An optimization method for low-carbon foundation treatment solutions

Abstract

The present invention discloses a method for optimizing a low-carbon foundation treatment scheme, comprising the following steps: Step 1, determining six indicators of various foundation treatment construction design schemes; Step 2, calculating six indicator weights, including the following procedures: S21, positive treatment of positive indicators; reverse treatment of negative indicators; S22, calculating the standard deviation of various indicator data after treatment; S23, calculating various conflicting indicators: S24, calculating the objective weight of each indicator; S25, calculating the subjective weight of each indicator; S26, calculating the indicator weight; Step 3, determining the correlation coefficient based on the grey correlation method theory; Step 4, calculating the comprehensive evaluation coefficient; Step 5, determining the construction design scheme with the largest comprehensive evaluation coefficient according to the above calculation results, and then optimizing and adjusting the construction design scheme, so as to obtain a better construction design scheme. The present invention can not only meet the subjective judgment of decision makers, but also take into account the objective and scientific evaluation of each indicator.

Description

Technical Field

[0001] The invention relates to a method for optimizing a low-carbon foundation treatment solution. Background Art

[0002] Ground treatment is an important part of civil engineering, which is crucial to ensure the safety, stability and durability of buildings. When choosing a ground treatment solution, multiple factors need to be considered comprehensively, mainly including economic efficiency, technical rationality, construction technology difficulty, etc.

[0003] In recent years, as green and low-carbon indicators have received more and more attention, the evaluation and optimization of green and low-carbon construction plans have also received widespread attention. How to evaluate and optimize construction plans from a green and low-carbon perspective is very necessary. Most of the existing evaluation and optimization methods only consider carbon emission indicators from a subjective perspective. The weight of the evaluation indicators is overly dependent on the subjective judgment of decision makers. At the same time, it also lacks comprehensive considerations from the aspects of economy, technology, carbon emissions, construction effects, etc., and cannot provide method support for the optimization of low-carbon foundation treatment construction plans at this stage. Summary of the invention

[0004] The purpose of the present invention is to overcome the defects of the prior art and provide an optimization method for low-carbon foundation treatment solutions, which can not only meet the subjective judgment of decision makers, but also take into account the objective and scientific evaluation of various indicators.

[0005] The object of the present invention is achieved by: a method for optimizing a low-carbon foundation treatment solution, comprising the following steps:

[0006] Step 1: Determine the six indicators of various foundation treatment construction design schemes, namely, total cost indicator, construction period indicator, carbon emission indicator, technical feasibility indicator, construction difficulty indicator and treatment efficacy indicator;

[0007] Step 2: Calculate the weights of the six indicators, including the following steps:

[0008] S21, positively processing the positive indicators according to the following formula (1); the positive indicators include: technical feasibility indicators and treatment efficacy indicators;

[0009] X′=(X-Min) / (Max-Min) (1)

[0010] The negative indicators are reversed according to the following formula (2); the negative indicators include: total cost indicator, construction period indicator, carbon emission indicator and construction difficulty indicator;

[0011] X′=(Max-X) / (Max-Min) (2)

[0012] In the above formula (1) and formula (2), X′ is the index data after processing; X is the index data before processing; Max is the maximum number of the index; Min is the minimum number of the index;

[0013] S22, calculate the standard deviation δk of each type of index data after processing according to the following formula (3):

[0014]

[0015] In the above formula (3), N is the total number of X'; μ is the arithmetic mean;

[0016] S23, calculate each conflict index according to the following formula (4):

[0017] Conflict index = ∑(1-r i ) (4)

[0018] In the above formula (4), r is the correlation coefficient. The correlation coefficients of the above six indicators are calculated in pairs according to the following formula (5):

[0019]

[0020] In the above formula (5), x represents the data of indicator 1; represents the average value of the data column of indicator 1; y represents the data of indicator 2; It represents the average value of the data column of indicator 2;

[0021] S24, calculate the objective weight w of each indicator according to the following formula (6): k ;

[0022]

[0023] In the above formula (6), w k is the objective weight of the kth indicator after normalization; C k is the comprehensive information of the kth indicator, calculated according to the following formula (7):

[0024]

