decision maker.

Here, the absolute economic feasibility is estimated by comparing the estimated cost of each alternative with the allocated budget. In other words, the budget serves as an absolute comparison value of the reinforcement method and a constraint that determines the adequacy of the reinforcement. Absolute economics are used as an indicator to determine how economical the reinforcement method is compared to the budget. In addition, the absolute economic feasibility is calculated through an uncertainty analysis, because the cost of construction estimated by the contractor includes various uncertainties, so that there is an error in the estimation of the rough construction cost, which may unexpectedly exceed the budget. Means to calculate the probability.

In addition, the probability analysis of absolute economic feasibility assumes a normal distribution of reinforcement construction costs by construction method, and exceeds the maintenance budget by using the degree of uncertainty (standard deviation, coefficient of variation) of the maintenance cost of the alternatives evaluated by the maintenance body. Calculate the probability of doing For example, as shown in Equation 1, further analysis, for example, an economic evaluation and a performance evaluation, may be performed for alternatives where the budget excess probability does not exceed 10%.

,

는 각 대안의 평균 보강비용과 표준편차를 의미한다. 이때, 다음의 수학식 2에 도시된 바와 같이, 예산초과 확률 10%는 신뢰성지수로 표현하면 1.28에 해당하는 값이다. 그리고 표준정규분포함수

(평균=0, 분산=1인 정규분포함수)는 다음의 수학식 3과 같게 된다.here,

,

Means average reinforcement cost and standard deviation of each alternative. In this case, as shown in Equation 2 below, the probability of exceeding the budget of 10% is a value corresponding to 1.28 when expressed as a reliability index. And standard normal distribution function

(Normal distribution function with mean = 0 and variance = 1) becomes as shown in Equation 3 below.

Therefore, a reliability index of 1.28 or less, as assessed by the maintenance budget and the average price and uncertainty of the alternatives, means that the probability of budget overrun exceeds 10%. can do.

In addition, the probability assessment of relative economics also provides a relative comparison between the reinforcement method and the overall mean of each alternative for alternatives that meet the constraints of the preceding government budget, for example, equations (1) and (2). Can be evaluated.

For example, calculate the probability that each alternative would exceed the average of all alternatives, and compare the probability of excess of 0-100% with a table separated by 11 intervals, as shown in FIG. Can be obtained quantitatively.

2 is a diagram showing the relationship between the alternative reliability index, the average excess probability, and the score.

Referring to FIG. 2, the economic index 10 means that the probability of exceeding the average is less than about 9%, the economic index 5 is equivalent to the average, and the economic index 0 is about 91% that the probability of reinforcing the alternative is above the average. Means that.

At this time, assuming that the cost of each alternative is a normal distribution, the statistical parameters (average value, variance) of the reinforcement method may calculate the average value by the following equation (4), and calculate the variance by the equation (5).

Then, the reliability index at which the alternatives will exceed the average value is determined as shown in Equation 6 below, and equations 7 and 8 can be used to calculate the probability of each alternative exceeding the average value and the rank of each alternative. have.

, n은 대안의 수를 나타낸다.here,

, n represents the number of alternatives.

On the other hand, the economics of reinforcement method should consider not only direct construction cost but also indirect cost incurred by performing reinforcement work. In the case of indirect costs, it may be composed of vehicle operation costs, travel time costs, etc. caused by the delay and congestion caused by the reinforcement work. In other words, the indirect cost is the amount of money valued by the cost of the vehicle passing through and the time value of the driver and passenger in the vehicle because it takes much time compared to the conventional one to travel the same distance due to delay and congestion. .

For example, road traffic varies by time of day, so delays in lane control will also vary by time of day. In other words, if the reinforcement work is carried out during rush hour when the traffic is heavy, more indirect cost will be incurred. In addition, it is obvious that the duration of the renovation work will also depend on the characteristics of the construction method and the resource investment plan. In order to take this into consideration, the maintenance subject receives a work plan from the reinforcement bidder, and the user cost estimation program for analyzing the life cycle cost of the previously developed bridge (Ministry of Construction and Transportation / Korea Facility Safety Technology Authority, 2004) or the aforementioned patent It can be calculated through the method disclosed in the application number 2006-30899, etc., the specific procedure for the economic evaluation described above is as shown in FIG.

