Search results

The purpose of this paper is to determine the suitability of adopting hybridized multicriteria decision-making models as a decision tool in engineering design. This decision tool will assist design engineers and manufacturers to determine a robust design concept before simulation and manufacturing while all the design features and sub features would have been identified during the decision-making process.

Fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) are hybridized and applied to obtain optimal design of a reconfigurable assembly fixture (RAF) from a set of alternative design concepts. Design features and sub features associated with the RAF are identified and compared using fuzzified pairwise comparison matrices to obtain weights of their relative importance in the optimal design. The FAHP obtained the fuzzy synthetic extent (FSE) values of the design features and sub features. The FSE values are used as weights of the design features and sub features in generating the decision matrix. FTOPSIS and FTOPSIS based on left and right scores were adopted to predict effects of the weights. Results were obtained for normalized and unnormalized weights of the design features and its effects on the relative closeness coefficients of the design alternatives.

The improved performance of the FTOPSIS based on left and right scores is due to the involvement of the left and right scores of weights of the design features in the computation of distances from positive and negative ideal solutions. Embedding the weights of the design features in the normalized decision matrix before estimating the distances of the design concepts from ideal solutions reduces the dependency of the closeness coefficients on the weights of the design features. This also decreases the difference in the final values of the design concepts. In essence, the weights of the design features have an impact in the closeness coefficient. There is reduction in the closeness coefficients of the design concepts due to normalization of the weights of the design features. However, normalizing the weights of the design features did not affect the variations in the final values of the design concept. As the final value of the design concepts can be influenced by the normalized weights of the design features, it can be implied that normalization of weights of the sub features will also affect the decision matrix. The study has been able to proof that hybridizing FAHP and FTOPSIS can produce effective results for decisions on optimal design by the application of FTOPSIS based on left and right scores rather than the general FTOPSIS.

This research develops a hybridized multicriteria decision-making model for decision-making in engineering design. It presents a detailed extension of hybridized FAHP and FTOPSIS based on left and right scores as a useful tool for considering the relative importance of design features and sub features in optimal design selection.

This paper aims to propose a hybrid multiple criteria decision-making (MCDM) technique for performance evaluation of banks in which the banks are assessed and ranked according to the criteria of the balanced scorecard (BSC) methodology and corporate social responsibility (CSR) views.

To clarify the performance of the proposed model, the MCDM technique was implemented in four banks in Iran as a pilot. First, proper criteria for banking industry are identified considering BSC and CSR. Consequently, analytic hierarchy process (AHP) and modified digital logic (MDL) techniques are used to determine the weights of criteria. The banks are ranked by fuzzy TOPSIS (FTOPSIS) and fuzzy VIKOR (FVIKOR). Using a combination of these techniques, four methods, namely, AHP-FTOPSIS, AHP-FVIKOR, MDL-FTOPSIS and MDL-FVIKOR, are obtained, each of which provides a different set of rankings for banks. Eventually, the obtained ranks are integrated using the Copeland method.

The results showed that the return on investment, debt ratio and lower energy consumption criteria are the most important, and enhancement of brand value, increasing customer loyalty and environmental care criteria have the lowest percentage of importance. Also, the final bank ranking is determined by the proposed method.

This paper identifies 6 criteria and 25 sub-criteria for evaluating the banks considering BSC and CSR viewpoints including some new sub-criteria that has not been considered before. Moreover, these hybrid approaches and especially MDL techniques have not been used by previous researchers.

The purpose of this paper is to outline and prioritizes risk sources in medical device development (MDD) process using an integrated “structural equation modeling” (SEM) and fuzzy “technique for order performance by similarity to ideal solution (TOPSIS)” framework.

Risk sources which deter MDD process are explored through literature review. Initial structural model is proposed, factor loadings are determined by exploratory factor analysis and model fit is established by confirmatory factor analysis. Further, the sources are ranked using FTOPSIS, and sensitivity analysis is carried to check robustness of results.

The sources of risks have catastrophic effect on MDD process. The initial SEM model developed based on survey of experts is found reliable and valid which breaks up the risk sources into three categories – internal sources of risks, user-related sources of risks and third-party-related sources of risks. The risk sources are ranked and prioritized based on perspective of experts from the categories using FTOPSIS; unmet user needs/requirements is found as the most important source of risk. Results of sensitivity analysis confirm that the factors are relatively less sensitive to criteria weights confirming reliability of initial solution.

