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Article
Publication date: 30 April 2021

Zeki Ayağ

In this paper, the four popular multiple-criteria decision-making (MCDM) methods in fuzzy environment are utilized to reflect the vagueness and uncertainty on the…

Abstract

Purpose

In this paper, the four popular multiple-criteria decision-making (MCDM) methods in fuzzy environment are utilized to reflect the vagueness and uncertainty on the judgments of decision-makers (DMs), because the crisp pairwise comparison in these conventional MCDM methods seems to be insufficient and imprecise to capture the right judgments of DMs. Of these methods, as Fuzzy analytic hierarchy process (F-AHP) is used to calculate criteria weights, the other methods; Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS), Fuzzy Grey relational analysis (F-GRA) and Fuzzy Preference Ranking Organization METhod for Enrichment of Evaluations (F- PROMETHEE II) are used to rank alternatives in the three different ways for a comparative study.

Design/methodology/approach

The demand for green products has dramatically increased because the importance and public awareness of the preservation of natural environment was taken into consideration much more in the last two decades. As a result of this, especially manufacturing companies have been forced to design more green products, resulting in a problem of how they incorporate environmental issues into their design and evaluate concept options. The need for the practical decision-making tools to address this problem is rapidly evolving since the problem turns into an MCDM problem in the presence of a set of green concept alternatives and criteria.

Findings

The incorporation of fuzzy set theory into these methods is discussed on a real-life case study, and a comparative analysis is done by using its numerical results in which the three fuzzy-based methods reveal the same outcomes (or rankings), while F-GRA requires less computational steps. Moreover, more detailed analyses on the numerical results of the case study are completed on the normalization methods, distance metrics, aggregation functions, defuzzification methods and other issues.

Research limitations/implications

The designing and manufacturing environmental-friendly products in a product design process has been a vital issue for many companies which take care of reflecting environmental issues into their product design and meeting standards of recent green guidelines. These companies have utilized these guidelines by following special procedures at the design phase. Along the design process consisting of various steps, the environmental issues have been considered an important factor in the end-of-life of products since it can reduce the impact on the nature. In the stage of developing a new product with the aim of environmental-friendly design, the green thinking should be incorporated as early as possible in the process.

Practical implications

The case study was inspired from the previous work of the author, which was realized in a hot runner systems manufacturer, used in injection molding systems in a Canada. In a new product development process, the back- and front-ends of development efforts mainly determine the following criteria: cost, risk, quality and green used in this paper. The case study showed that the three fuzzy MCDM methods come to the same ranking outcomes. F-GRA has a better time complexity compared to the other two methods and uses a smaller number of computational steps. Moreover, a comparative analysis of the three F-MCDM methods; F-PROMETHEE II, F-TOPSIS and F-GRA used in ranking for green concept alternatives using the numerical results of the case study. For the case study; as seen in table 20, the three F-MCDM methods produced the numerical results on the rankings of the green concept alternatives as follows; {Concept A-Concept C–Concept B–Concept D}.

Social implications

Inclusion of environmental-related criteria into concept selection problem has been gaining increasing importance in the last decade. Therefore, to facilitate necessary calculations in applying each method especially with its fuzzy extension, it can be developed a knowledge-based (KB) or an expert system (ES) to help the DMs make the required calculations of each method, and interpret its results with detailed analysis.

Originality/value

The objective of the research was to propose a F-AHP based F-MCDM approach to green concept selection problem through F-PROMETHEE II, F-TOPSIS and F-GRA methods. As the F-AHP is used to weight evaluation criteria, the other methods are respectively used for ranking the concept alternatives and determine the best concept alternative.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 14 no. 3
Type: Research Article
ISSN: 1756-378X

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Article
Publication date: 14 February 2020

Priyabrata Chowdhury and Sanjoy Kumar Paul

Corporate sustainability (CS) is becoming a popular research topic. In recent years, researchers have conducted a significant number of studies in this area. Although a…

Abstract

Purpose

Corporate sustainability (CS) is becoming a popular research topic. In recent years, researchers have conducted a significant number of studies in this area. Although a number of those studies have used a variety of multicriteria decision-making (MCDM) methods, to date there is no systematic literature review of this area of research. This paper fulfills this research gap.

Design/methodology/approach

The authors use a systematic literature review and bibliometric analysis approach to analyze the applications of MCDM methods in research on CS.

Findings

The authors have observed that both single and integrated MCDM methods have been used in this domain; however, single MCDM methods are dominant. Further, this review shows that most of the integrated methods use only two MCDM methods and that there has been no comparison of results obtained from different MCDM methods. After reviewing these developments and summarizing the findings, the authors propose directions for future research, including investigating and formulating strategies for specific CS initiatives, integrating three or more MCDM methods, integrating MCDM methods with optimization techniques, analyzing results from a small and medium-sized enterprise (SME) perspective, reconsidering the tenets of existing theories via MCDM methods, and comparing the results of studies of CS in different kinds of economies, as well as the results of using different MCDM methods.