FIG. 3 is an operation flowchart specifically illustrating an economic evaluation process in a decision method for selecting an uncertainty-based cost-effective reinforcement method according to an embodiment of the present invention.

Referring to Figure 3, the analysis sequence for decision making is a basic step consisting of maintenance budget allocation (S11), bid request (S12), bid request receipt (S13) and bid request analysis (S14), and economic analysis (S15) And an analysis and evaluation step consisting of a decision (S16) is performed, the decision system 120 according to an embodiment of the present invention inputs a budget (S21) in response to the maintenance budget allocation (S11), Corresponding to the bid request analysis (S14) to establish the reinforcement construction cost, uncertainty degree and construction plan for each company (S22), and analyzes the budget excess probability as described above (S23). Thereafter, the decision system 120 checks the feasibility of the alternative (S24) and performs the overhead evaluation (S25) and the economic evaluation (S26) as described above.

On the other hand, the relative performance in consideration of uncertainty is evaluated based on whether the infrastructure, for example, the bridge, which has improved performance through reinforcement method, can maintain such performance in the long term, and whether the reinforcement method itself achieves the target performance. At this time, it is key to evaluate how long the performance improvement that is exhibited when the reinforcement method is applied to the deteriorated structure is maintained for the bridge which has improved performance in the long term. In other words, it means the expected remaining time (year) until the target performance is exceeded, and the time (year) until the target performance is exceeded becomes a factor of performance evaluation between the respective methods.

In addition, whether the reinforcement method itself exhibits the target performance means that the target performance index is satisfied. Therefore, if the target performance can be assumed to be a normal distribution and the average performance is achieved but there is an uncertainty of 10%, then the target performance coefficient P can be expressed in the form of N (1.0, 0.1). . If we have the same uncertainty and only 90% of the target performance is expected on average, it can be expressed as N (0.9, 0.1).

The indicator combines the performance of the reinforcement method with the target performance and the possibility of maintaining the long-term performance of the reinforcement method. In other words, it is possible to calculate the average deterioration rate of the aged bridge in which the reinforcement work is performed through the possibility of maintaining the long-term performance of the reinforcement method input by the user, and modify the initial intercept value of the average deterioration rate straight line to show the target performance of the reinforcement method. By doing so, the performance of the reinforcement method can be modeled as the possibility of maintaining long-term performance (guaranteed year) considering the average deterioration rate. This process is performed according to the procedure of FIG. 4, and finally the result shown in FIG. 5 can be obtained.

FIG. 4 is a flowchart illustrating a process of estimating the extension of common life for evaluating relative performance in consideration of uncertainty in a decision method for selecting an uncertainty-based cost-effective reinforcement method according to an embodiment of the present invention, and FIG. 4 is a diagram illustrating the probabilistic modeling of the performance of the reinforcement method according to the calculation of the common life extension amount of 4.

Referring to FIG. 4, in the process of calculating the common life extension amount for the relative performance evaluation considering the uncertainty, first, the common life extension amount of the reinforcement method is input (S41), and the average degradation rate of the aged facility is calculated ( S42), but is corrected according to whether the reinforcement method is exhibited (S43), as shown in Figure 5, to modify the initial intercept value of the average deterioration rate straight line whether or not to exhibit the target performance of the reinforcement method. Thereafter, the common life extension amount is calculated through the simulation (S45) (S45).

On the other hand, the cost efficiency according to the embodiment of the present invention is calculated as shown in the following Equation 9 through the ratio of the relative performance and relative economics previously analyzed in consideration of the uncertainty. That is, Equation (9) shows, for example, an index for evaluating how long the life of an aged bridge can be extended with a unit cost.

