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The fuzzy reasoning numerical spiking neural P systems (FRNSN P systems) are proposed by introducing the interval-valued triangular fuzzy numbers into the numerical spiking neural P systems (NSN P systems). The NSN P systems were applied to the SAT problem and the FRNSN P systems were applied to induction motor fault diagnosis. The FRNSN P system can easily model fuzzy production rules for motor faults and perform fuzzy reasoning. To perform the inference process, a FRNSN P reasoning algorithm was designed. During inference, the interval-valued triangular fuzzy numbers were used to characterize the incomplete and uncertain motor fault information. The relative preference relationship was used to estimate the severity of various faults, so as to warn and repair the motors in time when minor faults occur. The results of the case studies showed that the FRNSN P reasoning algorithm can successfully diagnose single and multiple induction motor faults and has certain advantages over other existing methods. [ABSTRACT FROM AUTHOR]

The fuzzy reasoning numerical spiking neural P systems (FRNSN P systems) are proposed by introducing the interval-valued triangular fuzzy numbers into the numerical spiking neural P systems (NSN P systems). The NSN P systems were applied to the SAT problem and the FRNSN P systems were applied to induction motor fault diagnosis. The FRNSN P system can easily model fuzzy production rules for motor faults and perform fuzzy reasoning. To perform the inference process, a FRNSN P reasoning algorithm was designed. During inference, the interval-valued triangular fuzzy numbers were used to characterize the incomplete and uncertain motor fault information. The relative preference relationship was used to estimate the severity of various faults, so as to warn and repair the motors in time when minor faults occur. The results of the case studies showed that the FRNSN P reasoning algorithm can successfully diagnose single and multiple induction motor faults and has certain advantages over other existing methods.

Shortest path (SP) optimization problems arise in a wide range of applications such as telecommunications and transportation industries. The main purpose of these problems is to find a path between two predetermined nodes within a network as cheaply or quickly as possible. Conventional SP problems generally assume that the arc weights are defined by crisp variables, though imprecise data have been lately incorporated into the analysis. The present study formulates the SP problem in a directed interval-valued triangular fuzzy network. The resulting interval-valued fuzzy SP (IVFSP) problem is converted into a multi objective linear programming (MOLP) problem. Then, a lexicographic optimization structure is used to obtain the efficient solution of the resulting MOLP problem. The optimization process confirms that the optimum interval-valued fuzzy shortest path weight preserves the form of an interval-valued triangular fuzzy number. The applicability of the proposed approach is illustrated through an example dealing with wireless sensor networks. [ABSTRACT FROM AUTHOR]

Highlights • A comprehensive hybrid fuzzy-based occupational risk assessment model for the construction workers is developed. • All the crucial stages of a complete assessment approach are prudently taken into consideration. • A comprehensive step-by-step risk identification approach is proposed. • The proposed method for analyzing the identified risks is proved to produce very consistent and accurate results. • The adoption of suitable treatments for the pertinent risks is viable. • The robustness of the proposed assessment model is verified through its application to a real-life case study. Abstract Although some studies have focused on assessing the related risks to the workers involved in the construction activities, the developed models hitherto are tangled with some shortfalls, including unstructured ways of risks identification, low consistency and accuracy of the used analysis methods, and paucity of prudent evaluation strategies. These shortcomings lead to taking imprudent and inappropriate mitigative actions. As such, a Comprehensive Hybrid Fuzzy-based Occupational Risk Assessment Model (CHFORAM) is developed in this paper to systematically identify, analyze, and evaluate the risks to which the construction workers are exposed. The application of the developed CHFORAM to a real-life case study was observed to have the following contributions: obtaining a detailed list of critical risks posing danger to the workers in a stepwise manner, obviating the need for having statistical data associated with incompletion and uncertainty, analyzing the identified risks with improved consistency and accuracy, proposing the effective treatment strategies to deal with the risks, and providing future plans for dealing with the risks at post-treatment stage. The application of CHFORAM to any projects can guide the safety inspectors and managers in taking the further jauntier mitigative actions, leading to the improvement in safety and health of the involved workers. [ABSTRACT FROM AUTHOR]

The development of information and communication technologies has revolutionized and changed the way we do business in various areas. The field of education did not remain immune to the mentioned changes; there was a gradual integration of the educational process and the mentioned technologies. As a result, platforms for distance learning, as well as the organization of e-learning courses of various types, have been developed. The rapid development of e-learning courses has led to the problem of e-learning course selection and evaluation. The problem of the e-learning course selection can be successfully solved by using multiple-criteria decision-making (MCDM) methods. Therefore, the aim of the paper is to propose an integrated approach based on the MCDM methods and symmetry principles for e-learning course selection. The pivot pairwise relative criteria importance assessment (PIPRECIA) method is used for determining the weights of criteria, and the interval-valued triangular fuzzy additive ratio assessment (ARAS) method is used for the ranking of alternatives i.e., e-learning courses. The suitability of the proposed integrated model is demonstrated through a numerical case study.

