CN108876199A - A kind of commercial bid evaluation method based on multidimensional Weighted Fuzzy Study on similar degree method - Google Patents

A kind of commercial bid evaluation method based on multidimensional Weighted Fuzzy Study on similar degree method Download PDF

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CN108876199A
CN108876199A CN201810812918.4A CN201810812918A CN108876199A CN 108876199 A CN108876199 A CN 108876199A CN 201810812918 A CN201810812918 A CN 201810812918A CN 108876199 A CN108876199 A CN 108876199A
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李国良
廖恒枭
庞蓉蓉
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Kunming University of Science and Technology
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Abstract

The invention discloses a kind of commercial bid evaluation methods based on multidimensional Weighted Fuzzy Study on similar degree method,The approach degree of the commercial bid quotation and bid contrul valence of each tenderer is determined by multidimensional fuzzy nearness method,It sorts according to approach degree size,Recommend the candidate that gets the bid out,Analyze and determine the harmony for recommending acceptance of the bid candidate's quotation,Targeted suggestion is provided for the investment control in owner's later period,Bid Evaluation is specifically quantified to each index,The influence of reasonable consideration whole index and each index weights to assessment of bids result,Fining control assessment of bids result,The present invention overcomes the one-sidedness that the interference of subjective factor and the electronics assessment of bids extracting part are itemized,The present invention realizes the automatic assessment of bids of commercial bid by Multiple Attribute Decision Model,The candidate that recommends to get the bid out carries out the final review of technical bid,Change whole submit a tender of evaluation and the bid that the automatic assessment of bids is recommended is evaluated by concentrating manpower,Compared with existing assessment of bids means,Bid Evaluation process can be improved,Improve assessment of bids efficiency.