In addition, cost efficiency can be calculated by considering the uncertainty by comparing the average cost efficiency of the alternatives that satisfy the absolute economic analysis with the cost efficiency of each alternative in the same way as the previous economic evaluation.

Meanwhile, comprehensive decision making according to an embodiment of the present invention is an analytic hierarchy process when there are qualitative decision factors such as social factors, aesthetic factors, and political factors in addition to quantitative decision factors (cost-effectiveness). : AHP) is used to determine the weight of the decision factor, calculate the weighted product by multiplying each of the weights by the rank of the qualitative decision factor determined by the maintenance agent, and adding up the weighted products for each alternative. This value will lead to a series of procedures for evaluating alternatives.

FIG. 6 is a diagram illustrating an evaluation criterion of relative importance for relative comparison between decision factors, and FIG. 7 is a diagram illustrating a hierarchical structure of an analytical stratification method (AHP).

Referring to FIG. 7, analytical stratification (AHP) compares only two objects or criteria at a time to rule out inconsistencies that may arise in considering multiple alternatives simultaneously. As a result, it was used as a method of evaluating the whole, but in the embodiment of the present invention, the relative importance (weight) between the quantitative decision factor (cost efficiency) and the qualitative decision factor (aesthetic, social, political, etc.) Will be used to make the decision.

In addition, this analytic stratification method can be used to determine normalized weights through relative comparison between decision factors. Relative comparisons between decision factors may be made by individual comparison methods, where a comparison matrix is constructed for individual comparisons, and an evaluation scale as shown in FIG. 6 may be used for evaluation. Such AHP evaluation scales allow construction managers to reflect their subjective judgment, experience, and knowledge in decision making in an intuitive and natural way.

After the comparison on the comparison matrix, the relative weighting factors of the various components are derived. Specifically, the relative weights of the two-level constituents for each of the top-level elements are calculated by treating the values of the comparison matrix as vector components. The sum of the weights of the alternatives is determined by summing each weight associated with that alternative through a path from the top level to the bottom level of the hierarchy. Finally, the priority of each alternative can be obtained by multiplying the weight determined through the hierarchy with the weight of the higher level criteria. Here, the mathematical basis for determining the weight may refer to "The Analytic Hierarchy Process (Saaty) 1980".

Meanwhile, FIG. 8 is a flowchart illustrating a decision method for selecting a cost-effective reinforcement method based on uncertainty according to an exemplary embodiment of the present invention.

Referring to FIG. 8, in the decision-making method for selecting an uncertainty-based cost-effective reinforcement method according to an embodiment of the present invention, first, a maintenance budget is input (S101), and alternatives considering uncertainties are input (S102). . These alternatives are specified in the database.

After that, it is checked whether the constraint is satisfied (S103). Here, constraints are indicative of the absolute value of applying the method, unlike the factors of decision making. For example, as mentioned above, the maintenance budget should be excluded from the alternative, because no matter how good the performance of the proposed reinforcement method can be, if it exceeds the maintenance budget. And even though the reinforcement method is excellent, there is no company that can apply the reinforcement method because the technology level of the reinforcement company is low, or the reinforcement method itself is very economical, but the specification of the reinforcement method is not maintained. However, it would not be feasible to select such a process if it is difficult to implement. Such constraints are placed before the decision-making system analyzes the cost effectiveness, and only alternatives that meet the constraints are selected for evaluation.

Next, the relative economics considering the uncertainty of the alternatives satisfying the absolute economics are evaluated, and the relative performance considering the uncertainty of the alternatives satisfying the absolute economics is evaluated (S104).

Next, the cost efficiency considering the uncertainty is evaluated using the relative economic and relative performance that has been performed (S105).

Next, it is checked whether the qualitative evaluation is to be performed in addition to the quantitative indicators (S106), and when the qualitative evaluation is to be performed, the above-mentioned qualitative decision factor is derived and input (S107).

