Solving construction project selection problem by a new uncertain weighting and ranking based on compromise solution with linear assignment approach

Selecting a suitable construction project is a significant issue for contractors to decrease their costs. In real cases, the imprecise and uncertain information lead to decisions made based on vagueness.  Fuzzy sets theory could help decision makers (DMs) to address incomplete information. However, this article develops a new integrated multi-criteria group decision-making model based on compromise solution and linear assignment approaches with interval-valued intuitionistic fuzzy sets (IVIFSs). IVIFSs by presenting a membership and non-membership degree for each candidate based on appraisement criteria could decrease the vagueness of selection decisions. The proposed algorithm involves a new decision process under uncertain conditions to determine the importance of criteria and DMs, separately. In this regard, no subjective or additional information is needed for this process; only the input information required is an alternative assessment matric. In this approach, weights of criteria and DMs are specified based on novel indexes to increase the reliability of obtained results. In this respect, the criteria’ weights are computed regarding entropy concepts. The basis for calculating the weight of each DM is the distance between each DM and an average of the DMs’ community. Furthermore, the linear assignment model is extended to rank the candidates. A case study about the construction project selection problem (CPSP) is illustrated to indicate the application of proposed model

A Security-by-Design Decision-Making Model for Risk Management in Autonomous Vehicles

Autonomous/self-driving vehicles have gained significant attention these days, as one of the intelligent transportation systems. However, those vehicles have risks related to their physical implementation and security against cyber threats. Therefore, this study proposes a new security-by-design model for estimating the uncertainty of autonomous vehicles and measuring cyber risks; thus it assists decision-makers in addressing the risks of the physical design and their attack surfaces. The proposed model is developed using neutrosophic sets that efficiently tackle multi-criteria decision-making (MCDM) problems with extensive conflicting criteria and alternatives. The proposed model integrates MCDM, Analytic Hierarchy Process (AHP), Multi-Attributive Border Approximation Area Comparison (MABAC), and Preference Ranking Organization Method for Enrichment Evaluations II (PROMETHEE II), along with single-valued neutrosophic sets (SVNSs). An illustrative case considering ten risks in self-driving vehicles is used to validate the feasibility of the proposed model. Compared to the state-of-the-art methods, the proposed model is considered consistent and reliable to deal with and represent uncertainty and incomplete risk information using neutrosophic sets

Project portfolio selection problems: a review of models, uncertainty approaches, solution techniques, and case studies

Project portfolio selection has been the focus of many scholars in the last two decades. The number of studies on the strategic process has significantly increased over the past decade. Despite this increasing trend, previous studies have not been yet critically evaluated. This paper, therefore, aims to presents a comprehensive review of project portfolio selection and optimization studies focusing on the evaluation criteria, selection approach, solution approach, uncertainty modeling, and applications. This study reviews more than 140 papers on project portfolio selection research topic to identify the gaps and to present future trends. The findings show that not only the financial criteria but also social and environmental aspects of project portfolios have been focused by researchers in project portfolio selection in recent years. In addition, meta-heuristics and heuristics approach to finding the solution of mathematical models have been the critical research by scholars. Expert systems, artificial intelligence, and big data science have not been considered in project portfolio selection in the previous studies. In future, researchers can investigate the role of sustainability, resiliency, foreign investment, and exchange rates in project portfolio selection studies, and they can focus on artificial intelligence environments using big data and fuzzy stochastic optimization techniques

Sustainable infrastructure project selection by a new group decision-making framework introducing MORAS method in an interval type 2 fuzzy environment

Project management is a process that is involved with making important decisions under uncertainty. In project management often the existing data is limited and vague. Sustainable project selection has a multi-criteria evaluation nature which calls for attending to various often conflicting factors under vagueness. To deal with sustainable project selection several important factors should be properly considered. In this paper, in order to provide a new multi-criteria project selection method, a novel last aggregation method is presented. This method has several main novelties. First, to address uncertainty interval type 2 fuzzy sets (IT2FSs) are used. Second, the importance of criteria is investigated by using IT2F entropy. Third, a novel index for decision making is presented that has the merits of ratio system in MOORA and COPRAS, named MORAS. Fourth, the weights of decision makers are computed according to the obtained judgments and the weights are employed to aggregate the results. Fifth, the defuzzification is carried out in the last step of the process by means of a new IT2F ranking method. To present the applicability of the method, it is used in an existing case study in the literature and the outcomes are presented