Originality/value

To the best of the authors' knowledge, this is the first study that has conducted a systematic literature review to analyze applications of MCDM methods to different aspects of corporate sustainability, including enablers of and barriers to CS, the evaluation and design of CS initiatives, system or strategy formulation, and performance evaluation, among others.

Details

Management of Environmental Quality: An International Journal, vol. 31 no. 2
Type: Research Article
ISSN: 1477-7835

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Article
Publication date: 22 August 2019

Jeremy Yee Li Yap, Chiung Chiung Ho and Choo-Yee Ting

The purpose of this paper is to perform a systematic review on the application of different multi-criteria decision-making (MCDM) methods in solving the site selection…

Abstract

Purpose

The purpose of this paper is to perform a systematic review on the application of different multi-criteria decision-making (MCDM) methods in solving the site selection problem across multiple problem domains. The domains are energy generation, logistics, public services and retail facilities. This study aims to answer the following research questions: Which evaluating criteria were used for each site selection problem domain? Which MCDM methods were frequently applied in a particular site selection problem domain?

Design/methodology/approach

The goals of the systematic review were to identify the evaluating criteria as well as the MCDM method used for each problem domain. A total of 81 recent papers (2014–2018) including 32 papers published in conference proceedings and 49 journal articles from various databases including IEEE Xplore, PubMed, Springer, Taylor and Francis as well as ScienceDirect were evaluated.

Findings

This study has shown that site selection for energy generation facilities is the most active site selection problem domain, and that the analytic hierarchy process (AHP) method is the most commonly used MCDM method for site selection. For energy generation, the criteria which were most used were geographical elements, land use, cost and environmental impact. For logistics, frequently used criteria were geographical elements and distance, while for public services population density, supply and demand, geographical layout and cost were the criteria most used. Criteria useful for retail facilities were the size (space) of the store, demographics of the site, the site characteristics and rental of the site (cost).

Research limitations/implications

This study is limited to reviewing papers which were published in the years 2014–2018 only, and only covers the domains of energy generation, logistics, public services and retail facilities.

Practical implications

MCDM is a viable tool to be used for solving the site selection problem across the domains of energy generation, logistics, public services and retail facilities. The usage of MCDM continues to be relevant as a complement to machine learning, even as data originating from embedded IoT devices in built environments becomes increasingly Big Data like.

Originality/value

Previous systematic review studies for MDCM and built environments have either focused on studying the MCDM techniques itself, or have focused on the application of MCDM for site selection in a single problem domain. In this study, a critical review of MCDM techniques used for site selection as well as the critical criteria used during the MCDM process of site selection was performed on four different built environment domains.

Details

Built Environment Project and Asset Management, vol. 9 no. 4
Type: Research Article
ISSN: 2044-124X

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Book part
Publication date: 5 October 2018

Long Chen and Wei Pan

With numerous and ambiguous sets of information and often conflicting requirements, construction management is a complex process involving much uncertainty. Decision…

Abstract

With numerous and ambiguous sets of information and often conflicting requirements, construction management is a complex process involving much uncertainty. Decision makers may be challenged with satisfying multiple criteria using vague information. Fuzzy multi-criteria decision-making (FMCDM) provides an innovative approach for addressing complex problems featuring diverse decision makers’ interests, conflicting objectives and numerous but uncertain bits of information. FMCDM has therefore been widely applied in construction management. With the increase in information complexity, extensions of fuzzy set (FS) theory have been generated and adopted to improve its capacity to address this complexity. Examples include hesitant FSs (HFSs), intuitionistic FSs (IFSs) and type-2 FSs (T2FSs). This chapter introduces commonly used FMCDM methods, examines their applications in construction management and discusses trends in future research and application. The chapter first introduces the MCDM process as well as FS theory and its three main extensions, namely, HFSs, IFSs and T2FSs. The chapter then explores the linkage between FS theory and its extensions and MCDM approaches. In total, 17 FMCDM methods are reviewed and two FMCDM methods (i.e. T2FS-TOPSIS and T2FS-PROMETHEE) are further improved based on the literature. These 19 FMCDM methods with their corresponding applications in construction management are discussed in a systematic manner. This review and development of FS theory and its extensions should help both researchers and practitioners better understand and handle information uncertainty in complex decision problems.