Next, the weights of the quantitative decision factors and the qualitative decision factors are determined using the analytic stratification method (S108). Next, the weighted average value of each alternative is calculated using the weighted average method, and the alternatives are evaluated. In operation S109, the result of the evaluation of the alternative is used as an indicator of decision making (S110). In this case, the quantitative decision factor and the qualitative decision factor may be adjusted or adjusted according to the decision of the decision maker.

As a result, the decision-making method for selecting a cost-effective reinforcement method based on uncertainty according to an embodiment of the present invention analyzes the relative economics, relative performance, and relative cost-efficiency of the reinforcement method by a quantitative evaluation method considering uncertainty. In the case of additional qualitative decision factors, weights are determined by analytical stratification method to induce a comprehensive judgment, and then decision is made by combining qualitative performance evaluation results and quantitative evaluation results.

FIG. 9 is a detailed flowchart illustrating a decision algorithm in a decision method for selecting an uncertainty-based cost-effective reinforcement method according to an embodiment of the present invention.

Referring to FIG. 9, in the decision making method for selecting an uncertainty-based cost-effective reinforcement method according to an embodiment of the present invention, the decision algorithm first inputs reinforcement costs, traffic conditions, and reinforcement method performance for each alternative ( S201), the simulation is performed according to the alternative reinforcement cost, traffic conditions and reinforcement method performance for each alternative (S202).

Next, the average reinforcement cost, average overhead cost, and average performance of the alternatives are calculated (S203), and the average cost efficiency of each alternative is evaluated as described above (S204).

Next, the number of simulations is increased once (S205), and then, it is evaluated whether the value (average-simulation for each alternative) is smaller than zero (S206).

Next, if the (average-alternative simulation) value is less than 0, Icount is increased by 1 (S207). At this time, if the (average-alternative simulation) value is not less than zero, Icount is not increased. Here, Icount is a variable indicating whether or not the various samples obtained by simulation with the statistical characteristics of each alternative pass the conditional expression of S206.

Next, it is checked whether the simulation number N is greater than the preset simulation number (S208). If N is larger than the preset simulation number, Pf = Icount / N is set (S209). At this time, if N is not greater than the predetermined number of simulations, the process returns to step S205 of increasing the number of simulations once.

Next, the score is calculated in comparison with the table (S210), and then, a cost-effective reinforcement method is selected (S211).

Meanwhile, FIG. 10 is a diagram illustrating a calculation of a comprehensive score according to a decision method for selecting an uncertainty-based cost-effective reinforcement method according to an embodiment of the present invention.

As shown in FIG. 10, the decision making method for selecting a cost-effective reinforcement method based on uncertainty according to an embodiment of the present invention includes a weighting factor for each evaluation criterion determined as described above, and a reinforcement plan for each decision criterion. The overall score is calculated by multiplying the ranks and adding the values for each alternative. As a result, it can be seen that the alternative score was determined to be higher than the alternative 1 and the alternative 2 according to the quantitative cost efficiency, provided that each alternative does not exceed 10%.

The foregoing description of the present invention is intended for illustration, and it will be understood by those skilled in the art that the present invention may be easily modified in other specific forms without changing the technical spirit or essential features of the present invention. will be. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive.

The scope of the present invention is shown by the following claims rather than the above description, and all changes or modifications derived from the meaning and scope of the claims and their equivalents should be construed as being included in the scope of the present invention. do.

1 is a schematic configuration diagram of a system for performing a decision method for selecting a cost-effective reinforcement method based on uncertainty according to an embodiment of the present invention.

2 is a diagram illustrating the relationship between an alternative reliability index, an average excess probability, and a score.

FIG. 3 is an operation flowchart specifically illustrating an economic evaluation process in a decision method for selecting an uncertainty-based cost-effective reinforcement method according to an embodiment of the present invention.

FIG. 4 is a flowchart illustrating a process of estimating a common life extension for a relative performance evaluation considering uncertainty in a decision method for selecting an uncertainty-based cost-effective reinforcement method according to an exemplary embodiment of the present invention.