[0025] S25, calculate the subjective weight w of each indicator z

[0026] According to the priority diagram method and the evaluation results of the indicator weights at the subjective level of each expert, the average values ​​of the six indicators are calculated, namely the average value of the cost indicator, the average value of the construction period indicator, the average value of the carbon emission indicator, the average value of the technical feasibility indicator, the average value of the construction difficulty indicator and the average value of the treatment efficacy indicator; the average value of each indicator is first calculated, and then the average value is compared according to the size of the average value; when the average value is large, 1 point is obtained, when the average value is small, 0 point is obtained, and when the average values ​​are exactly the same, 0.5 point is obtained, and then the score values ​​of each row are added, and then the added values ​​are normalized to obtain the corresponding subjective weight w of each indicator z ;

[0027] S26, calculate the indicator weight W according to the following formula (8): j

[0028] W j =α*W z +(1-α)W k ,α∈[0,1] (8)

[0029] In the above formula (8), W j is the indicator weight; α is the subjective certainty coefficient, which is selected according to the needs of decision makers;

[0030] Step 3: Determine the correlation coefficient based on the grey correlation method theory, including the following steps:

[0031] S31, take It represents the optimal value of the jth index in the selected construction design scheme; the technical feasibility index and the treatment efficacy index take the maximum value; the total cost index, the construction period index, the carbon emission index, and the construction difficulty index take the minimum value, and the index vector matrix of n+1 construction design schemes is obtained as follows:

[0032]

[0033] S32, normalize the index vector matrix of n+1 construction design schemes

[0034] For total cost index, construction period index, carbon emission index and construction difficulty index,

[0035] For technical feasibility indicators and treatment efficacy indicators, Thus, the standardized indicator vector matrix is ​​obtained as follows:

[0036]

[0037] S33, calculate the correlation coefficient ξ of the indicator vector matrix according to the following formula (9): ij

[0038]

[0039] In the above formula (9), ρ is the resolution coefficient, which is 0.5;

[0040] So we get the correlation coefficient matrix

[0041]

[0042] Step 4: Calculate the comprehensive evaluation coefficient R according to the following formula (10): i

[0043]

[0044] In the above formula (10), R i is the evaluation result of the i-th construction design scheme, R i The larger it is, the higher the correlation between the construction design scheme and the optimal construction design scheme, that is, the better the construction design scheme is;

[0045] Step 5: Determine the comprehensive evaluation coefficient R based on the above calculation results i The largest construction design plan is then optimized and adjusted to obtain a better construction design plan.

[0046] In the above-mentioned optimization method of the low-carbon foundation treatment solution, when performing step 1,

[0047] The total cost indicator is the total cost of the construction design solution;

[0048] The construction period indicator is the total construction period of the construction design plan; the carbon emissions are calculated in accordance with the "Building Carbon Emission Calculation Standard" GB / T 51366-2019;

[0049] The technical feasibility index is a low, medium or high evaluation made by experts based on the actual situation of the construction design plan, with low being 0 points, medium being 0.5 points and high being 1 point;

[0050] The evaluation criteria for the construction difficulty index are divided into five levels: extremely easy (1 point), easy (2 points), medium (3 points), difficult (4 points), and difficult (5 points); the evaluation contents of the construction difficulty index include five aspects: technical difficulty, organizational difficulty, management difficulty, safety difficulty, and environmental difficulty;

[0051] The treatment efficacy index is evaluated by experts based on the overall treatment efficacy of various construction design solutions and is given a score of 0-9, with the larger the score, the better the treatment efficacy.

[0052] The optimization method of the low-carbon foundation treatment scheme of the present invention has the following characteristics: comprehensive consideration is given to the aspects of economy, technology, carbon emissions, construction effect, etc., providing method support for the optimization of the current low-carbon foundation treatment construction scheme, which can not only meet the subjective judgment of decision makers, but also take into account the objective and scientific evaluation of various indicators. DETAILED DESCRIPTION

[0053] The present invention will be further described below in conjunction with the embodiments.

[0054] The optimization method of the low-carbon foundation treatment solution of the present invention comprises the following steps:

[0055] Step 1: Determine the six indicators of various foundation treatment construction design schemes, namely, total cost indicator, construction period indicator, carbon emission indicator, technical feasibility indicator, construction difficulty indicator and treatment efficacy indicator;

[0056] The total cost indicator is the total cost of the construction design solution;

[0057] The construction period indicator is the total construction period of the construction design plan;

[0058] Carbon emissions are calculated in accordance with the Building Carbon Emission Calculation Standard GB / T 51366-2019;

[0059] The technical feasibility index is a low, medium or high evaluation made by experts based on the actual situation of the construction design plan, with low being 0 points, medium being 0.5 points and high being 1 point;

[0060] There are five levels of evaluation criteria for the construction difficulty index: 1 point for extremely easy, 2 points for easy, 3 points for medium, 4 points for difficult, and 5 points for difficult. There are five evaluation contents for the construction difficulty index: technical difficulty, organizational difficulty, management difficulty, safety difficulty, and environmental difficulty.

