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The whole panel industry has been impacted profoundly by global recession from 2007 to 2009, and the TFT–LCD industry is not an exception. Currently, the major TFT–LCD manufacturers cluster in South Korea, Taiwan and Japan, which totally contribute more than 80% sales in global market. All these TFT–LCD manufacturers face the five industry characteristics, including intensive capital, intensive technology, short product life cycle and fast technology advancement, fluctuating prices easily influenced by market demand/supply and business cycle, and international collaboration. In view of rapid growth of global demand, TFT–LCD manufacturers face a tremendous competition environment. Therefore, how to configure the best resource allocation and create more profits tend to be an essential issue for the managers of TFT–LCD industry. This paper employs improved DEA and VIKOR to evaluate the dynamic operation performances for TFT–LCD manufacturers in Taiwan, South Korea and Japan from 2002 to 2009. Research results show that South Korean firms have relatively better stable operation performances, while the performance of the firms in Taiwan and Japan are relatively worse and varied over time. After referring to the disclosure statements and industrial experts' opinions, this paper also portraits the reason of Sony with great performance in 2007 was resulted from the sales boost of high-level touch panels which leads to 50% high gross profit ratio and rapidly increasing pre-tax profit in 2007. As a result, how to develop high-level or multi-function panels might be an essential issue for the TFT–LCD manufacturers in Taiwan.

This paper, proposes the Multi-Criteria Decision Making (MCDM) methodology for selection of a maintenance strategy to assure the consistency and effectiveness of maintenance decisions. The methodology is based on an AHP-enhanced TOPSIS, VIKOR and benefit-cost ratio, in which the importance of the effectiveness appraisal criteria of a maintenance strategy is determined by the use of AHP. Furthermore, in the proposed methodology the different maintenance policies are ranked using the benefit-cost ratio, TOPSIS and VIKOR. The method provides a basis for consideration of different priority factors governing decisions, which may include the rate of return, total profit, or lowest investment. When the preference is the rate of return, the benefit-cost ratio is used, and for the total profit TOPSIS is applied. In cases where the decision maker has specific preferences, such as the lowest investment, VIKOR is adopted. The proposed method has been tested through a case study within the aviation context for an aircraft system. It has been found that using the methodology presented in the paper, the relative advantage and disadvantage of each maintenance strategy can be identified in consideration of different aspects, which contributes to the consistent and rationalized justification of the maintenance task selection. The study shows that application of the combined AHP, TOPSIS, and VIKOR methodologies is an applicable and effective way to implement a rigorous approach for identifying the most effective maintenance alternative.

Excellent qualities including a good balance of strength and toughness, good wear resistance, cost-effectiveness, high machinability, functionality, durability, and reliability make C-45 steel a desirable option for automotive, tool and die-making industries, agricultural, railway, power transmission equipment, etc. When accuracy and precision are crucial, C-45 can be machined using wire electrical discharge machining (WEDM). In this study, input parameters like pulse-on time ($T_{\text{on}}$), pulse-off time ($T_{\text{off}}$), wire feed (WF), and wire tension (WT) were taken to investigate three crucial machining outputs namely average cutting speed (V), kerf width (KW), and material removal rate (MRR), using 0.25 mm brass wire. Taguchi’s ($L$${}_{27}$) orthogonal array has been utilized to perform the trial runs. A hybrid approach combining VIKOR in conjunction with the analytical hierarchy process (AHP) is used to identify optimal WEDM process parameters. Finally, the optimal settings of the input process parameters are $T_{\text{on}}$ = 110 $\mu$s, $T_{\text{off}}$ = 40 $\mu$s, WF = 5 mm/min, and WT = 6 N, respectively. For the desired MRR, KW, and V, the ideal input factors were also achieved using Taguchi’s $S$/$N$ ratio. Additionally, SEM micrographs revealed different effects on the machined surface during machining on optimal parameter settings. This study will help the decision-makers to find the best compromise solution to handle complex decision problems with multiple criteria and prioritize alternatives using a systematic approach which leads to a more effective and rational decision-making process.