FIG. 5 is a diagram illustrating stochastic modeling of the reinforcement method performance according to the calculation of the common life extension amount of FIG. 4.

6 is a diagram illustrating criteria for evaluating relative importance for relative comparison between decision factors.

FIG. 7 is a diagram illustrating the hierarchical structure of the Analytic Hierarchy Process (AHP).

8 is an operation flowchart of a decision method for selecting a cost-effective reinforcement method based on uncertainty according to an embodiment of the present invention.

9 is a detailed flowchart illustrating a decision algorithm in a decision method for selecting a cost-effective reinforcement method based on uncertainty according to an embodiment of the present invention.

10 is a diagram illustrating a calculation of a comprehensive score according to a decision method for selecting an uncertainty-based cost-effective reinforcement method according to an embodiment of the present invention.

<Brief Description of Drawings>

100: asset management system 110: asset management strategy planning system

120: Decision Making System 121: Cost Effectiveness Assessment Unit

122: qualitative performance evaluation unit 123: construction method selection unit

130: database (DB) 131: facility performance history DB

132: reinforcement effect DB 133: reinforcement cost DB

134: Facility asset management DB 200: Social infrastructure

201, 202, 203: bridge

Claims (8)

a) assessing relative economics, taking into account uncertainty, for alternatives that meet absolute economics, as quantitative indicators; b) as a quantitative indicator, assessing relative performance taking into account uncertainty for alternatives that meet absolute economics; c) evaluating cost effectiveness taking into account uncertainty using the evaluated relative economics and relative performance; d) deriving decision factors for performing a qualitative assessment other than the quantitative indicators; e) determining weights of the quantitative decision factor and qualitative decision factor using analytical stratification; And f) calculating the weighted average of each alternative using the weighted average method and using it as an indicator of decision making; Including, The decision making method is a decision method for selecting a cost-effective reinforcement method based on uncertainty, characterized in that the decision making is performed based on a quantitative decision based on a quantitative performance evaluation result and a comprehensive decision on the quantitative performance evaluation result and a qualitative evaluation result. . The method of claim 1, The quantitative decision-making process generates stochastic economic and performance indicators probabilistically through simulation techniques for alternatives that satisfy absolute economic feasibility, and then calculates the cost-effectiveness of the reinforcement method. A decision method for selecting a cost-effective reinforcement method based on uncertainty, which is used as a basis for decision making by calculating a probability of exceeding an average value of. The method of claim 2, The absolute economic feasibility is estimated by comparing the estimated cost of each alternative with the allocated budget, and the probability analysis of the absolute economic feasibility assumes a normal distribution of the reinforcement construction costs for each reinforcement method, and the maintenance costs of the alternatives evaluated by the maintenance agent. A decision method for selecting a cost-effective reinforcement method based on uncertainty, wherein the probability of exceeding the maintenance budget is calculated using the estimated degree of uncertainty. The method of claim 1, The relative economics of step a) is the sum of direct costs, indirect costs, and user costs, and the alternative is a reinforcement method. The method of claim 1, The probability evaluation of the relative economic feasibility of step a) is a cost-effective reinforcement method based on uncertainty, which is evaluated by comparing each alternative (reinforcement method) and the total average with respect to the alternatives satisfying the budget constraint. Decision making method for selection. The method of claim 1, The relative performance in consideration of the uncertainty of step b) is evaluated based on whether the social-based structure having improved performance through the reinforcement method can be maintained in the long term and whether the target performance of the reinforcement method itself is achieved. Decision-making method for selecting cost-effective reinforcement methods The method of claim 1, The cost efficiency of step c) is calculated based on the ratio of the relative performance and relative economics in consideration of the uncertainty, the decision method for selecting a cost-effective reinforcement method based on the uncertainty. The method of claim 1, The cost-effectiveness of step c) is calculated by comparing the average cost effectiveness of the alternatives satisfying the absolute economic analysis with the cost efficiency of each alternative.

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