The proposed methodology combines qualitative and quantative approaches, making it little complex and lengthy, but results in dual confirmation.

The outcomes of this research will be of prime use for MDD industries to mitigate risk sources. It will help to increase the success rate of MDD.

Integrated SEM-FTOPSIS provides a unique and effective structural modeling-based decision support tool. The framework can be effectively utilized in other domains, and failure events of medical devices can be potentially controlled by applying risk mitigation measures.

Owing to the importance of the portfolio problem in modern financial investment fields, the aim of this paper is to rank and choose suitable stocks in stock markets under vague environment.

Many new principles and methods have been introduced to help the investor to decide which stocks are worth to be chosen. In real word, people prefer to express their attributes by using linguistic terms, so the used data are often imprecise and vague. In this paper, the second method of constrained fuzzy analysis hierarchy process (CFAHP) is used to evaluate the relative weights of the criteria and rank alternatives by fuzzy technique for order preference by similarity to an ideal solution (FTOPSIS).

In this paper, empirical result shows that the proposed method is capable of helping investor to allocate asset in portfolio problems under vague environment.

The proposed method gives a new mathematical framework for portfolio selection. Investors can decide the asset allocation by using the combination of CFAHP and FTOPSIS.

Besides the benefit of sorting feature, the proposed method can be used to obtain the asset allocation.

The aim of the portfolio selection theory is to rank and decide the asset allocations. But it is still a difficult task in deciding which assets should be selected under uncertain environment. The proposed method in this paper has been proved to be an efficient method to deal with vague information in decision-making programs.

This study analyzes the effectiveness of the combined method of CFAHP and TOPSIS in portfolio problem.

This paper aims to assist managers and food supply chain practitioners in efficiently implementing lean and green (LG) practices for sustainability. Examining barriers to LG practices, as well as prioritizing mitigation strategies in the food supply chain, are all part of this work.

Using a combination of literature review and expert team inputs, this paper investigated the LG barriers and their solutions under PESTEL (Political, Economic, Social, Technological, Environmental and Legal) framework. To prioritize them, this work used the fuzzy best worst method (fuzzy BWM) with the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS).

From the fuzzy BWM, the economic barriers were identified as the most significant. From the FTOPSIS approach, top management expertise and commitment to adopting LG practices were identified as the best solution for overcoming the barriers.

This paper discusses the barriers and solutions for successfully implementing LG techniques from the real-time food supply chain. The practitioners and food chain managers welcomed the methodology for its use in prioritizing the barriers to LG practices. Conclusions drawn from this work were found to be realistic.

The original contribution of this study is to present the model framework for barriers and solutions of LG practices in the dairy supply chain using the hybrid MCDM technique.

Due to the fierce market competition, many organizations seek global suppliers because of lower procurement costs and better product quality. However, selecting suitable global suppliers is one of the complicated decision-making tasks for decision-makers due to the involvement of various qualitative and quantitative factors. The primary purpose of this research is to design an integrated approach for global supplier selection and order allocation in the context of developing an environment-friendly supply chain under data uncertainty.

Initially, the fuzzy analytical hierarchy process (FAHP) is used to calculate the selected criteria weights. After that, the weights obtained from FAHP are inserted into the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) to examine the performance of selected suppliers and determine their final ranks. Finally, the obtained results from FTOPSIS are incorporated into the multi-choice goal programming (MCGP) model, which involves multi-aspiration levels to allocate the optimal order quantity to the selected global suppliers.

A real-time case study of the automotive industry is presented to demonstrate the efficiency and practicality of the suggested approach. The case study and sensitivity analysis results show that the proposed model effectively tackles suppliers' evaluation and order allocation data uncertainty.

Incorporation of risks, environmental management and economic factors during global supplier selection in the automotive sector has not been given much attention in the past literature. So, this research aims to fulfill the gap by developing an integrated approach that can tackle data uncertainty effectively.

This paper aims to select key criteria for sustainable vendor assessment and spare-parts supplies in the Indian petroleum refining sector using stochastic fuzzy technique for order of preference by similarity to ideal solution (SFTOPSIS).