Most multicriteria methods focus on ranking and selecting from a set of alternatives. These methods are usually used to compare all alternatives based on the synthesized scorings within a normalized scale with respect to the same criteria in multicriteria problems. However, the decision makers often simultaneously manage one or several alternatives/projects with conflicting and noncommensurable criteria to reduce the gaps to achieve the aspired grade in practice. They then need to rank the gaps that have not been reduced or improved (the unimproved gaps) for the alternatives/projects or aspects of a project to get the most benefit. Because these compared alternatives/projects do not usually have the same criteria/aspects, traditional methods are unsuitable to deal with them. Thus, this research proposes a new VIKOR method to solve this problem; this new method allows the decision maker to understand these gaps of the projects/aspects and rank them to improve these large gaps in control items to achieve the aspired level. Its concept originates in compromise solutions, in particular the VIKOR method. In addition, this research also provides an example of improving information security risk to demonstrate the suitability of this new method. The results show the effectiveness of the new method.

The multiple attribute decision making (MADM) is an important research field in decision science and operations research. Recently, several commonly used methods such as the TOPSIS and the VIKOR were proposed to solve the MADM problems. The TOPSIS and VIKOR are based on aggregating functions representing closeness to the ideal, which originated in the compromise programming method. The aim of this paper is to develop a new methodology called the relative ratio (RR) for the MADM problems. In this RR method, a compromise solution/alternative is determined based on the concept that the chosen alternative should be as close to the ideal solution as possible and as far away from the negative-ideal solution as possible simultaneously. The computation principle and procedure of the RR method are described in detail in this paper. Moreover comparisons of the RR method with the TOPSIS as well as the VIKOR are made theoretically and illustrated with a numerical example.

Classification algorithm selection is an important issue in many disciplines. Since it normally involves more than one criterion, the task of algorithm selection can be modeled as multiple criteria decision making (MCDM) problems. Different MCDM methods evaluate classifiers from different aspects and thus they may produce divergent rankings of classifiers. The goal of this paper is to propose an approach to resolve disagreements among MCDM methods based on Spearman's rank correlation coefficient. Five MCDM methods are examined using 17 classification algorithms and 10 performance criteria over 11 public-domain binary classification datasets in the experimental study. The rankings of classifiers are quite different at first. After applying the proposed approach, the differences among MCDM rankings are largely reduced. The experimental results prove that the proposed approach can resolve conflicting MCDM rankings and reach an agreement among different MCDM methods.

Real estate brokerage services have developed from individual stores into a chain-store system, and the location of those stores plays a key role in their operation. The purpose of this study is to define and quantify the factors that affect the selection of a site for real estate brokerage services. Mutual relationships between the factors and sub-factors for site selection and their relative weights are also discussed to provide a complete set of decision evaluation models, then how to reduce the gaps to achieve the aspiration level. This research uses a new hybrid Multiple Criteria Decision Making (MCDM) model, combining the Decision Making Trial and Evaluation Laboratory (DEMATEL), DEMATEL-based Analytic Network Process (DANP), and VIšekriterijumsko KOmpromisno Rangiranje (VIKOR) methods to solve these problems. The DEMATEL technique is used to build an influential network relations map, and DANP is expected to obtain the influential weights using the basic concept of Analytic Network Process (ANP), to solve the dependence and feedback problems in the real world. Then, the VIKOR method is used to integrate the performance gaps from criteria to dimensions and overall. As the result shows, there is an interactive and auto-feedback relationship among the four dimensions. Among the 11 evaluation criteria, the income and consumption level is the most important consideration for selection of the site. The number and density of population ranks second in this regard. This study uses VIKOR method for selection of the best site, among three potential sites. Site A is closest to the aspiration level. Site A is better in this regard than the other two sites. The study develops and provides a decision-making system for the site selection in the real estate brokerage services.

