Contractor Selection Model for Highway Projects Using Integrated Simulation and Analytic Network Process

El-Abbasy, Mohammed S.; Zayed, Tarek; Ahmed, Mahrous; Alzraiee, Hani; Abouhamad, Mona

doi:10.1061/(asce)co.1943-7862.0000647

Cited by 62 publications

(31 citation statements)

References 30 publications

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“…In the context of project procurement management in the construction industry especially, contractor selection process is an essential process to be undertaken. Due to the primary responsibility of contractors in handling the main activities, the project success and achievement is heavily dependent on the selection of a capable contractor [12]. Thus, it is important for the project owner or consultant to identify and allocate projects to appropriate contractor.…”

Section: Overview Of Project Managementmentioning

confidence: 99%

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Contractor Selection Criteria: a Study on Malaysian Public Construction Projects

Rashid¹,

Ismail²,

Mohamed³

et al. 2018

IJET

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The complexity of a construction project renders the implementation of a systematic approach in selecting contractors to be of vital importance, especially for the public construction projects. Nevertheless, public construction projects in Malaysia often suffer from delay, over budget and low-quality issues. These are very much affected by the contractors who tend to manipulate the tender price with the sole intention of getting the contract, thus led to many issues throughout the projects delivery. Hence, this paper is aimed to investigate a list of contractor selection criteria for public construction projects in Malaysia. A total of 43 selection criteria have been identified and categorised into seven categories from an initial review via content analysis. These findings were then verified via a questionnaire survey, which was responded by 276 local Malaysian construction industry practitioners. Data collected were analysed using the IBM Statistical Package of Social Sciences (SPSS). The analysis showed that all 43 selection criteria were significant in selecting contractors. It is hoped that the findings of this paper would encourage the governing bodies and authorities to consider the use of multi criteria assessment in selecting contractors for public construction projects, rather than being solely reliant on the tendered price.

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Section: Overview Of Project Managementmentioning

confidence: 99%

“…The classification has been summarised in Table 1. [3], [12], [15]- [17], [19] 7. Others  Time completion  Risk management  Political consideration [3], [12], [16], [19]…”

Section: Contractor Selection Criteriamentioning

confidence: 99%

Contractor Selection Criteria: a Study on Malaysian Public Construction Projects

Rashid¹,

Ismail²,

Mohamed³

et al. 2018

IJET

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“…Random consistency index (Saaty, 2004 decision problems since it was first proposed in 1996. This approach was used in data analysis (e.g., Kuo and Lin, 2012), product planning (e.g., Kahraman et al, 2006), product development (e.g., Ayȃg andÖzdemïr, 2007), performance measurement (e.g., Yurdakul, 2003;Abdi and Labib, 2011;Poveda-Bautista et al, 2012), project selection (e.g., Tavana et al, 2013;El-Abbasy et al, 2013), supplier selection (e.g., Moalagh and Ravasan, 2013), construction management (e.g., Fouladgar et al, 2012aFouladgar et al, , 2012b and other applications. Although the ANP is widely applied in many studies, it is rarely used with a product selection problem focusing on quality and cost, and furthermore the existing studies also ignore the uncertainty of the data.…”

Section: Use Of An Analytic Network Processmentioning

confidence: 99%

Use of an Analytic Network Process and Monte Carlo Analysis in New Product Formula Selection Decisions

Wudhikarn

Chakpitak²,

Neubert³

2015

Asia Pac. J. Oper. Res.

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One crucial matter in routine life is decision-making. Although decision-making in everyday life appears to be easily dealt with by one-on-one comparisons, the same is not true with decision-making in business. In business management decisions, problems are more complicated than those in individual life because most business situations fall into the category of multi-criteria decision-making (MCDM) problems. Therefore, appropriate multi-criteria decision methods should be carefully selected to solve these problems. This study uses the analytic network process (ANP), one of the widely available multi-criteria decision methods. However, this popular method generally ignores the uncertainty inherent in the input data. Therefore, this paper proposes an improved process that considers uncertainty by using Monte Carlo analysis with input values then applied to the ANP procedures. This proposed method is implemented by a real business that produces roof tiles; the primary goal of the study is to select among newly developed roof formulas by considering the uncertainty and interrelation among decision criteria and elements as well as alternatives. The outcomes of study accurately rank the new product formulas. Furthermore, the results of improved method differ the rankings produced by the original ANP. The observed dissimilarities mainly result from uncertainty consideration discussed in this study. be independent from other elements, but, in fact, most real-life problems involve interaction as well as dependency among elements (Saaty, 2001). Thus, an improved method, the analytic network process (ANP), was developed to overcome this problem. The ANP is extended to consider both dependency and feedback. For these reasons, the ANP was later consolidated with several quality methods to produce an improved and more comprehensive decision-making method (Kahraman et al., 2006). However, ANP approximates the prioritization of the competing candidates. Eigenvalues from ANP are calculated from interrelations among input data computations and are normally applied as a basis of prioritization; however, they still lack inclusion of the uncertainty and probability information and lead to inappropriate decision-making (Wey, 2008;Hsu and Pan, 2009).Normally, there is available research that considers the uncertainty in single input data such as the calculation of cost or quality; nevertheless, there has been little attention focused on the uncertainty between cost and quality coordination in MCDM problems. Moreover, most of ANP studies largely ignored the uncertainty (Huang and Tzeng, 2007). Generally, MCDM anticipates the costs, opportunity, benefits, resource consumption, material supplies and other factors, but the exact values of these various attributes are difficult to estimate. Thus, decision-makers may be operating with incomplete knowledge as to the complete data values. Consequently, uncertainty must be included in the data. Some researchers have proposed using the integrated MCDM with an uncertainty module. Lee and Kim (200...

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“…Several computational techniques have been relied on in the development of prequalification and selection models or tools. They include the dimensional weighting model [10]; multi-attribute analysis and utility theory [5]; case-based reasoning system for the capture and reuse experimental knowledge experts in evaluation models [11]; neural networks (NN) for matching contractors' attributes to the clients objectives [12]; Analytical Hierarchy Process (AHP) or its Fuzzy extension [13,14]; ANP and Monte Carlo simulations [15]; and fuzzy set theory [9,16]. These models however predate BIM, thus, do not include criteria related to BIM.…”

Section: Computational Methods For Construction Firms and Supplier Sementioning

confidence: 99%

Supplier BIM competence assessments within the cloud: a proposed Fuzzy-TOPSIS approach

Mahamadu

Mahdjoubi

Booth

2015

WIT Transactions on the Built Environment

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Contractor Selection Model for Highway Projects Using Integrated Simulation and Analytic Network Process

Cited by 62 publications

References 30 publications

Contractor Selection Criteria: a Study on Malaysian Public Construction Projects

Contractor Selection Criteria: a Study on Malaysian Public Construction Projects

Use of an Analytic Network Process and Monte Carlo Analysis in New Product Formula Selection Decisions

Supplier BIM competence assessments within the cloud: a proposed Fuzzy-TOPSIS approach

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