The criteria for sustainable vendor evaluation and selection are identified from the review of the literature and further; it is finalized using the Delphi method. Eight supply chain (SC) experts from the Indian petro refining sector were identified as having more than five years of experience and agreed to participate in this study (known as decision-makers (DM)). Five vendors supplying spare-parts are shortlisted from the market with the discussion and consent of procurement experts from petroleum refineries. Subsequently, criteria and vendors are rated based on relative importance in linguistic terms from the group of eight DMs. As ratings involve uncertainties in the decision-making, the SFTOPSIS method is applied to determine criteria weight and vendor ranking at a distinct significance level (α). The ranking of the vendors is obtained for sustainable supply of spare-parts in the Indian petro refining sector using the SFTOPSIS method.

The ranking of sustainable vendors is obtained through the integrated application of the fuzzy and stochastic approach to capture the uncertainties in the ratings of DMs. The sensitivity analysis is carried out at distinct confidence limits of a normal distribution to obtain a robust ranking of the vendors. In this paper, a case application of SFTOPSIS in the Indian petro refining sector is presented in which key criteria and the vendor ranking are found to be changing with confidence limit for sustainable vendor evaluation.

The fuzziness and randomness in relative ratings collects from a group of DMs are taken in the proposed methodology. The distinct approaches are compared with changing significance-level under stochastic, fuzzy and deterministic TOPSIS to acquire robustness in the ranking. The proposed SFTOPSIS model can be useful to practitioners from the petroleum sector.

The originality of the paper contributes to an application of the SFTOPSIS method that is the extension of FTOPSIS in the petro refining sector of a developing country. The sensitivity analysis with distinct significance-level shows the uncertainties in the collected ratings from the DMs that supports robustness in the ranking. It might be helpful for SC professionals from the petro refining sector, who assess the rank of the vendors at different confidence limits for sustainable supply of spare-parts. Further research in the petroleum industry from emerging economies needs to be undertaken to broaden its scope and applicability.

The purpose of this paper model and prioritizes barriers to product development in medical device manufacturing industries using an integrated “structural equation modelling” (SEM) and “fuzzy technique for order performance by similarity to ideal solution” (FTOPSIS) framework.

Barriers to medical device development (MDD) are adopted from literature. The initial structural model is proposed, exploratory factor analysis and confirmatory factor analysis are used to determine factor loading and model fit, respectively. Further, FTOPSIS is used to rank the barriers and sensitivity analysis is carried to check the robustness of results. The results are discussed in detail and the recommendations to overcome the barriers are presented.

Barriers analysed and prioritized in this research significantly hinder the MDD. The expert survey is used to develop an initial structural equation model of barriers to MDD, find the reliability and validity of the model. Based on the opinion of the experts, the barriers are divided into three categories – internal, policy and induced barriers. FTOPSIS is applied to rank and prioritize the barriers based on views from these three classes of experts. More reliance on imported devices leading to increased imports (B11) and lack of uniform regulatory standards (B6) are found to have the highest rank together, indicating these to be the most important barriers from the perspective considered here. Sensitivity analysis indicates that the factors are less sensitive to the weights of criteria further confirming the reliability of the initial solution.

The prioritization of barriers may vary based upon experts. Policymakers, existing and new device developers need to give utmost importance to these barriers, which will help to accelerate the indigenous development of medical devices to overcome the present dependence on imports.

This paper demonstrates an integrated structural based modelling and prioritization technique for statistical modelling and prioritization of barriers to MDD. The results and recommendations will help policymakers and manufacturers to increase the indigenous share of medical devices. The integrated methodology can be effectively applied where the need for the combined quantitative and qualitative approach is there.

This paper demonstrates an effective structural based modelling and prioritization technique. It can be effectively applied in various fields, it will help policymakers and manufacturers to increase the indigenous share of medical devices.

The purpose of this paper is to identify the radio frequency identification (RFID) strategic value attributes (RFIDSVAs) mechanism selections preferences and also integration of RFID tags with technology coordination tools (IRTWTCTs) alternatives ranking performance decisions in supply chain management (SCM). RFID-enabled techno-economic feasibility decisions are enhancing the SC visibility in apparel supply chains (ASCs). The RFIDSVAs mechanism selections have performed significant agility to strategic competitive advantages, namely, inventory visibility, multi-tags ownership transfer within trusted third party, etc.