Corporations would utilize advanced information technologies for generating corporate social responsibility (CSR) reports and communicating with their stakeholders. However, corporations often could not determine whether their CSR websites are capable of effective communication with the stakeholders. The purpose of this study would be to analyze websites of benchmark companies for establishing an evaluation model to be a reference for CSR website design. Information from expert interviews carried out in this study underwent DEMATEL method for analyzing the mutual relationships between the quality criteria and dimensions of CSR websites. DANP was then used to calculate the weight of each criterion. Finally, we would make use VIKOR method to prioritize the performance CSR website satisfaction. The following provides the recommended improvement priorities according to results of the expert interviews: service quality (C) followed by information quality (B) followed by technical quality (A).

This paper presents an integrated model based on a compromised solution method to solve fuzzy belief multi-objective large-scale nonlinear programming (FBMOLSNLP) problem with block angular structure. A new method is proposed to transfer each belief decision-making problem into some fuzzy problems. Furthermore, we propose a new compromise method of decision-making as one of the most efficient methods based on the particular measure of closeness to the ideal solution to aggregate multi-objective decision-making (MODM) problems into a single problem. The decomposition algorithm based on Dantzig–Wolfe is utilized to reduce the large-dimensional objective space into a two-dimensional space. Then, Zimmerman method is applied to transfer each bi-objective to a single-objective. Moreover, TOPSIS and VIKOR are utilized as two independent solution methods to aggregate each multi-objective sub-problem. Finally, a new single-objective nonlinear programming problem is solved to find the final solution. To justify the proposed model, two illustrative examples are provided, and the results of three decision methods are compromised.

A great number of real-world problems can be associated with multi-criteria decision-making. These problems are often characterized by a high degree of uncertainty. Intuitionistic fuzzy sets (IFSs) are a generalized form of an ordinal fuzzy set to deal with this natural uncertainty. In this paper, we propose a hybrid version of the intuitionistic fuzzy ELECTRE based on VIKOR method, which was never considered before. The advantage and strengths of the intuitionistic fuzzy ELECTRE based on VIKOR method as decision aid technique and IFS as an uncertain framework make the proposed method a suitable choice in solving practical problems. Finally, a numerical example for engineering manager choice is given to illustrate the application of proposed method. The paper also gives a special view of point to the research along IFSs: It can be viewed as a kind of factorial scalar theory in factor space, which helps the authors to complete the paper with clear ideas.

There are several factors that need to be considered in fleet management when it is necessary to resolve disturbances which necessitate aircraft re-assignment due to flight cancellations, making this a multiple-criteria decision-making problem. A change in the type of aircraft assigned can lead to additional alterations as well as directly affecting connecting flights and interconnected schedules serving specific flight segments. Decision-making is crucial and involves the consideration of complex cost effects, with possible disruptive actions evaluated according to the priorities of airline management and the available resources. Airline managers require a practical and flexible tool to help them make appropriate decisions in a rapidly changing and highly competitive environment. Differing from prior studies using mathematical programming, we propose a hybrid model based on the decision-making trial and evaluation laboratory method and the concepts of analytic network process (DANP) to aid in the decision-making process. We also recommend using the VIKOR method to select the most appropriate alternatives, with the corresponding weights obtained using the DANP method. The efficiency and effectiveness of the proposed method is demonstrated by testing it on a real-world flight cancellation case and in consultation with experts. The results show that this hybrid model is an effective resource that airline managers can use to address and resolve aircraft re-assignment irregularities.