[0061] The treatment efficacy index is evaluated by experts based on the overall treatment efficacy of various construction design schemes, and is scored from 0 to 9. The larger the score, the better the treatment efficacy.

[0062] Step 2: Calculate the weights of the six indicators, including the following steps:

[0063] S21, positively processing the positive indicators according to the following formula (1); the positive indicators include: technical feasibility indicators and treatment efficacy indicators;

[0064] X′=(X-Min) / (Max-Min) (1)

[0065] The negative indicators are reversed according to the following formula (2); the negative indicators include: total cost indicator, construction period indicator, carbon emission indicator and construction difficulty indicator;

[0066] X′=(Max-X) / (Max-Min) (2)

[0067] In the above formula (1) and formula (2), X′ is the index data after processing; X is the index data before processing; Max is the maximum number of the index; Min is the minimum number of the index;

[0068] S22, calculate the standard deviation δ of each type of index data after processing according to the following formula (3): k

[0069]

[0070] In the above formula (3), N is the total number of X'; μ is the arithmetic mean;

[0071] S23, calculate each conflict index according to the following formula (4):

[0072] Conflict index = ∑(1-r i ) (4)

[0073] In the above formula (4), r is the correlation coefficient. The correlation coefficients of the above six indicators are calculated in pairs according to the following formula (5):

[0074]

[0075] In the above formula (5), x represents the data of indicator 1; represents the average value of the data column of indicator 1; y represents the data of indicator 2; It represents the average value of the data column of indicator 2;

[0076] S24, calculate the objective weight w of each indicator according to the following formula (6): k ;

[0077]

[0078] In the above formula (6), w k is the objective weight of the kth indicator after normalization; C k is the comprehensive information of the kth indicator, calculated according to the following formula (7):

[0079]

[0080] S25, calculate the subjective weight w of each indicator z

[0081] According to the priority diagram method and the evaluation results of the indicator weights at the subjective level of each expert, the average values ​​of the six indicators are calculated, namely the average value of the total cost indicator, the average value of the construction period indicator, the average value of the carbon emission indicator, the average value of the technical feasibility indicator, the average value of the construction difficulty indicator and the average value of the treatment efficacy indicator; the average value of each indicator is first calculated, and then the average value is compared according to the size of the average value; when the average value is large, 1 point is obtained, when the average value is small, 0 point is obtained, and when the average values ​​are exactly the same, 0.5 point is obtained, and then the score values ​​of each row are added, and then the added values ​​are TTL normalized to obtain the corresponding subjective weight w of each indicator z ;

[0082] S26, calculate the indicator weight according to the following formula (8)

[0083] W j =α*W z +(1-α)W k ,α∈[0,1] (8)

[0084] In the above formula (8), W j is the indicator weight; α is the subjective certainty coefficient, which is selected according to the needs of decision makers; generally, the lower the uncertainty of project construction, the larger α is; conversely, the higher the uncertainty of project construction, the smaller α is;

[0085] Step 3: Determine the correlation coefficient based on the grey correlation method theory, including the following steps:

[0086] S31, take It represents the optimal value of the jth index in the selected construction design scheme; the technical feasibility index and the treatment efficacy index take the maximum value; the total cost index, the construction period index, the carbon emission index and the construction difficulty index take the minimum value, and the index vector matrix of n+1 construction design schemes is obtained as follows:

[0087]

[0088] S32, normalize the index vector matrix of n+1 construction design schemes

[0089] For total cost index, construction period index, carbon emission index and construction difficulty index,

[0090] For technical feasibility indicators and treatment efficacy indicators, Thus, the standardized indicator vector matrix is ​​obtained as follows:

[0091]

[0092] S33, calculate the correlation coefficient ξ of the indicator vector matrix according to the following formula (9): ij

[0093]

[0094] In the above formula (9), ρ is the resolution coefficient, which is 0.5;

[0095] So we get the correlation coefficient matrix

[0096]

[0097] Step 4: Calculate the comprehensive evaluation coefficient R according to the following formula (10): i

[0098]

[0099] In the above formula (10), R i is the evaluation result of the i-th construction design scheme, R i The larger it is, the higher the correlation between the construction design scheme and the optimal construction design scheme, that is, the better the construction design scheme is;

[0100] Step 5: Determine the comprehensive evaluation coefficient R based on the above calculation results i The largest construction design plan is then optimized and adjusted to obtain a better construction design plan.

