Evaluation and selecting the contractor in bidding with incomplete information using MCGDM method
The main concern of construction projects is to select the right contractor in uncertain environment. According to the complex nature of today’s projects, classical approaches are not successful since they have considered only the proposed price and completion time of the project. The selection of a...
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Veröffentlicht in: | Soft computing (Berlin, Germany) Germany), 2019-10, Vol.23 (20), p.10569-10585 |
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description | The main concern of construction projects is to select the right contractor in uncertain environment. According to the complex nature of today’s projects, classical approaches are not successful since they have considered only the proposed price and completion time of the project. The selection of a successful contractor depends on multi-criteria such as managerial and financial ability, technical capability, and organizational performance criteria in the presence of a decision-making group. Due to the uncertainties, ambiguities, and lack of information in this multi-criteria decision-making problem, this paper proposes an outranking method based on intuitionistic fuzzy theory. This approach involves reciprocal preference relation (RPR) and credibility function. The RPR is used to complete information, and credibility function is employed to select the best contractor. Choosing appropriate contractor to work in power plant projects is essentially owing to the fact that high-sensitive power plant construction projects are handed over to the contractor through tenders. Finally, a case study for selecting contractor in a power plant project is presented to demonstrate the effectiveness of the proposed method. |
doi_str_mv | 10.1007/s00500-019-04050-y |
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According to the complex nature of today’s projects, classical approaches are not successful since they have considered only the proposed price and completion time of the project. The selection of a successful contractor depends on multi-criteria such as managerial and financial ability, technical capability, and organizational performance criteria in the presence of a decision-making group. Due to the uncertainties, ambiguities, and lack of information in this multi-criteria decision-making problem, this paper proposes an outranking method based on intuitionistic fuzzy theory. This approach involves reciprocal preference relation (RPR) and credibility function. The RPR is used to complete information, and credibility function is employed to select the best contractor. Choosing appropriate contractor to work in power plant projects is essentially owing to the fact that high-sensitive power plant construction projects are handed over to the contractor through tenders. 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Akhyani, Fatemeh ; Sheikh, Reza ; Sana, Shib Sankar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-1e847cadedc1989d1e9b11cab217059a8e91688dd3a6b5206067d46a1b5410033</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Artificial Intelligence</topic><topic>Bids</topic><topic>Completion time</topic><topic>Computational Intelligence</topic><topic>Construction industry</topic><topic>Contractors</topic><topic>Control</topic><topic>Critical path</topic><topic>Decision making</topic><topic>Engineering</topic><topic>Fuzzy sets</topic><topic>Linguistics</topic><topic>Mathematical Logic and Foundations</topic><topic>Mechatronics</topic><topic>Methodologies and Application</topic><topic>Multiple criterion</topic><topic>Plant construction</topic><topic>Power plants</topic><topic>Preferences</topic><topic>Project evaluation</topic><topic>Robotics</topic><topic>Set theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Birjandi, Alireza Komeili</creatorcontrib><creatorcontrib>Akhyani, Fatemeh</creatorcontrib><creatorcontrib>Sheikh, Reza</creatorcontrib><creatorcontrib>Sana, Shib Sankar</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Soft computing (Berlin, Germany)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Birjandi, Alireza Komeili</au><au>Akhyani, Fatemeh</au><au>Sheikh, Reza</au><au>Sana, Shib Sankar</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation and selecting the contractor in bidding with incomplete information using MCGDM method</atitle><jtitle>Soft computing (Berlin, Germany)</jtitle><stitle>Soft Comput</stitle><date>2019-10-01</date><risdate>2019</risdate><volume>23</volume><issue>20</issue><spage>10569</spage><epage>10585</epage><pages>10569-10585</pages><issn>1432-7643</issn><eissn>1433-7479</eissn><abstract>The main concern of construction projects is to select the right contractor in uncertain environment. According to the complex nature of today’s projects, classical approaches are not successful since they have considered only the proposed price and completion time of the project. The selection of a successful contractor depends on multi-criteria such as managerial and financial ability, technical capability, and organizational performance criteria in the presence of a decision-making group. Due to the uncertainties, ambiguities, and lack of information in this multi-criteria decision-making problem, this paper proposes an outranking method based on intuitionistic fuzzy theory. This approach involves reciprocal preference relation (RPR) and credibility function. The RPR is used to complete information, and credibility function is employed to select the best contractor. Choosing appropriate contractor to work in power plant projects is essentially owing to the fact that high-sensitive power plant construction projects are handed over to the contractor through tenders. 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subjects | Artificial Intelligence Bids Completion time Computational Intelligence Construction industry Contractors Control Critical path Decision making Engineering Fuzzy sets Linguistics Mathematical Logic and Foundations Mechatronics Methodologies and Application Multiple criterion Plant construction Power plants Preferences Project evaluation Robotics Set theory |
title | Evaluation and selecting the contractor in bidding with incomplete information using MCGDM method |
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