Description

Business bid evaluation method based on multi-dimensional weighted fuzzy closeness method
Technical Field
The invention relates to a business bid evaluation method based on a multi-dimensional weighted fuzzy closeness method, and belongs to the technical field of business bid evaluation.
Background
In project bidding, the minimum bid price method after evaluation is one of the main bid evaluation methods in China, and the method has strong universality and wide application. However, in the actual bid evaluation process, the phenomena of human factor influence, incomplete bid evaluation reference items and the like exist, the bid evaluation result easily causes the problems of low price bid winning, high price claim and the like, and the engineering quality and the construction period are difficult to ensure. In order to ensure the reasonability and objectivity of the business bid evaluation and improve the efficiency of bid evaluation work, a more scientific and effective bid evaluation method is needed.
Disclosure of Invention
The invention aims to provide a business bid evaluation method based on a multi-dimensional weighted fuzzy closeness method, which overcomes the interference of subjective factors and the one-sidedness that only part of items are extracted for electronic bid evaluation. And (4) specifically quantifying the bid evaluation work to each index, reasonably considering the influence of all indexes and the weight of each index on the bid evaluation result, and finely managing and controlling the bid evaluation result.
The technical scheme of the invention is as follows: a business bid evaluation method based on a multi-dimensional weighted fuzzy closeness method comprises the following steps:
step S01: taking the commercial bid quotation schemes of m bidding units as an alternative scheme set, wherein all list items in the commercial bid quotation scheme of each bidding unit form a characteristic fuzzy vector set for measuring the goodness and the badness of the bidding unit quotation scheme, and the bid control prices of all the list items of the bidding unit form a standard fuzzy vector set for measuring the goodness and the badness of the bidding unit scheme;
step S02: carrying out normalization processing on the feature fuzzy vector set and the standard fuzzy vector set;
step S03: determining the index weight by adopting a combined weighting method;
step S04: carrying out comprehensive evaluation analysis by using a multi-dimensional weighted fuzzy proximity method;
step S05: sequencing the results of the comprehensive evaluation analysis in the step S04 to determine recommended winning bid candidates;
step S06: and analyzing the rationality and the balance of the quoted prices of the candidate who wins the bid, and providing suggestions for the post-management of the owners.
The method comprises the following specific steps:
(1) the business bid quotation schemes of m bidding units are used as alternative scheme setsIs shown to beWhereinRespectively representing the bidding schemes of each bidding unit, and if n list items are arranged in each bidding scheme and constitute a characteristic fuzzy vector set for measuring the quality of the bidding schemes of the unit, the bidding scheme of a certain bidding unitWherein i is 1, 2, m, the bid control price of n list items of the bid unit constitutes a standard fuzzy vector set for measuring the quality of the bid unit scheme, and is recorded asThen
(2) Normalizing the characteristic fuzzy vector set and the standard fuzzy vector set in the step (1), namely respectively normalizing each list item in the characteristic fuzzy vector set and the standard fuzzy vector set by using the following bid offer normalization formula and bid control price normalization formula to obtain normalized offers of each list item in a bidding unit and a bid unit:
the bid offer is normalized by the formula:
the bid control price is normalized by the formula:
in the above formula, j represents the jth list item in the bidding proposal of the bidding unit, and j is 1, 2, n, XijnormNormalized quote, X, representing the jth list item of the ith bid UnitijOriginal quote, X, representing the jth inventory item for the ith bid UnitjminMinimum of the j' th list item quotes, X, representing all of the bidding unitstjRepresenting the original offer, X, for the jth list item of the bidding entitytjnormExpressing the price quoted after the normalization of each list item of the bidding unit;
if all X's obtained by the above formula are presentijnormValue of (A) and XtjnormIf all the values are less than 1, the obtained value is the normalized quoted price, if all the X values are less than 1ijnormValue of (A) and XtjnormIf more than one of the values is greater than 1, all X's are assignedijnormValue of (A) and XtjnormAll multiplied by 0.5, if multiplied by 0.5, all XijnormValue of (A) and XtjnormAll values are less than 1, and the values are normalizedQuotation, if more than one quotation is larger than 1, the quotation after the normalization of the inventory item represented by more than one value larger than 1 is made to be 1, and the rest values smaller than 1 are used as the quotation after the normalization of each inventory item;
(3) comprehensively weighting each bidding unit to determine the index weight: determining the index weight vector of the jth list item according to the weighting method of the 'function drive' principleDetermining the index weight vector of the jth list item according to the weighting method of the 'difference drive' principleAccording toAnddetermining a comprehensive weight vector WjThen, then
Weight W ═ W1,W2,..Wj.,Wn)TWherein
(4) Carrying out comprehensive evaluation analysis by using a multi-dimensional weighted fuzzy proximity method; the feature fuzzy vector set of the bidding unit isStandard fuzzy vector set of bidding unitsThe tender price and tender control price of a certain bidding unit are in the jthThe closeness under the index of the list is as follows:
wherein,and (3) calculating the weighted closeness of each scheme and the bidding control price under the multidimensional index according to the weight W obtained in the step (3), wherein the closeness of the jth list item of the ith bidding unit and the bidding control price is represented as follows:
wherein,
(5) subjecting the product obtained in step (4)Sorting according to the sequence from big to small, and taking the bidding unit with the minimum value as a winning unit;
(6) and (5) comparing the price of the bid-winning unit determined in the step (5) with the bid-bidding control price, judging the proximity of the price and the bid-winning candidate price, and recommending the balance of the price of the bid-winning candidate to provide suggestions for the post-management of the owner.
Determining the index weight vector of the jth attribute vector according to the mean square error method in the weighting method of the 'difference drive' principle
In the step (3), the index weight is determined based on a 'function driving' principle and a 'difference driving' principle.
The weighting method based on the function driving principle determines the weight coefficient according to the relative importance degree of the evaluation index, and generally has two modes of a subjective way and an objective way, the invention obtains the weight of the business mark quotation index, and compares the importance degree of each index through the objective way to obtain the weight coefficient: specifically, the method is determined by calculation according to the proportion of each list item in the whole item quotation;
the weighting method based on the principle of 'difference driving' reflects the difference between the evaluated objects as much as possible on the whole, so that the evaluated objects are ranked as far as possible to facilitate the ranking of the evaluated objects.
The weight vector of the index determined by the weighting method according to the function driving principle isThe weight vector of the index determined by the weighting method of the 'difference drive' principle isDetermining combining weights Wj。
The invention adopts the principle of minimum price bid after evaluation, the bid and quoted prices are all cost-type attributes,the larger the bid price, the closer the bid price of the unit i is to the bid control price, and the lower the bid price, the more desirable the commercial bid is.
And (5) analyzing the rationality and the balance of the quoted prices of the candidate people for winning the bid in the recommendation in the step (6) to provide suggestions for the owner for later investment management and control, specifically comparing the quoted prices of the candidate people for winning the bid in the recommendation determined in the step (5) with the quoted prices of the bid inviting control price, judging the proximity of the quoted prices and the balance of the quoted prices of the candidate people for winning the bid in the recommendation, and suggesting the owner to pay key attention to the projects with over-high floating rate and the projects with over-low floating rate.