Supplier evaluation and selection in fuzzy environments: a review of MADM approaches

In past years, the multi-attribute decision-making (MADM) approaches have been extensively applied by researchers to the supplier evaluation and selection problem. Many of these studies were performed in an uncertain environment described by fuzzy sets. This study provides a review of applications of MADM approaches for evaluation and selection of suppliers in a fuzzy environment. To this aim, a total of 339 publications were examined, including papers in peer-reviewed journals and reputable conferences and also some book chapters over the period of 2001 to 2016. These publications were extracted from many online databases and classified in some categories and subcategories according to the MADM approaches, and then they were analysed based on the frequency of approaches, number of citations, year of publication, country of origin and publishing journals. The results of this study show that the AHP and TOPSIS methods are the most popular approaches. Moreover, China and Taiwan are the top countries in terms of number of publications and number of citations, respectively. The top three journals with highest number of publications were: Expert Systems with Applications, International Journal of Production Research and The International Journal of Advanced Manufacturing Technology

A study on decision criteria for assessing construction readiness of highway projects

The impact of highway construction delays is not limited to the construction industry but also affects the nation’s overall economic and social conditions. In addition, delays in highway projects across the country have seriously eroded the confidence of foreign investors and the local business community. One of the factors that cause delay to highway projects is that project teams tend to rush into construction without assessing the readiness of the project. Adequately assessing the readiness of a project may prevent delay. Therefore, this study aims to identify the key decision criteria (KDC) specifically for assessing the construction readiness of highway projects. To achieve that aim, the objectives are to: (1) identify decision criteria specifically for assessing the construction readiness of highway projects; (2) determine the key decision criteria for construction readiness assessment; and (3) evaluate the relationship between the key decision criteria. The scope of this research is the construction industry with the primary focus being the highway construction projects in Malaysia. In phase I of the study, interviews with fifteen industry practitioners working on highway construction projects are being conducted and analysed. Then, in phase II, data from 109 responses are analysed using the mean ranking technique, normalization, Least Significant Difference (LSD) test, and agreement analysis. In phase III, using factor analysis, the relationships between the key decision criteria are examined. A total of eighteen KDCs to assess the readiness of highway projects are identified. The key decision criteria are grouped into four categories reduced uncertainties, availability of resources, approvals and permits, and adequate traffic management plan. In conclusion, construction readiness not only can be assessed during the execution phase, but it can be assessed during the start - up phase. These identified key decision criteria can help industry practitioners to assess their projects before mobilizing their highway construction project. Hence, avoiding impacts from premature starts such as schedule slippage, poor worker productivity, and production delay. In addition, these KDC can help policymakers to take suitable measures to prevent premature starts and mitigate delays, thus avoiding negative impacts to economic and social growth. Also, researchers can use the identified KDCs and their relationship to develop decision support tool for assessing construction readiness in highway construction projects

An integration of QFD and Fuzzy-AHP approach in hospital services, case study: a hospital in Iran

Purpose This paper shows a development of an integrated model to identify the customer needs and select the best solution to optimize the quality of healthcare systems, namely at hospitals. Design/methodology/approach After determining the patient's requirements by data gathering from experts and patients, a questionnaire was prepared to implement the Fuzzy Analytic Hierarchy Process (FAHP) method. Afterward, the requirement's weight has determined by the patients. Finally, the most important technical requirements were achieved applying the 3-phases Quality Function Deployment (QFD) model. Findings The results show that by adapting the FAHP on ideas of the patients and hospital's experts to determine the weights of patients' requirements, led to have more flotation in FAHP questionnaires in the hospital services. In this domain, adopting the decision-making tools help more precise ranking of patients' requirements. Originality/value Since high-quality urgent services are vital to the protection of human life, it is significant to precisely rank the patient’s requirements by novel methodologies. By the implementation of an integrated model using FAHP and QFD, we were able to show the improvement of the quality of an hospital in Iran. After precisely ranking the patient requirements, "increasing human resource" and "establishing requirements and instructions in initial measures and reducing medication errors", are obtained as the most important technical requirements.This work was supported by National Funds through FCT (Portuguese Foundation for Science and Technology), and the first author acknowledges the grant PD/BDE/143092/2018 provided by FCT. Also, this work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/202