Hotel competency is inherently intangible and multivariate. It involves a multiple-criteria decision-making problem. Particularly in the currently rapidly shrinking hotel market in Taiwan, what determines domestic chain hotel groups’ (DCHGs’) competence and survival involves more complex and multiple factors. A practical and effective tool is urgently required for making appropriate decisions. This paper thus proposes a combined consistent fuzzy preference relations (CFPR) and the VIKOR model, aiming to prioritize criteria and solution alternatives for hotel managers. In contrast to prior studies that have used mathematical programming, the model here is also tested using real-world hotel management cases and expert consultation. First, based upon the resource-based view, we propose 21 criteria and six dimensions as the determinants of DCHG competencies. Then, VIKOR is applied to produce the most appropriate alternatives with the corresponding weights obtained using the CFPR method. The combined method successfully manages the problems of linguistic ambiguity and consistency, determines the relative weights of the different factors and provides a ranking priority. The result is compared with some similar methods and is shown to be more useful and reliable. Finally, the verified model can be used to produce strategies. A decision-maker can make selection(s) from the solution formula. Our study may thus contribute to the hotel industry with the efficient decision-making tool of resource-based view (RSV) and two-phase methodologies.

The increasing demand for image dehazing-based applications has raised the value of efficient evaluation and benchmarking for image dehazing algorithms. Several perspectives, such as inhomogeneous foggy, homogenous foggy, and dark foggy scenes, have been considered in multi-criteria evaluation. The benchmarking for the selection of the best image dehazing intelligent algorithm based on multi-criteria perspectives is a challenging task owing to (a) multiple evaluation criteria, (b) criteria importance, (c) data variation, (d) criteria conflict, and (e) criteria tradeoff. A generally accepted framework for benchmarking image dehazing performance is unavailable in the existing literature. This study proposes a novel multi-perspective (i.e., an inhomogeneous foggy scene, a homogenous foggy scene, and a dark foggy scene) benchmarking framework for the selection of the best image dehazing intelligent algorithm based on multi-criteria analysis. Experiments were conducted in three stages. First was an evaluation experiment with five algorithms as part of matrix data. Second was a crossover between image dehazing intelligent algorithms and a set of target evaluation criteria to obtain matrix data. Third was the ranking of the image dehazing intelligent algorithms through integrated best–worst and VIseKriterijumska Optimizacija I Kompromisno Resenje methods. Individual and group decision-making contexts were applied to demonstrate the efficiency of the proposed framework. The mean was used to objectively validate the ranks given by group decision-making contexts. Checklist and benchmarking scenarios were provided to compare the proposed framework with an existing benchmark study. The proposed framework achieved a significant result in terms of selecting the best image dehazing algorithm.

Coronavirus disease (COVID-19) pandemic has a tremendous effect on people’s lives worldwide, and the number of infected patients increases daily. The healthcare sector is affected by a large number of patients with COVID-19, and a solution is urgently needed to avert the risk of deteriorating patients in terms of prioritizing patients based on their health conditions. Prioritization of patients with COVID-19 is a complex and multi-criteria decision-analysis (MCDA) problem due to (i) multiple biological laboratory examination criteria, (ii) criteria importance and (iii) trade-off amongst the criteria. This study presents a new multi-biological laboratory examination framework for prioritizing patients with COVID-19 on the basis of integrated MCDA methods. The experiment was conducted on the basis of three phases. In the first phase, patient datasets containing eight biological laboratory examination criteria for six patients with COVID-19 were derived and discussed. The outcome of this phase was used to propose a decision matrix on the basis of the intersection between “biological laboratory examination criteria” and “COVID-19 patients list”. In the second phase, the analytic hierarchy process (AHP) method was utilized to set the subjective weights for the biological laboratory examination criteria by respiratory experts. In the last phase, the VIekriterijumsko KOmpromisno Rangiranje (VIKOR) method was adopted to prioritize patients in the context of individual and group decision making (GDM). Results showed that (1) the integration of AHP–VIKOR method based on individual and GDM contexts was effective for solving prioritization problems for patients with COVID-19, and (2) the prioritization results of patients with COVID-19 showed no variation in the internal and external VIKOR GDM contexts. The proposed multi-biological laboratory examination framework can differentiate between the mild and serious or critical condition of patients with COVID-19 by prioritizing them based on integrated AHP–VIKOR methods. In conclusion, medical sectors can use the proposed framework to differentiate the health conditions of infected patients and to assign appropriate care with prompt and effective treatment.

