Soft Computing Methods in Human Sciences

Many academic researchers have conducted studies on the selection of design-build (DB) delivery method; however, there are few studies on the selection of DB operational variations, which poses challenges to many clients. The selection of DB operational variation is a multi-criteria decision making process that requires clients to objectively evaluate the performance of each DB operational variation with reference to the selection criteria. This evaluation process is often characterized by subjectivity and uncertainty. In order to resolve this deficiency, the current investigation aimed to establish a fuzzy multicriteria decision-making (FMCDM) model for selecting the most suitable DB operational variation. A three-round Delphi questionnaire survey was conducted to identify the selection criteria and their relative importance. A fuzzy set theory approach, namely the modified horizontal approach with the bisector error method, was applied to establish the fuzzy membership functions, which enables clients to perform quantitative calculations on the performance of each DB operational variation. The FMCDM was developed using the weighted mean method to aggregate the overall performance of DB operational variations with regard to the selection criteria. The proposed FMCDM model enables clients to perform quantitative calculations in a fuzzy decision-making environment and provides a useful tool to cope with different project attributes.

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“…Where, (Cross and Sudkamp, 2002;Niskanen, 2004). The degrees of membership of a single element are expressed by the membership function.…”

Section: Fuzzy Multi-criteria Decision-making (Fmcdm) Modelmentioning

confidence: 99%

Developing a Fuzzy Multicriteria Decision-Making Model for Selecting Design-Build Operational Variations

Xia

Chan

Yeung

2011

J. Constr. Eng. Manage.

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“…In the explorative studies in human sciences [23] we aim at reducing the number of the original variables by grouping first the similar variables and then specifying such new variables that constitute these variable groups. These new variables are often referred to as sum variables because they are usually the (possibly weighted) sums the original variables.…”

Section: Dimensionality Reduction In Statisticsmentioning

confidence: 99%

A Rapid Soft Computing Approach to Dimensionality Reduction in Model Construction

Niskanen

2017

Uncertainty Modeling

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“…A fuzzy set is a set whose elements having varying degrees of membership (Bharathi and Sarma 1985;Civanlar and Trussell 1986;Ng et al 2002;Cross and Sudkamp 2002;Niskanen 2004). A fuzzy membership function enables one to perform quantitative calculations in fuzzy decision making.…”

Section: Establishment Of Fuzzy Membership Functionsmentioning

confidence: 99%

Fuzzy Set Theory Approach for Measuring the Performance of Relationship-Based Construction Projects in Australia

Yeung

Chan

2012

J. Manage. Eng.

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Research into performance measures for relationship-based construction projects becomes crucial because there exhibits an increasing trend of client organizations to adopt relationship-based (or relational contracting) approach to their construction projects worldwide over the last decade. However, few, if any, comprehensive and systematic research studies focus on developing a comprehensive, objective, reliable and practical performance evaluation model for relationship-based construction projects. A Performance Index (PI), which comprises eight weighted Key Performance Indicators (KPIs) and a set of corresponding Quantitative Indicators (QIs) for measuring the performance of relationshipbased construction projects have been developed in Australia. The PI and QIs can assist in developing a benchmark for measuring the performance of relationship-based construction projects. However, the establishment of a set of QIs cannot fully solve the subjectivity of performance evaluation. In order to remedy this deficiency, the aim of this paper is to adopt a Fuzzy Set Theory (FST) approach to establish a well-defined range of Quantitative Requirements (QRs) for each QI within each of the five performance levels. By using the modified horizontal approach, Fuzzy Membership Functions (FMFs) have been constructed through three various methods, namely Constrained Regression Line with the Vertical Error Method (VEM), the Horizontal Error Method (HEM), and the Bisector Error Method (BEM). It was shown that the results derived from the three methods were similar and it seems that the Bisector Error Method is the best technique to construct the FMFs as it considers both the errors created by the residual sum of squares by both vertical and horizontal distances. The newly developed performance evaluation model is not only innovative in nature but it can also improve the objectiveness, reliability and practicality in evaluating the performance of relationship-based construction projects.

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Soft Computing Methods in Human Sciences

Cited by 18 publications

References 0 publications

Developing a Fuzzy Multicriteria Decision-Making Model for Selecting Design-Build Operational Variations

Developing a Fuzzy Multicriteria Decision-Making Model for Selecting Design-Build Operational Variations

A Rapid Soft Computing Approach to Dimensionality Reduction in Model Construction

Fuzzy Set Theory Approach for Measuring the Performance of Relationship-Based Construction Projects in Australia

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