This study aims at developing an inexact interval-valued triangular fuzzy based multi-attribute preference model (IVTF-MAPM) method for supporting the selection of remediation strategies of groundwater remediation. The introduction of interval-valued triangular fuzzy parameters into the attributes makes it possible for dealing with multiple uncertainties existing in many real-world cases, considering more possible values and expressing the decision making information more precisely. A attribute system which consists of fifteen remediation alternatives with respect to ten attributes in each period were taken into consideration assessment of the technologies for groundwater remediation. The pairwise comparisons between the alternatives were expressed by the valued preference model and the weights of the attributes were scored by interval Analytic Hierarchy Process. After the modeling formulation, a chlorhydrocarbons-contaminated groundwater management system was provided to demonstrate the applicability of the developed method. Final results showed that A14, A3, A9 and A1 were placed at the top ranking levels for 5-, 10-, 15- and 20-years of remediation, respectively. Compared to the results conducted form FMAPM and MAPM, it is indicated that the significant impact of multiple uncertainties existing in the system is specified. [ABSTRACT FROM AUTHOR]

Firms act to reduce environmental impact and contribute to improving the quality of the environment. However, corporate sustainability is lacking with regard to development in practice, and the decision-making process is absent from a hierarchical structure that has complicated interdependent relationships among the attributes. However, the elimination of less important criteria from various measures and the criteria that are encountered remain with respect to both qualitative and quantitative measures. Thus, this study proposes to develop a corporate sustainability model for a focal firm in supply chain networks using the fuzzy Delphi method, interval-valued triangular fuzzy numbers and analytical network process method. The findings are as follows: the firm focused on the environmental operation design aspect, and it ranked five criteria, which included (1) decreasing the generation of toxic and hazardous matter; (2) environmental certificates; (3) service cycle processing time; (4) reducing the service costs, i.e., the service costs as a percentage of the revenue; and (5) the service output per hour/facility utilization. Sensitivity analysis is performed on the coordination of green design in operations and products, which indicated the corporate sustainable development criteria for the next frontier. The implications and conclusions are discussed. [ABSTRACT FROM AUTHOR]

Earned value is a renowned project management technique that integrates the information on cost and schedule of projects to evaluate their current status. Despite the ability of earned value management (EVM) to measure and control the current status, it is not able to estimate the projects' future performances because EVM does not consider the changes in environmental circumstances or other elements that could influence on the future performance of the project. In the contrary with EVM, the risk analysis technique regards risky conditions for the future performance of the project by recognizing and analyzing the opportunities and threats. In this paper, a new evaluation model of the EVM blended with the risk analysis is presented to improve the project future performance forecasting. In addition, these indices and evaluations are defined under real-life uncertain conditions using linguistic variables represented by interval-valued triangular fuzzy numbers. Finally, a case study from the recent literature for construction industry is given in this paper to show the effectiveness of the proposed EVM model under uncertain conditions. [ABSTRACT FROM AUTHOR]

Decision-making in fuzzy environment is often a very complex, especially when related to predictions and assessments. The Ratio system approach of the MOORA method and Intervalvalued fuzzy numbers have already proved themselves as the effective tools for solving complex decision-making problems. Therefore, in this paper an extension of the Ratio system approach of the MOORA method, which allows a group decision-making as well as the use of interval-valued triangular fuzzy numbers, is proposed. Interval-fuzzy numbers are rather complex, and therefore, they are not practical for direct assigning performance ratings. For this reason, in this paper it has also been suggested the approach which allows the expression of individual performance ratings using crisp, interval or fuzzy numbers, and their further transformation into the group performance ratings, expressed in the form of interval-valued triangular fuzzy numbers, which provide greater flexibility and reality compared to the use of linguistic variables. Finally, in this paper the weighted averaging operator was proposed for defuzzification of interval-valued triangular fuzzy numbers. First published online: 21 Sep 2015

