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Combined Approach for Government E-Tendering Using GA and TOPSIS with Intuitionistic Fuzzy Information.

Wang Y, Xi C, Zhang S, Zhang W, Yu D - PLoS ONE (2015)

Bottom Line: As E-government continues to develop with ever-increasing speed, the requirement to enhance traditional government systems and affairs with electronic methods that are more effective and efficient is becoming critical.TOPSIS is employed to search for the optimal tenderer.A prototype system is built and validated with an illustrative example from GeT to verify the feasibility and availability of the proposed approach.

View Article: PubMed Central - PubMed

Affiliation: School of Information, Zhejiang University of Finance and Economics, Hangzhou, China.

ABSTRACT
As E-government continues to develop with ever-increasing speed, the requirement to enhance traditional government systems and affairs with electronic methods that are more effective and efficient is becoming critical. As a new product of information technology, E-tendering is becoming an inevitable reality owing to its efficiency, fairness, transparency, and accountability. Thus, developing and promoting government E-tendering (GeT) is imperative. This paper presents a hybrid approach combining genetic algorithm (GA) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to enable GeT to search for the optimal tenderer efficiently and fairly under circumstances where the attributes of the tenderers are expressed as fuzzy number intuitionistic fuzzy sets (FNIFSs). GA is applied to obtain the optimal weights of evaluation criteria of tenderers automatically. TOPSIS is employed to search for the optimal tenderer. A prototype system is built and validated with an illustrative example from GeT to verify the feasibility and availability of the proposed approach.

No MeSH data available.


Related in: MedlinePlus

Graphical interface for optimizing weights.
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pone.0130767.g009: Graphical interface for optimizing weights.

Mentions: After inputting all the information, by clicking the “Optimize weights” button in the top right corner of the window displayed in Fig 9, one can obtain the optimal weights of the five evaluation criteria. Because of the nature of GA, the weight value of each criterion is not invariable, i.e., each calculation makes the weight value of each criterion get tiny change. However, these changes are reasonable and acceptable. In this example, the optimal weight values are shown in Fig 9, indicated as “function 0.256”, “artistry 0.080”, “safety 0.276”, “feasibility 0.244”, and “price 0.144”. We can observe that compared with “artistry”, the remaining four criteria are more critical to the government in selecting a suitable decoration firm. This is realistic.


Combined Approach for Government E-Tendering Using GA and TOPSIS with Intuitionistic Fuzzy Information.

Wang Y, Xi C, Zhang S, Zhang W, Yu D - PLoS ONE (2015)

Graphical interface for optimizing weights.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4493125&req=5

pone.0130767.g009: Graphical interface for optimizing weights.
Mentions: After inputting all the information, by clicking the “Optimize weights” button in the top right corner of the window displayed in Fig 9, one can obtain the optimal weights of the five evaluation criteria. Because of the nature of GA, the weight value of each criterion is not invariable, i.e., each calculation makes the weight value of each criterion get tiny change. However, these changes are reasonable and acceptable. In this example, the optimal weight values are shown in Fig 9, indicated as “function 0.256”, “artistry 0.080”, “safety 0.276”, “feasibility 0.244”, and “price 0.144”. We can observe that compared with “artistry”, the remaining four criteria are more critical to the government in selecting a suitable decoration firm. This is realistic.

Bottom Line: As E-government continues to develop with ever-increasing speed, the requirement to enhance traditional government systems and affairs with electronic methods that are more effective and efficient is becoming critical.TOPSIS is employed to search for the optimal tenderer.A prototype system is built and validated with an illustrative example from GeT to verify the feasibility and availability of the proposed approach.

View Article: PubMed Central - PubMed

Affiliation: School of Information, Zhejiang University of Finance and Economics, Hangzhou, China.

ABSTRACT
As E-government continues to develop with ever-increasing speed, the requirement to enhance traditional government systems and affairs with electronic methods that are more effective and efficient is becoming critical. As a new product of information technology, E-tendering is becoming an inevitable reality owing to its efficiency, fairness, transparency, and accountability. Thus, developing and promoting government E-tendering (GeT) is imperative. This paper presents a hybrid approach combining genetic algorithm (GA) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to enable GeT to search for the optimal tenderer efficiently and fairly under circumstances where the attributes of the tenderers are expressed as fuzzy number intuitionistic fuzzy sets (FNIFSs). GA is applied to obtain the optimal weights of evaluation criteria of tenderers automatically. TOPSIS is employed to search for the optimal tenderer. A prototype system is built and validated with an illustrative example from GeT to verify the feasibility and availability of the proposed approach.

No MeSH data available.


Related in: MedlinePlus