Compared with the prior art, the invention has the beneficial effects that:
(1) the invention can be used for evaluating bidding projects such as house construction, municipal administration, highways, water conservancy and hydropower, land arrangement and the like, and has wide application range.
(2) According to the method, the automatic evaluation of the commercial bid is realized by means of the multi-attribute decision model, the bid candidate is recommended to carry out the final evaluation of the technical bid, and all the evaluation bids are changed into the bids recommended by the automatic evaluation of the centralized manpower and material resources (namely, the 'more preferred selection' is changed into 'preferred selection'), so that compared with the existing bid evaluation means, the working flow of bid evaluation can be improved, and the bid evaluation efficiency is improved.
(3) The combined weighting method provided by the invention has the advantages that the combined weighting method determines the index weight, the importance of the list item is considered, the price difference degree of each bidding unit on the item is considered, the influence of subjective factors on bid evaluation results is avoided in commercial bid evaluation by comprehensively evaluating all list items of each bidding unit including branch projects, branch projects and unit projects and the multidimensional weighting fuzzy closeness of bid control prices, and the defect of extracting part items to perform electronic bid evaluation is overcome.
(4) The invention timely finds the items with over-high floating rate and over-low floating rate by analyzing and judging the rationality and the balance of the quoted prices of the candidate who recommends winning a bid, and provides targeted management suggestions for owners.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
Example 1: as shown in fig. 1, in this embodiment, a commercial offer part of a building and decoration project of an overground part of a project of a certain residential building is selected, and 14 units bid and offer the building and decoration project of the overground part of the project of the certain residential building, that is, m is 14, and an evaluation index selects a unit project level of the commercial offer. The 14 bidding units respectively use B1～B14The expression shows that as shown in the table 1, the indexes of the unit project level are respectively 6 items in total of a structure part, a building part, an electric part, a weak current embedded part, a water supply and drainage part and a measure item, and then the scheme setBid and offer scheme for the ith unitThe n inventory items form a feature fuzzy vector set ofIt acts as a point in n-dimensional space that uniquely characterizes scheme Bi(ii) a Using fuzzy vector setsUniquely characterizing the bid control price, expressed as the following formula:
alternative scheme set (Bidding unit)
Characteristic vector set for measuring quality of scheme (list item of bid quotation)
Standard vector set for measuring quality of scheme (inventory item for bidding control price)
TABLE 1
The business bidding price and bidding control price of 14 units in table 1 are normalized and normalized, and the normalization formula is as follows:
the bid offer is normalized by the formula:
the bid control price is normalized by the formula:
in the above formula, j represents the jth list item in the bidding proposal of the bidding unit, and j is 1, 2, n, XijnormNormalized quote, X, representing the jth list item of the ith bid UnitijOriginal quote, X, representing the jth inventory item for the ith bid UnitjminMinimum of the j' th list item quotes, X, representing all of the bidding unitstjRepresenting the original offer, X, for the jth list item of the bidding entitytjnormExpressing the price quoted after the normalization of each list item of the bidding unit;
normalized total XijnormValue of (A) and XtjnormIf a value greater than 1 occurs in the value, let all X' sijnormValue of (A) and XtjnormAll X's are multiplied by 0.5 and 0.5ijnormValue of (A) and XtjnormIf the value is greater than 1, then the normalized quote of the list item represented by the value greater than 1 is 1, and the rest values less than 1 are used asThe normalized quotes for each list item, the normalized results are shown in table 2:
TABLE 2
(3) Determining the index weight W by using a combined weighting method:
applying the empowerment method of 'function driving' principle to the data of table 1 to obtain
W1＝(0.5595，0.2037，0.0458，0.0142，0.0198，0.1570)
Using the mean square error weighting method of the 'difference drive' principle to the data of the table 2 to obtain
W2＝(0.1263，0.1337，0.1666，0.2606，0.1987，0.1140)
By combining the above two weighting methods, the combined weighting is
W＝(0.5392，0.2078，0.0582，0.0282，0.0300，0.1366)
(4) Calculating the multidimensional weighting fuzzy closeness of the business bid quotation and the bid inviting control price of each unit under the multidimensional indexes:
the closeness formula of the tender price and the tender control price of a certain bidding unit under the indexes of the jth list item is as follows:
wherein,represents the ithThe closeness of the jth list item of the bidding unit to the bidding control price is shown in the first 7 columns of the table 3;
calculating the weighted closeness of each scheme and the bid control price under the multidimensional index according to the weight W obtained in the step (3), wherein the specific results are shown in the last column of the table 3 as follows:
wherein,
TABLE 3
(5) Subjecting the product obtained in step (4)Sorting according to the sequence from big to small, and sorting the minimum values
The bidding unit is used as a winning unit;
B10＞B6＞B1＞B4＞B8＞B14＞B13＞B2＞B9＞B7＞B5＞B12＞B11＞B3
the 3 rd unit is a winning unit;
(6) and analyzing the reasonability and the balance of the quoted prices of the candidate who wins the bid, and providing suggestions for the post-management of the owners as shown in the table 4.
TABLE 4
From table 4, it can be seen that the float condition of each list item offer of the recommended winning bid candidate relative to the bid control price: 3 items float up and 3 items float down, wherein 3 items float up to about 21.34 percent; the overall floating rate of the project is 7.02 percent; it can be seen that the bidding units adopt unbalanced quotation means.
If the owner is advised to bid for the candidate who is recommended to bid for winning a bid, the cost and quality problems of the owner in a building part, a weak current embedded part and a water supply and drainage part and the problem of excessive engineering quantity change in the structural part are mainly concerned in the project implementation process.
The comprehensive evaluation and sorting method provided by the invention has the advantages that the comprehensive evaluation and sorting of the closeness of all the list items and the bid inviting control price of the bidding unit are carried out by using the multidimensional weighting fuzzy closeness method, the interference of subjective factors and the one-sidedness that only part of items are extracted by electronic bid evaluation are avoided, and the bid evaluation result is more comprehensive and scientific; and comparing the bid price of the candidate for recommending the winning bid with the bid inviting control price, and analyzing the variation condition of the bid price of the candidate for recommending the winning bid, so as to judge the reasonability and the balance of the evaluation result and provide investment management and control suggestions for owners.
The total price of the 5 th bidding unit is the lowest, namely the total price is the 1 st recommended winning bid party according to the current general evaluation method, but the result of the business bidding evaluation method based on the multidimensional weighting fuzzy closeness method shows that each index of the 3 rd unit is the least close to the bidding control price and is reasonably the lowest, so the last recommended winning unit is the 3 rd unit. This shows that the bid evaluation method is greatly different from the current general bid evaluation method.
While the present invention has been described in detail with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, and various changes and modifications can be made within the knowledge of those skilled in the art without departing from the spirit of the present invention.

