A fuzzy multi-criteria decision-making model for construction contractor prequalification (original) (raw)
Related papers
Fuzzy decision support model for the selection of contractor in construction works
Revista de la construcción, 2018
The major employer in Turkish construction sector is the public and the selection of contractor within the public sector is implemented in accordance with the regulations. Sound utilization of public resources in developing countries with certain development plans is very important; also the establishment of transparency and competition in public procurement increases saving and encourages the correct usage of tax revenues. Within this context, keeping the quality while increasing the level of competition and having successful public investments will be possible by selecting the most ideal contractor. The key for success in public investments on construction projects is to provide the minimum project cost with the ability to reach at the required quality level within the determined period; and therefore some criteria other than the amount of bid should be determined for construction tenders and the evaluation should be one within the scope of such criteria in order to select the contractor. A fuzzy logic methodology is used within the scope of this study, in which the criteria except the price are evaluated with the help of a model and the verbal terms are modeled.
A fuzzy multiple-criteria decision-making model for contractor prequalification
Journal of Decision Systems, 2015
This article presents a new fuzzy multiple criteria decision making model for the evaluation of airline competitiveness over a period. The evaluation problem is formulated as a fuzzy multiple criteria decision making problem and solved by our strength-weakness based approach. For finding out the strength and weakness of an airline over another airline, we present a preference function based on the extended fuzzy preference relation. The strength and weakness matrices are then calculated based on the preference function. We propose a method to aggregate the weights of criteria, strength matrix and weakness matrix into the strength indices and the weakness indices of airlines, by which each airline can identify its own strength and weakness. The strength and weakness indices can be further integrated into an overall performance indices, by which airlines can identify their competitiveness ranking.
Contractor Selection for Construction Project, with the Use of Fuzzy Preference Relation
Procedia Engineering, 2015
During the phase of investment planning, choice of contractor is one of the most important decisions. One of the methods for assessing competences of contractors applying for the contract is their pre-selection. In the article, author describes algorithm for choice (selection) of contractor. The algorithm is based on fuzzy preference relation. In mathematical point of view, it is based on ordering theory and fuzzy sets theory. The article provides an example of the algorithm used for selection of contractor for construction works. The choice was made basing on criteria such as: reputation, technical capabilities, financial situation and organizational skills.
A Fuzzy Logic Approach for Contractor Selection
Contractor selection is the process of selecting the most appropriate contractor to deliver the project with specified quality, time, and cost. Construction clients had realized through the last decades that the lowest price bid is not always the best. Evaluation of contractors based on multi-criteria basis is, therefore, becoming more important to the construction industry. In most countries, contractor selection is done upon regulating laws that take into consideration different circumstances involved in the industry. In Egypt, for example, tender law is evaluating contractors according to both technical and financial basis, but no specific technical criteria were determined in each type of construction industry. This paper presents a fuzzy logic framework to help decision-makers to evaluate the capability of the contractors in residential building projects. An in-depth literature review of the criteria that may affect prequalifying and selecting the appropriate contractor in different countries are presented. Semi-structured interviews were conducted with construction experts to select the appropriate criteria that suit Egyptian industry. An illustrative example is then presented to demonstrate the data requirements and the application of the method in selecting the most appropriate contractor for residential building projects.
A fuzzy sets based contractor prequalification procedure
Automation in Construction, 2012
Contractor prequalification makes it possible to admit for tendering only competent contractors. The paper presents a proposal for contractor prequalification schema involving two stages of prequalification: "on a standing list" and "per project". A model of prequalification employing the theory of fuzzy sets to evaluate the "per project" contractors is precisely described. A simple numerical example illustrates the model operation and a description of a program supporting the prequalification procedure follows.