Details

Fuzzy Hybrid Computing in Construction Engineering and Management
Type: Book
ISBN: 978-1-78743-868-2

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Article
Publication date: 27 July 2020

Djan Magalhaes Castro and Fernando Silv Parreiras

Governments around the world instituted guidelines for calculating energy efficiency of vehicles not only by models, but by the whole universe of new vehicles registered…

Abstract

Governments around the world instituted guidelines for calculating energy efficiency of vehicles not only by models, but by the whole universe of new vehicles registered. This paper compiles Multi-criteria decision-making (MCDM) studies related to automotive industry. We applied a Systematic Literature Review on MCDM studies published until 2015 to identify patterns on MCDM applications to design vehicles more fuel efficient in order to achieve full compliance with energy efficiency guidelines (e.g., Inovar-Auto). From 339 papers, 45 papers have been identified as describing some MCDM technique and correlation to automotive industry. We classified the most common MCDM technique and application in the automotive industry. Integrated approaches were more usual than individual ones. Application of fuzzy methods to tackle uncertainties in the data was also observed. Despite the maturity in the use of MCDM in several areas of knowledge, and intensive use in the automotive industry, none of them are directly linked to car design for energy efficiency. Analytic Hierarchy Process was identified as the common technique applied in the automotive industry.

Details

Applied Computing and Informatics, vol. 17 no. 1
Type: Research Article
ISSN: 2634-1964

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Article
Publication date: 15 October 2020

Zitong He, Xiaolin Ma, Jie Luo, Anoop Kumar Sahu, Atul kumar Sahu and Nitin Kumar Sahu

Advanced manufacturing machines (AMMs) are searched as a momentous asset across the manufacturing societies for quenching and addressing the production units under…

Abstract

Purpose

Advanced manufacturing machines (AMMs) are searched as a momentous asset across the manufacturing societies for quenching and addressing the production units under economical circumstances, i.e. production of high-quality of goods under feasible cost. AMMs are significant in holding the managers against their rivals and competitors with high profit margins. The authors developed the decision support mechanism/portfolio (DSM-P) consist of knowledge-based cluster approach with a dynamic model. The purpose of research work is to measure overall economic worth of AMMs under objective and grey-imperfect (mixed) data by exploring the proposed DSM-P.

Design/methodology/approach

The authors developed the DSM-P that consist of knowledge-based cluster, three multi-criteria decision-making (MCDM) techniques-1-2-3 with complementary grey relational analysis-4(GRA), approach with a dynamic model (complied by technical plus cost and agility measures of AMMs). The proposed DSM-P enables the manager to map the overall economic worth of candidate AMMs under objective and grey-mixed data.

Findings

The presented DSM-P assist the managers for handling the selection problem of AMMs, i.e. CNCs, robots, automatic-guided vehicle, etc under mixed (objective cum grey) data. To enable the readers for intensely understand the work, the utility of proposed approach is displayed by illustrating a polar robot evaluation and selection problem. It is ascertained that the robot candidate-11 alternative is fulfilling the entire technical cum cost and agility measures.

Originality/value

The DSM-P provides more precise and reliable outcomes due to a usage of the dominance theory. Under the dominance theory, the ranks are obtained by MCDM techniques-1-2-3 are compared with ranks gathered by the GRA-4 under objective cum grey data, formed the novelties in presented research work. From a future perspective, the grey-based models in DSM-P can be built/extended/constructed more extensive and can be simulated by the same approach.

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Article
Publication date: 29 June 2020

Nurcan Deniz

Expert evaluation is the backbone of the multi-criteria decision-making (MCDM) techniques. The experts make pairwise comparisons between criteria or alternatives in this…

Abstract

Purpose

Expert evaluation is the backbone of the multi-criteria decision-making (MCDM) techniques. The experts make pairwise comparisons between criteria or alternatives in this evaluation. The mainstream research focus on the ambiguity in this process and use fuzzy logic. On the other hand, cognitive biases are the other but scarcely studied challenges to make accurate decisions. The purpose of this paper is to propose pilot filters – as a debiasing strategy – embedded in the MCDM techniques to reduce the effects of framing effect, loss aversion and status quo-type cognitive biases. The applicability of the proposed methodology is shown with analytic hierarchy process-based Technique for Order-Preference by Similarity to Ideal Solution method through a sustainable supplier selection problem.

Design/methodology/approach

The first filter's aim is to reduce framing bias with restructuring the questions. To manipulate the weights of criteria according to the degree of expected status quo and loss aversion biases is the second filter's aim. The second filter is implemented to a sustainable supplier selection problem.

Findings

The comparison of the results of biased and debiased ranking indicates that the best and worst suppliers did not change, but the ranking of suppliers changed. As a result, it is shown that, to obtain more accurate results, employing debiasing strategies is beneficial.

Originality/value

To the best of the author's knowledge, this approach is a novel way to cope with the cognitive biases. Applying this methodology easily to other MCDM techniques will help the decision makers to take more accurate decisions.