[0101] The technical solution of the present invention is described below with a specific embodiment:

[0102] There are five foundation reinforcement schemes, namely Scheme A, B, C, D, and E. Among them, Scheme A uses ordinary gravel piles for reinforcement; Scheme B uses strong-penetrating gravel piles for reinforcement; Scheme C uses precast piles for reinforcement; Scheme D uses compacted sand piles for reinforcement; and Scheme E uses cast-in-place piles for reinforcement.

[0103] The optimization method of the low-carbon foundation treatment solution of the present invention comprises the following steps:

[0104] Step 1: Determine the six indicators of foundation reinforcement design schemes A, B, C, D, and E, namely, total cost indicator, construction period indicator, carbon emission indicator, technical feasibility indicator, construction difficulty indicator, and treatment efficacy indicator;

[0105]

[0106] The six indicator data of schemes A, B, C, D, and E are calculated as follows:

[0107]

[0108] Step 2: Calculate the weights of the six indicators

[0109] S21, positive indicators are processed positively and negative indicators are processed negatively;

[0110]

[0111] S22, calculate the standard deviation of various index data after processing δ k

[0112] index Technical feasibility Treatment efficacy Cost (yuan / m) <![CDATA[Standard deviation δ k > 0.4472136 0.54772256 0.436171181

[0113] index Construction period (days) <![CDATA[Carbon emissions kgCO 2 / m)]]> Construction difficulty <![CDATA[Standard deviation δ k > 0.234402313 0.462353993 0.4472136

[0114] S23, calculate each conflict index:

[0115] index Technical feasibility Treatment efficacy Cost (yuan / m) Conflict 2.96895188 3.1632264 2.059834111

[0116] index Construction period (days) <![CDATA[Carbon emissions (kgCO 2 / m)]]> Construction difficulty Conflict 1.19052891 2.277422743 2.39761127

[0117] S24, calculate the objective weight w of each indicator k

[0118]

[0119]

[0120] index Construction period (days) <![CDATA[Carbon emissions (kgCO 2 / m)]]> Construction difficulty <![CDATA[Objective weight w k > 0.084689492 0.162006797 0.17055653

[0121] S25, calculate the subjective weight w of each indicator z

[0122]

[0123] S26, calculate the indicator weight W j =α*W z +(1-α)W k ,α∈[0,1]

[0124] α is the subjective certainty coefficient, which is selected according to the needs of decision makers. Generally speaking, the lower the uncertainty of project construction, the larger α is; conversely, the higher the uncertainty of project construction, the smaller α is;

[0125] When α is 0.5, the above calculation scheme is as follows:

[0126]

[0127] Step 3: Determine the correlation coefficient based on the grey correlation method theory and obtain the correlation coefficient matrix:

[0128]

[0129] Step 4: Calculate the comprehensive evaluation coefficient R i ,

[0130] The calculation results are shown in the following table:

[0131] Calculate the correlation coefficient Comprehensive evaluation coefficient Plan A 0.980242236 Plan B 0.866290881 Plan C 0.812267884 Plan D 0.570420348 Plan E 0.785842274

[0132] Step 5: Determine the comprehensive evaluation coefficient R based on the above calculation results i The largest plan, Plan A, is then optimized and adjusted to obtain a better construction design plan.

[0133] The above embodiments are only used to illustrate the present invention, rather than to limit the present invention. Those skilled in the relevant technical field may make various changes or modifications without departing from the spirit and scope of the present invention. Therefore, all equivalent technical solutions should also belong to the scope of the present invention and should be defined by the claims.