The positioning of roadside units (RSUs) in a vehicle-to-infrastructure (V2I) communication system may have an impact on network performance. Optimal RSU positioning is required to reduce cost and maintain the quality of service. However, RSU positioning is considered a difficult task because numerous criteria, such as the cost of RSUs, the intersection area and communication strength, affect the positioning process and must be considered. Furthermore, the conflict and trade-off amongst these criteria and the significance of each criterion are reflected on the RSU positioning process. Thus, this work proposes a new RSU positioning framework based on multicriteria decision-making (MCDM) in the context of the V2I communication system. Three stages are completed for this purpose. First, a real-time V2I hardware is developed to collect data. The developed hardware consists of multiple mobile nodes (i.e., cars with sending–receiving hardware devices) and physical RSUs. The RSUs and the devices in the cars are connected via the nRF24L01$+$PA/LNA transceiver module with Arduino Uno. Second, seven testing scenarios are identified toward acquiring the required data upon the connection of the V2I devices. Moreover, three evaluation attributes (i.e., number of packet losses [PKL], cost and ratio of intersection area [RIA]) are used to evaluate each scenario. A decision matrix is constructed on the basis of the crossover between ‘RSU positioning scenarios’ and ‘multi-evaluation attributes (i.e., PKL, cost and RIA)’. Third, the RSU positioning scenarios are ranked using MCDM techniques, such as the integrated analytic hierarchy process (AHP), entropy and group Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Furthermore, the Borda voting approach is used to aggregate multiple individual rankings into a uniform and final rank. Results indicate the following: (1) integrating AHP, entropy and VIKOR is effective for solving RSU positioning problems; (2) the VIKOR ranking results for individuals vary; (3) the rank of scenarios obtained from the group-VIKOR-based Borda voting context shows that the second scenario, which consists of four RSUs distributed along the street with a maximum distance of 200m between them and 2-m high antennas, is the best in terms of optimally placing the RSUs; and (4) significant differences are observed amongst the scores of the groups, indicating that the ranking results are valid.

Increasing demand for open-source software (OSS) has raised the value of efficient selection in terms of quality; usability is an essential quality factor that significantly affects system acceptability and sustainability. Most large and complex software packages partitioned across multiple portals and involve many users — each with their role in the software package; those users have different perspectives on the software package, defined by their knowledge, responsibilities, and commitments. Thus, a multi-perspective approach has been used in usability evaluation to overcome the challenge of inconsistency between users’ perspectives; the inconsistency challenge would lead to an ill-advised decision on the selection of a suitable OSS. This study aimed to assist the public and private organizations in evaluating and selecting the most suitable OSS. The evaluation of the OSS software packages to choose the best one is a challenging task owing to (a) multiple evaluation criteria, (b) criteria importance, and (c) data variation; thus, it is considered a sophisticated multi-criteria decision making (MCDM) problem; moreover, the multi-perspective usability evaluation framework for OSS selection lacks in the current literature. Hence, this study proposes a novel multi-perspective usability evaluation framework for the selection of OSS based on the multi-criteria analysis. Integration of best-worst method (BWM) and VIKOR MCDM techniques has been used for weighting and ranking OSS alternatives. BWM is utilized for weighting of evaluation criteria, whereas VIKOR is applied to rank OSS-LMS alternatives. Individual and group decision-making contexts, and the internal and external groups aggregation were used to demonstrate the efficiency of the proposed framework. A well-organized algorithmic procedure is presented in detail, and a case study was examined to illustrate the validity and feasibility of the proposed framework. The results demonstrated that BWM and VIKOR integration works effectively to solve the OSS software package benchmarking/selection problems. Furthermore, the ranks of OSS software packages obtained from the VIKOR internal and external group decision making were similar; the best OSS-LMS based on the two ways was ‘Moodle’ software package. Among the scores of groups in the objective validation, significant differences were identified; this indicated that the ranking results of internal and external VIKOR group decision making were valid, which pointed to the validation of the framework.