Claims (3)

1. A business bid evaluation method based on a multi-dimensional weighted fuzzy closeness method is characterized by comprising the following steps:
step S01: taking the commercial bid quotation schemes of m bidding units as an alternative scheme set, wherein all list items in the commercial bid quotation scheme of each bidding unit form a characteristic fuzzy vector set for measuring the goodness and the badness of the bidding unit quotation scheme, and the bid control prices of all the list items of the bidding unit form a standard fuzzy vector set for measuring the goodness and the badness of the bidding unit scheme;
step S02: carrying out normalization processing on the feature fuzzy vector set and the standard fuzzy vector set;
step S03: determining the index weight by adopting a combined weighting method;
step S04: carrying out comprehensive evaluation analysis by using a multi-dimensional weighted fuzzy proximity method;
step S05: sequencing the results of the comprehensive evaluation analysis in the step S04 to determine recommended winning bid candidates;
step S06: and analyzing the rationality and the balance of the quoted prices of the candidate who wins the bid, and providing suggestions for the post-management of the owners.
2. The business bid evaluation method based on the multidimensional weighting fuzzy closeness method as claimed in claim 1, wherein: the method comprises the following specific steps:
(1) the business bid quotation schemes of m bidding units are used as alternative scheme setsIs shown to beWhereinRespectively representing the bidding schemes of each bidding unit, and if n list items are arranged in each bidding scheme and constitute a characteristic fuzzy vector set for measuring the quality of the bidding schemes of the unit, the bidding scheme of a certain bidding unitWherein i is 1, 2, m, the bid control price of n list items of the bid unit constitutes a standard fuzzy vector set for measuring the quality of the bid unit scheme, and is recorded asThen
(2) Normalizing the characteristic fuzzy vector set and the standard fuzzy vector set in the step (1), namely respectively normalizing each list item in the characteristic fuzzy vector set and the standard fuzzy vector set by using the following bid offer normalization formula and bid control price normalization formula to obtain normalized offers of each list item in a bidding unit and a bid unit:
the bid offer is normalized by the formula:
the bid control price is normalized by the formula:
in the above formula, j represents the jth list item in the bidding proposal of the bidding unit, and j is 1, 2, n, XijnormNormalized quote, X, representing the jth list item of the ith bid UnitijOriginal quote, X, representing the jth inventory item for the ith bid UnitjminMinimum of the j' th list item quotes, X, representing all of the bidding unitstjRepresenting the original offer, X, for the jth list item of the bidding entitytjnormExpressing the price quoted after the normalization of each list item of the bidding unit;
if all X's obtained by the above formula are presentijnormValue of (A) and XtjnormIf all the values are less than 1, the obtained value is the normalized quoted price, if all the X values are less than 1ijnormValue of (A) and XtjnormIf more than one of the values is greater than 1, all X's are assignedijnormValue of (A) and XtjnormAll multiplied by 0.5, if multiplied by 0.5, all XijnormValue of (A) and XtjnormIf more than one value is larger than 1, the normalized quoted price of the list item represented by more than one value larger than 1 is made to be 1, and the rest values smaller than 1 are taken as the quoted price of each list item after normalization;
(3) for each bidding unitAnd performing comprehensive weighting to determine the index weight: determining the index weight vector of the jth list item according to the weighting method of the 'function drive' principleDetermining the index weight vector of the jth list item according to the weighting method of the 'difference drive' principleAccording toAnddetermining a comprehensive weight vector WjThen, then
Weight W ═ W1,W2,..Wj.,Wn)TWherein
(4) Carrying out comprehensive evaluation analysis by using a multi-dimensional weighted fuzzy proximity method; the feature fuzzy vector set of the bidding unit isStandard fuzzy vector set of bidding unitsThe closeness of the tender price and tender control price of a certain bidding unit under the jth list item index is as follows:
wherein,the closeness of the jth list item representing the ith bidding unit to the bidding control price,
calculating the weighted closeness of each scheme and the bid control price under the multidimensional index according to the weight W obtained in the step (3), as shown in the following:
wherein,
(5) subjecting the product obtained in step (4)Sorting according to the sequence from big to small, and taking the bidding unit with the minimum value as a winning unit;
(6) and (5) comparing the price of the bid-winning unit determined in the step (5) with the bid-bidding control price, judging the proximity of the price and the bid-winning candidate price, and recommending the balance of the price of the bid-winning candidate to provide suggestions for the post-management of the owner.
3. The business bid evaluation method based on the multidimensional weighting fuzzy closeness method as claimed in claim 2, wherein: determining the index weight vector of the jth attribute vector according to the mean square error method in the weighting method of the 'difference drive' principle
CN201810812918.4A 2018-07-23 2018-07-23 A kind of commercial bid evaluation method based on multidimensional Weighted Fuzzy Study on similar degree method Pending CN108876199A (en)

