Bid Evaluation for Major Construction Projects Under Large-Scale Group Decision-Making Environment and Characterized Expertise Levels

Authors

Lu Xiao^1, , Zhen-Song Chen^{2, *,} , Xuan Zhang^{2, *,} , Jian-Peng Chang^3, , Witold Pedrycz⁴, Kwai-Sang Chin^5,

¹School of Management, Guangdong University of Technology, Guangzhou 510520, China

²School of Civil Engineering, Wuhan University, Wuhan 430072, China

³School of Business Planning, Chongqing Technology and Business University, Chongqing 400067, China

⁴Department of Electrical and Computer Engineering, University of Alberta, Edmonton AB, T6R 2G7, Canada

⁵Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong, 999077, China

^*Corresponding author. Email: zschen@whu.edu.cn

DOI

10.2991/ijcis.d.200801.002How to use a DOI?

Keywords

Bid evaluation; Expert classification; Consensus reaching processes; ELECTRE III; Multi-attribute group decision-making

Abstract

Rapid growth and development of civil engineering in recent years inspire building enterprises to concentrate on construction contractor selection for achieving more construction quality and lower construction cost. The existing studies generally regard the process of selecting the best contractor as a multi-criteria group decision making problem. Few research studies addressed the contractor selection problem in the context of large-scale group decision making, which is common in practical scenarios in terms of major construction projects as a number of experts with diverse backgrounds are usually involved. On this basis, we establish a contractor selection framework under large-scale group decision making environment, which covers expert classification, consensus reaching process, collective decision matrix generation, and the ranking-oriented decision making method. We cluster expert group with K-means clustering method based on expertise levels, which are depicted by six features generated with an expertise identification approach. The consensus model manages consensus reaching process from both intra- and inter- layers and takes into account the interactions between them. After reaching agreements among experts, this paper utilizes the concept of proportional hesitant fuzzy linguistic term set to assemble intra-subgroup assessments for the reduction of information loss or distortion. Then, an aggregation process carries on as to gather subgroup assessments in which the subgroup weights are derived from their cluster centers and sizes in the use of the TOPSIS method. Finally, the well-established decision making tool integrating qualitative and quantitative criteria, ELECTRE III, is adapted to elicit the ranking of bidders. An illustrative study and a comparative analysis are performed to demonstrate the feasibility and effectiveness of the established multi-criteria group decision making approach.

Copyright

© 2020 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Lu Xiao
AU  - Zhen-Song Chen
AU  - Xuan Zhang
AU  - Jian-Peng Chang
AU  - Witold Pedrycz
AU  - Kwai-Sang Chin
PY  - 2020
DA  - 2020/08/17
TI  - Bid Evaluation for Major Construction Projects Under Large-Scale Group Decision-Making Environment and Characterized Expertise Levels
JO  - International Journal of Computational Intelligence Systems
SP  - 1227
EP  - 1242
VL  - 13
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.200801.002
DO  - 10.2991/ijcis.d.200801.002
ID  - Xiao2020
ER  -