Proposição de um modelo de decisão multicritério para seleção de fornecedores no contexto da indústria 4.0

Mestrado APNOR e de dupla diplomação com a UTFPR - Universidade Tecnológica Federal do ParanáA indústria 4.0 compreende a aplicação de diferentes soluções tecnológicas de modo que os processos de negócios em toda a cadeia produtiva sejam integrados. A realização da seleção de fornecedores considerando os requisitos da indústria 4.0 é essencial na promoção de estratégias colaborativas entre fornecedores e fabricantes. Nesse enquadramento, por meio de uma revisão sistemática, foram caracterizados os estudos que propuseram modelos quantitativos para apoiar a seleção de fornecedores no contexto da indústria 4.0. No entanto, não foram encontrados modelos que empreguem critérios de avaliação de fornecedores relacionados a requisitos advindos da indústria 4.0, e que consideram a dificuldade de coletar dados para medir o desempenho dos fornecedores. Assim sendo, a fim de preencher a lacuna de pesquisa identificada, este estudo propõe um modelo de decisão para apoiar a seleção de critérios e fornecedores, com base na combinação de Hesitant Fuzzy Linguistic Term Set (HFLTS) com o método Quality Function Deployment (QFD) considerando um conjunto de critérios definidos a partir de requisitos advindos da indústria 4.0. Para isso, um modelo computacional foi desenvolvido no MS Excel e aplicado em um caso ilustrativo utilizando dados simulados. Por meio dos resultados da aplicação, é possível constatar a capacidade do método em apoiar a tomada de decisão em grupo e considerar pesos diferentes para os julgamentos dos decisores na escolha dos critérios e na avaliação dos fornecedores. A sensibilidade nos parâmetros de saída do modelo às alterações nos parâmetros de entrada sugere efetividade do modelo proposto.Industry 4.0 comprises the application of different technological solutions so that business processes throughout the integrated production chain. Carrying out the selection of suppliers considering the requirements of industry 4.0 is essential in the promotion of collaborative collaborators between suppliers and manufacturers. In this context, through a systematic review, studies were characterized that proposed quantitative models to support the selection of suppliers in the context of industry 4.0. However, no models were found that use supplier evaluation criteria related to requirements arising from industry 4.0, and which consider it a difficulty to collect data to assess supplier performance. Therefore, in order to fill an identified research gap, this study proposes a decision model to support a selection of criteria and suppliers, based on the combination of Hesitant Fuzzy Linguistic Term Set (HFLTS) with the Quality Function Deployment (QFD) method considering a set of criteria defined from the requirements arising from industry 4.0. For this, a computational model was developed in MS Excel and applied in an illustrative case using simulated data. Through the results of the application, it is possible to verify the capacity of the method to support group decision making and consider different weights for the judgments of decision makers in the choice of criteria and in the evaluation of suppliers. The sensitivity of the model's output parameters to changes in the input parameters, the effectiveness of the proposed model

The effectiveness of IF-MADM (intuitionistic-fuzzy multi-attribute decision-making) for group decisions: methods and an empirical assessment for the selection of a senior centre

This study determines the effectiveness of intuitionistic-fuzzy multi-attribute decision-making (IF-MADM) for making group decisions in practice. The effectiveness of the method is measured in terms of four dimensions: applicability, efficacy, efficiency and informativeness. To measure the efficacy, an IF-MADM model that has been recently proposed, AHP and the TOPSIS approach, which are compensatory models for group MADM, are used to model and solve the same collective decision. Using non-parametric statistical tests for data analytics, a ‘similarity confirmation method’ is proposed for a pair-wise test. This is to determine whether the score vectors are similar. Score vectors are used to determine the final ordinal ranks and whose scales differ greatly for different MADM methods. Since the latter two MADM models are both trustworthy with a known range of applications, any similarity in the results verifies the efficacy of IF-MADM. Using this process, the applicability of IF-MADM modelling is demonstrated. The efficiency and informativeness are also benchmarked and justified in terms of the model’s ability to produce a more informed decision. These results are of interest to practitioners for the selection and application of MADM models. Finally, the selection of a senior centre, which is a real group decision problem, is used to illustrate these. This extends the empirical application of IF-MADM, as relatively few studies practically compare issues for IF-MADM with those for other MADM models. The study also supports a rarely studied non-clinical healthcare decision that is relevant because there are many aging societies