IJERT-Contractor Selection in Construction Industry using Fuzzy-Logic System
International Journal of Engineering Research and Technology (IJERT), 2014
https://www.ijert.org/contractor-selection-in-construction-industry-using-fuzzy-logic-system https://www.ijert.org/research/contractor-selection-in-construction-industry-using-fuzzy-logic-system-IJERTV3IS111008.pdf Selection of the most appropriate & potential contractor to deliver a project in time is most significant decision making process to ensure the successful completion of construction projects. The construction industry has witnessed the failure of many contractors due to different reasons like labour problems, financial problems, poor performance, social and political problems, lack of safety considerations at worksite etc. All these incidents have led to the impression that the current scenario of awarding the contracts is inefficient in selecting the contractor capable of meeting the demands and challenges of present times and hence needs to be reviewed accordingly. This work presents contractor selection using Analytic Hierarchy Process & Fuzzy Group Decision making Method and results are evaluated by using an actual case study in infrastructure development.
Application of Fuzzy Logic on Selection of Contractors for Construction of High Rise Buildings
IOP Conference Series: Earth and Environmental Science, 2019
Selection process of a construction contractor is highly important and successful implementation of a project and realization of sustainability are largely dependent on it. Computer programs-expert systems-may be used to help the employer or his consultants in the process of best tenderer selection. This paper presents a new expert system based on the implementation of fuzzy logic as an aid in selecting a contractor for construction of high rise buildings.
Scientific African, 2020
Multi-Criteria Decision Making (MCDM) is a discipline aimed at supporting decisionmakers to settle on an ideal choice within the sight of different and clashing criteria. MCDM strategies have developed to oblige different kinds of utilizations. One comprehensively utilized MCDM strategy is the Analytic Hierarchy Process (AHP). AHP, in spite of its simplicity in idea, it can't consider imprecise input. Throughout the years, fuzzy logic has demonstrated its effectiveness as a MCDM technique. It includes a few preferences inside uncertain, imprecise and obscure settings than AHP and other MCDM strategies. Consolidating Fuzzy strategies with AHP is one methodology for taking care of the entangled issues of AHP. The significance of this study is to provide baseline information to the construction clients and consultants on the importance of contractor's prequalification decision criteria to be adopted, which will eventually translate to a better decision making and increase project performance. Taking into account our past research, this paper proposed a Feedback Integrated Fuzzy Analytic Hierarchy Process (FAHP) model for ranking decision criteria for contractual worker determination by combining the selection process and consistency control module. This consistency control module contains a feedback module that generates advice to decision makers so as to check the irregularity in their decisions' during pairwise comparisons. In this paper, the performance investigation of the proposed FAHP model is validated on datasets from three diverse FAHP models. The proposed model accuracy obtained when tested with three distinctive datasets were 98.2%, 99.99%, and 98.24% respectively. The results established the adequacy and uselfulness of the proposed FAHP model in ranking contractor decision criteria. The research additionally guide decision-makers on picking distinctive FAHP algorithms in assessing and ranking decision criteria utilized in contractors selection.
Decision - Making Model by Applying Fuzzy Numbers in Construction Project
Multi-attribute analysis is a useful tool in many economical, managerial, constructional, etc., problems. There is usually some uncertainty involved in all multi-attribute model inputs. The objective of this work is to demonstrate how simulation can be used to reflect fuzzy inputs, which allows more complete interpretation of model results. A case study is used to demonstrate the concept of general contractor choice of on the basis of multiple attributes of efficiency with fuzzy inputs applying COPRAS method. The work has concluded that the COPRAS method is appropriate to use.
A Decision Support Model for Civil Engineering Projects Based on Multi-Criteria and Various Data
JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT
This paper develops a model, introduced in software, namely Multi-Criteria Decision-Making Model (MCDMM). The model helps decision makers selecting the most suitable alternative based on the customer requirements and preferences. Analytic Hierarchy Process (AHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) form a package that covers most available data types in construction projects. In MCDMM, AHP produces criteria relative weights according to their influence on the discussed problem, while Fuzzy TOPSIS is applied to rank the available alternatives. The model consists of two modules, first one uses AHP only to deal with precise, qualitative alongside quantitative data, while the other module combines AHP with Fuzzy TOPSIS due to the importance of linguistic variables to cover undocumented data. MCDMM is verified using two real case studies. The model is applied to a real case project for constructing solar power plants at Saudi Arabia. ...