Time, cost, and quality are the three indispensable factors for the realization and success of a project. In this context, we propose a framework composed of a multi-objective approach and multi-criteria decision-making methods (MCDM) to solve time-cost-quality trade-off optimization problems. A multi-objective Simulated Annealing (MOSA) algorithm is used to compute an approximation to the Pareto optimal set. The concept of the exploratory grid is introduced in the MOSA to improve its performance. MCDM are used to assist the decision-making process. The Shannon entropy and AHP methods assign weights to criteria. The first methodology is for the inexperienced decision-makers, and the second concedes a personal and flexible weighting of the criteria weights, based on the project manager’s assessment. The TOPSIS and VIKOR methods are considered to rank the solutions. Although they have the same purpose, the rankings achieved are different. A tool is implemented to solve a time-cost-quality trade-off problem on a project activities network. The computational experiments are analyzed and the results with the exploratory grid in Simulated Annealing (SA) are promising. Despite the framework aims to solve multi-objective trade-off optimization problems, supporting the decisions of the project manager, the methodologies used can also be applied in other areas.

Websites of environmental content constitute an important tool for promoting environmental information, affect environmental attitudes and promote protected areas as touristic destinations. However, these websites have to be evaluated to ensure that they reach their final goal. The use of multi-criteria decision-making (MCDM) models in website evaluation is relatively new and not many models have been tested for this purpose. Comparisons of such models have been implemented in various domains but not for the purposes of environmental website evaluation. The main objective of this paper is on presenting the procedure of comparison of MCDM models spherical by providing in detail the steps that have to be followed. This process was implemented for website evaluation and investigated the comparative performance of the TOPSIS and VIKOR models. This comparison process involves reliability analysis of the questionnaire and the sample of decision makers, pairwise comparisons of the models by calculating the Pearson correlation coefficient and estimation of the Cohen’s Kappa for testing the inter-rater comparability, using the models as raters. Furthermore, a sensitivity and robustness analysis of those models is implemented, which also has not been implemented before in the application of those models in website evaluation. The tests implemented and presented in this paper reveal that the reasonable disagreement that was often observed among the methods did not affect their reliability. As a result, MCDM models proved very effective for evaluating websites of environmental content.

Site selection for a hospital is demanding and challenging work. It’s become more complicated when considering various infectious diseases. Multiple criteria and sub-criteria are considered for selecting the most suitable and efficient hospital location. In this paper, we find the most suitable location for multiple disease-related hospitals using the multi-criteria decision-making (MCDM) methodologies. The proposed study is done by the MCDM techniques, namely spherical Entropy and spherical VIekriterijumsko KOmpromisno Rangiranje (VIKOR) methods. The decision-making for site selection is based on multiple experts’ opinions. Also, we use real data sources in spherical fuzzy numbers (SFN) to capture all its uncertainty. We proposed a new score function and an accuracy function of the SFN to evaluate crisp value from fuzzy numbers. The most prioritized criteria and sub-criteria are determined with their weights. We optimized the proposed site based on demand and criterion weight. Finally, sensitivity analysis and comparative analysis are conducted to check the stability and robustness of the result.

In this paper, women’s empowerment in different states of India is considered. Based on considered data sets, the states of India are ranked with Decision-Making (MCDM) methodology. Here, Generalized Triangular Intuitionistic Fuzzy Numbers (GTIFNs) are considered. Here, GTIFNs are taken to deal with the uncertainty and we introduce a new de-fuzzification method for converting the GTIFNs to corresponding crisp values. Here, we have applied two MCDM techniques namely the Entropy-weighted method and Vlekriterijumsko KOmpromisno Rangiranje (VIKOR) method. The entropy-weighted method is used for evaluating the criteria weights and the VIKOR method is applied to rank the alternatives. Last, to verify the stability and vagueness of the system, we perform sensitivity and comparative analysis.