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Cited By (3)

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Publication number Priority date Publication date Assignee Title
CN111553779A (en) * 2020-06-04 2020-08-18 南京鑫智链科技信息有限公司 Method and device for sorting bid winning candidates, bid inviting terminal and storage medium
CN112396211A (en) * 2019-08-19 2021-02-23 中移(苏州)软件技术有限公司 Data prediction method, device, equipment and computer storage medium
CN113657655A (en) * 2021-08-06 2021-11-16 中国电子科技集团公司第五十四研究所 Product production method for optimal allocation of service resources

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112396211A (en) * 2019-08-19 2021-02-23 中移(苏州)软件技术有限公司 Data prediction method, device, equipment and computer storage medium
CN112396211B (en) * 2019-08-19 2022-12-13 中移(苏州)软件技术有限公司 Data prediction method, device, equipment and computer storage medium
CN111553779A (en) * 2020-06-04 2020-08-18 南京鑫智链科技信息有限公司 Method and device for sorting bid winning candidates, bid inviting terminal and storage medium
CN113657655A (en) * 2021-08-06 2021-11-16 中国电子科技集团公司第五十四研究所 Product production method for optimal allocation of service resources
CN113657655B (en) * 2021-08-06 2024-06-18 中国电子科技集团公司第五十四研究所 Product production method for optimal allocation of service resources

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