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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

Example of uniform crossover.
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pone.0130767.g002: Example of uniform crossover.

Mentions: Although a one-point crossover mechanism is a replication of the biological process, it has drawbacks when addressing real-value-represented chromosomes. Therefore, we adopt a uniform crossover that generates offspring based on a randomly generated crossover mask. The uniform crossover exchanges bits rather than segments and can combine features regardless of their relative locations [14]. This makes uniform crossover a superior operator for real-value-represented chromosomes. The operation is displayed in Fig 2.


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)

Example of uniform crossover.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0130767.g002: Example of uniform crossover.
Mentions: Although a one-point crossover mechanism is a replication of the biological process, it has drawbacks when addressing real-value-represented chromosomes. Therefore, we adopt a uniform crossover that generates offspring based on a randomly generated crossover mask. The uniform crossover exchanges bits rather than segments and can combine features regardless of their relative locations [14]. This makes uniform crossover a superior operator for real-value-represented chromosomes. The operation is displayed in Fig 2.

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