Fuzzy analytical hierarchy process (FAHP) and FAHP-fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) approaches have been used to evaluate the quantitative assessment of RFIDSVA mechanisms selection decision based on weight priority orders and IRTWTCTs alternatives selection in ASC networks. The comparison of FAHP and FAHP-FTOPSIS approaches to evaluate the integrated framework develop in RFIDSVAs mechanisms and IRTWTCTs alternatives selection decisions in Indian multi-tier ASC networks.

The result found that the FAHP-FTOPSIS approaches have used to prioritizing the RFIDSVA mechanism selection weights and also identify the IRTWTCTs alternatives ranking preferences order in apparel SCM. The comparison between the FAHP and FAHP-FTOPSIS approach to quantitative assessments from RFIDSVA mechanisms and IRTWTCTs alternatives selection decisions, which enable them SC agility potential across multi-tier visibility in ASC networks. ASC stakeholders can be benefited by techno-economic feasibility decisions, RFID-enabled shop floor activities, multi-tags ownerships transfer in SCs and knowledge-based cryptography tags/items separation in SCs.

The research work has considered only five RFIDSVA mechanisms and also three integration of RFIDTWTCTs alternatives in multi-tier ASC. The strategic competitive advantages are achieved by RFID-enabled break-even tags price decisions and also techno-economic feasibility decision by contractual design multi-tier SC stakeholder’s involvements.

The pilot project study explores that the quantitative assessment decision has based on RFID-enable techno-economic feasibility in ASCs. Stakeholders can be benefited by inventory control of the financial losses, reducing the inventory inaccuracies and multi-tags ownership transfer within trusted third-party traceability in ASC networks.

This study explores the RFID-enabled apparel SC process and activities visibility (natural fibre’s fibre producer, fibre dyeing producer, yarn spinning producer, knitting and finishing producer).

Decision-making problems in emergency plan selection for epidemic prevention and control (EPAC) are generally characterized by risky and uncertainty due to multiple possible emergency states and vagueness of decision information. In the process of emergency plan selection for EPAC, it is necessary to consider several obvious features, i.e. different states of epidemics, dynamic evolvement process of epidemics and decision-makers' (DMs') psychological factors such as risk preference and loss aversion.

In this paper, a novel decision-making method based on cumulative prospect theory (CPT) is proposed to solve emergency plan selection of an epidemic problem, which is generally regarded as hybrid-information multi-attribute decision-making (HI-MADM) problems in major epidemics. Initially, considering the psychological factors of DMs, the expectations of DMs are chosen as reference points to normalize the expectation vectors and decision information with three different formats. Subsequently, the matrix of gains and losses is established according to the reference points. Furthermore, the prospect value of each alternative is obtained and the comprehensive prospect values of alternatives under different states are calculated. Accordingly, the ranking of alternatives can be obtained.

The validity and robustness of the proposed method are demonstrated by a case calculation of emergency plan selection. Meanwhile, sensitivity analysis and comparison analysis with fuzzy similarity to ideal solution (FTOPSIS) method and TODIM (an acronym in Portuguese for interactive and MADM) method illustrate the effectiveness and superiority of the proposed method.

An emergency plan selection method is proposed for EPAC based on CPT, taking into account the psychological factors of DMs.

Highlights

1. This paper proposes a new CPT-based EDM method for EPAC under a major epidemic considering the psychological factorsof DMs, such as risk preference, loss aversion and so on.

2. The authors' work gives approaches of normalization, comparison and distance measurement for dealing with the integration of three hybrid formats of attributes.

3. This article gives some guidance, which contributes to solve the problems of risk-based hybrid multi-attribute EDM.

4. The authors illustrate the advantages of the proposed method by a sensitivity analysis and comparison analysis with existing FTOPSIS method and TODIM method.

This paper proposes a new CPT-based EDM method for EPAC under a major epidemic considering the psychological factorsof DMs, such as risk preference, loss aversion and so on.

The authors' work gives approaches of normalization, comparison and distance measurement for dealing with the integration of three hybrid formats of attributes.

This article gives some guidance, which contributes to solve the problems of risk-based hybrid multi-attribute EDM.

The authors illustrate the advantages of the proposed method by a sensitivity analysis and comparison analysis with existing FTOPSIS method and TODIM method.