Claims

1. A method for optimizing a low-carbon foundation treatment solution, characterized in that: The optimization method comprises the following steps: Step 1: Determine the six indicators of various foundation treatment construction design schemes, namely, total cost indicator, construction period indicator, carbon emission indicator, technical feasibility indicator, construction difficulty indicator and treatment efficacy indicator; Step 2: Calculate the weights of the six indicators, including the following steps: S21, positively processing the positive indicators according to the following formula (1); the positive indicators include: technical feasibility indicators and treatment efficacy indicators; X′=(X-Min) / (Max-Min) (1) The negative indicators are reversed according to the following formula (2); the negative indicators include: total cost indicator, construction period indicator, carbon emission indicator and construction difficulty indicator; X′=(Max-X) / (Max-Min) (2) In the above formula (1) and formula (2), X′ is the index data after processing; X is the index data before processing; Max is the maximum number of the index; Min is the minimum number of the index; S22, calculate the standard deviation δ of each type of index data after processing according to the following formula (3): k In the above formula (3), N is the total number of X'; μ is the arithmetic mean; S23, calculate each conflict index according to the following formula (4): Conflict index = ∑(1-r i ) (4) In the above formula (4), r is the correlation coefficient. The correlation coefficients of the above six indicators are calculated in pairs according to the following formula (5): In the above formula (5), x represents the data of indicator 1; represents the average value of the data column of indicator 1; y represents the data of indicator 2; It represents the average value of the data column of indicator 2; S24, calculate the objective weight w of each indicator according to the following formula (6): k ; In the above formula (6), w k is the objective weight of the kth indicator after normalization; C k is the comprehensive information of the kth indicator, calculated according to the following formula (7): S25, calculate the subjective weight w of each indicator z According to the priority diagram method and the evaluation results of the indicator weights at the subjective level of each expert, the average values ​​of the six indicators are calculated, namely the average value of the cost indicator, the average value of the construction period indicator, the average value of the carbon emission indicator, the average value of the technical feasibility indicator, the average value of the construction difficulty indicator and the average value of the treatment efficacy indicator; the average value of each indicator is first calculated, and then the average value is compared according to the size of the average value; when the average value is large, 1 point is obtained, when the average value is small, 0 point is obtained, and when the average values ​​are exactly the same, 0.5 point is obtained, and then the score values ​​of each row are added, and then the added values ​​are normalized to obtain the corresponding subjective weight w of each indicator z ; S26, calculate the indicator weight W according to the following formula (8): j W j =α*W z +(1-α)W k ,α∈[0,1] (8) In the above formula (8), W j is the indicator weight; α is the subjective certainty coefficient, which is selected according to the needs of decision makers; Step 3: Determine the correlation coefficient based on the grey correlation method theory, including the following steps: S31, take It represents the optimal value of the jth index in the selected construction design scheme; the technical feasibility index and the treatment efficacy index take the maximum value; the total cost index, the construction period index, the carbon emission index, and the construction difficulty index take the minimum value, and the index vector matrix of n+1 construction design schemes is obtained as follows: S32, normalize the index vector matrix of n+1 construction design schemes For total cost index, construction period index, carbon emission index and construction difficulty index, For technical feasibility indicators and treatment efficacy indicators, Thus, the standardized indicator vector matrix is ​​obtained as follows: S33, calculate the correlation coefficient ξ of the indicator vector matrix according to the following formula (9): ij In the above formula (9), ρ is the resolution coefficient, which is 0.5; So we get the correlation coefficient matrix Step 4: Calculate the comprehensive evaluation coefficient R according to the following formula (10): i In the above formula (10), R i is the evaluation result of the i-th construction design scheme, R i The larger it is, the higher the correlation between the construction design scheme and the optimal construction design scheme, that is, the better the construction design scheme is; Step 5: Determine the comprehensive evaluation coefficient R based on the above calculation results i The largest construction design plan is then optimized and adjusted to obtain a better construction design plan.

2. The optimization method for low-carbon foundation treatment scheme according to claim 1, characterized in that: When performing step 1, The total cost indicator is the total cost of the construction design solution; The construction period indicator is the total construction period of the construction design plan; the carbon emissions are calculated in accordance with the "Building Carbon Emission Calculation Standard" GB / T 51366-2019; The technical feasibility index is a low, medium or high evaluation made by experts based on the actual situation of the construction design plan, with low being 0 points, medium being 0.5 points and high being 1 point; The evaluation criteria for the construction difficulty index are divided into five levels: extremely easy (1 point), easy (2 points), medium (3 points), difficult (4 points), and difficult (5 points); the evaluation contents of the construction difficulty index include five aspects: technical difficulty, organizational difficulty, management difficulty, safety difficulty, and environmental difficulty; The treatment efficacy index is evaluated by experts based on the overall treatment efficacy of various construction design solutions and is given a score of 0-9, with the larger the score, the better the treatment efficacy.

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