Details

Journal of Enterprise Information Management, vol. 33 no. 5
Type: Research Article
ISSN: 1741-0398

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Article
Publication date: 13 July 2020

Jolly Puri and Meenu Verma

This paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking…

Abstract

Purpose

This paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking decision-making units (DMUs) based on cross-efficiency technique and subjective preference(s) of the decision maker.

Design/methodology/approach

Self-evaluation in data envelopment analysis (DEA) lacks in discrimination power among DMUs. To fix this, a cross-efficiency technique has been introduced that ranks DMUs based on peer-evaluation. Different cross-efficiency formulations such as aggressive and benevolent and neutral are available in the literature. The existing ranking approaches fail to incorporate subjective preference of “one” or “some” or “all” or “most” of the cross-efficiency evaluation formulations. Therefore, the integrated framework in this paper, based on DEA and multicriteria decision-making (MCDM), aims to present a ranking approach to incorporate different cross-efficiency formulations as well as subjective preference(s) of decision maker.

Findings

The proposed approach has an advantage that each of the aggressive, benevolent and neutral cross-efficiency formulations contribute to select the best alternative among the DMUs in a MCDM problem. Ordered weighted averaging (OWA) aggregation is applied to aggregate final cross-efficiencies and to achieve complete ranking of the DMUs. This new approach is further illustrated and compared with existing MCDM approaches like simple additive weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prove its validity in real situations.

Research limitations/implications

The choice of cross-efficiency formulation(s) as per subjective preference of the decision maker and different orness levels lead to different aggregated scores and thus ranking of the DMUs accordingly. The proposed ranking approach is highly useful in real applications like R and D projects, flexible manufacturing systems, electricity distribution sector, banking industry, labor assignment and the economic environmental performances for ranking and benchmarking.

Practical implications

To prove the practical applicability and robustness of the proposed integrated DEA-MCDM approach, it is applied to top twelve Indian banks in terms of three inputs and two outputs for the period 2018–2019. The findings of the study (1) ensure the impact of non-performing assets (NPAs) on the ranking of the selected banks and (2) are enormously valuable for the bank experts and policy makers to consider the impact of peer-evaluation and subjective preference(s) in formulating appropriate policies to improve performance and ranks of underperformed banks in competitive scenario.

Originality/value

To the best of the authors’ knowledge, this is the first study that has integrated both DEA and MCDM via OWA aggregation to present a ranking approach that can incorporate different cross-efficiency formulations and subjective preference(s) of the decision maker for ranking DMUs.

Details

Data Technologies and Applications, vol. 54 no. 4
Type: Research Article
ISSN: 2514-9288

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Article
Publication date: 12 October 2015

Mahmood Shafiee

Maintenance strategy selection (MSS) is considered as a complex multiple-criteria decision-making (MCDM) problem. The purpose of this paper is to present a comprehensive…

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Abstract

Purpose

Maintenance strategy selection (MSS) is considered as a complex multiple-criteria decision-making (MCDM) problem. The purpose of this paper is to present a comprehensive review on the use and application of MCDM approach and its associated case studies in the field of MSS.

Design/methodology/approach

The paper systematically classifies the published literature of both researchers and practitioners and then analyzes and reviews it methodically.

Findings

This paper outlines the important issues relevant to the subject, including the techniques used for data collection, the quantitative and qualitative criteria taken into account in decision making, the maintenance strategies considered for evaluation, the methods applied to find the solution, and the type of industries being studied. In each category, the gaps are identified along with recommendations for the future research work.

Practical implications

Literature on classification of the MCDM models used to select the most appropriate maintenance strategy is very limited. The proposed classification scheme not only will be useful to researchers, but also assists maintenance professionals to find the models that fit their specific needs.

Originality/value

The paper provides many references in the field, including the articles published in academic journals, conference papers, master and doctoral dissertations, text books, and industrial reports, and suggests a classification scheme according to various attributes.

Details

Journal of Quality in Maintenance Engineering, vol. 21 no. 4
Type: Research Article
ISSN: 1355-2511

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Article
Publication date: 21 August 2007

Wei‐Jaw Deng, Wen Pei and Chih‐Hung Tsai

Decision makers in the service industry must effectively cope with queuing problems, service capacity optimization, service efficiency and service quality problems. This…

Abstract

Decision makers in the service industry must effectively cope with queuing problems, service capacity optimization, service efficiency and service quality problems. This study proposes a computer simulation‐enabled MCDM framework that integrates computer simulation analysis, Taguchi method, expert opinion and multiple criteria decision making (MCDM) to assist decision makers in coping with decision problems. In this framework, Taguchi method is adopted to reduce the time required for the simulation experiment. Computer simulation analysis is adopted to obtain useful information for rapid decision‐making without interrupting actual production. MCDM is used to select the optimal alternative. The illustrative result is extremely promising.

Details

Asian Journal on Quality, vol. 8 no. 2
Type: Research Article
ISSN: 1598-2688

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