Purpose – The purpose of this paper is to enhance the understanding of sustainable supply chain management (SSCM) and provide a comprehensive and quantitative method to assess performance. Design/methodology/approach – The study applied interval-valued triangular fuzzy numbers associated with grey relational analysis to improve the insufficient information and overcome the incomplete system under uncertainty. Findings – The findings support the argument that the triple bottom line is insufficient to cover the entire concept of SSCM; in particular, the aspects of operations, stakeholders and resilience have not been addressed in previous studies. Research limitations/implications – The results reveal that the triple bottom line concept is insufficient to illustrate the principles of SSCM and to provide an extensive basis for theory development. The aspects and criteria considered in the study only relate to the studied company and may need to be reviewed when applied to other industries. Practical implications – The methodology and findings of the study demonstrate the core applications of criteria ranking and identify priority areas that utilize less investment but that may maintain the studied company’s current performance. Suggestions for the prioritization of criteria to enhance SSCM performance are provided. Originality/value – The present study provides three valuable contributions. First, it adopts collaboration theory to furnish a theoretical foundation for SSCM. Second, the proposed hybrid method is able to overcome uncertainty and subsequently evaluate SSCM while utilizing incomplete and imprecise information. Third, the evaluation provides significant results for consideration in decision making by the studied company. [ABSTRACT FROM AUTHOR]

Decision-making in fuzzy environment is often a very complex, especially when related to predictions and assessments. The Ratio system approach of the MOORA method and Intervalvalued fuzzy numbers have already proved themselves as the effective tools for solving complex decision-making problems. Therefore, in this paper an extension of the Ratio system approach of the MOORA method, which allows a group decision-making as well as the use of interval-valued triangular fuzzy numbers, is proposed. Interval-fuzzy numbers are rather complex, and therefore, they are not practical for direct assigning performance ratings. For this reason, in this paper it has also been suggested the approach which allows the expression of individual performance ratings using crisp, interval or fuzzy numbers, and their further transformation into the group performance ratings, expressed in the form of interval-valued triangular fuzzy numbers, which provide greater flexibility and reality compared to the use of linguistic variables. Finally, in this paper the weighted averaging operator was proposed for defuzzification of interval-valued triangular fuzzy numbers. [ABSTRACT FROM AUTHOR]

A robust scheme to address emergency pollution accident is becoming more and more important with the rise of the frequency and intensity of the emergency pollution accidents. Therefore, it is crucial to select an appropriate technology in an emergency response to chemical spills. In this study, an evaluation framework based on dynamic fuzzy GRA method has been developed to make forward optimum scheme for the selection of emergency treatment technology. Dynamic analysis and linguistic terms are used to evaluate alternatives to improve efficiency of emergency treatment procedures by addressing the vagueness and ambiguity in decision making. The method was then applied in a case study to evaluate emergency arsenic treatment technology and demonstrate its applicability and feasibility in emergency arsenic pollution under two scenarios associated with different arsenic levels. Therefore, not only the results can be used for selecting emergency treatment technology, but also help decision-makers identify desired decisions for contaminant mitigation with a quick response and cost-effective manner. [ABSTRACT FROM AUTHOR]

In recent years, many firms have come to understand that innovation is an important issue in sustainable business management, as it helps improve firm capabilities and competencies. Because of the fiercely competitive environment in the hotel industry, innovation has become a critical factor in the process of hotel differentiation, leading to sustainable business success. However, the literature has not thoroughly examined the role of innovation or the hierarchical structure of the capabilities and competencies in sustainable business management. This study adopts interval-valued triangular fuzzy numbers and grey relational analysis to provide a competitive priority ranking for the aspects and criteria that assist firms in decision-making. The study results indicate that innovation in technology capabilities and networking and social capabilities--in addition to competencies in systemic thinking--are the most important aspects of sustainable business management. In particular, this study indicates that to succeed in building a sustainable business in the hotel industry, firms should upgrade and integrate their business technologies, collaborate with actors inside and outside the firm, build trust as well as a shared vision that includes common agreement, and develop competencies in inventive thinking to support innovation and foster changes in strategy, structure, administrative procedures, and systems when necessary. [ABSTRACT FROM AUTHOR]

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This paper proposes an extension of the ARAS method which, due to the use of intervalvalued fuzzy numbers, can be more appropriate for solving real-world problems. In order to overcome the complexity of real-world decision-making problems, the proposed extension also includes the use of linguistic variables and a group decision making approach. In order to highlight the proposed methodology an example of a faculty websites evaluation is considered. [ABSTRACT FROM AUTHOR]

The development of information and communication technologies has revolutionized and changed the way we do business in various areas. The field of education did not remain immune to the mentioned changes; there was a gradual integration of the educational process and the mentioned technologies. As a result, platforms for distance learning, as well as the organization of e-learning courses of various types, have been developed. The rapid development of e-learning courses has led to the problem of e-learning course selection and evaluation. The problem of the e-learning course selection can be successfully solved by using multiple-criteria decision-making (MCDM) methods. Therefore, the aim of the paper is to propose an integrated approach based on the MCDM methods and symmetry principles for e-learning course selection. The pivot pairwise relative criteria importance assessment (PIPRECIA) method is used for determining the weights of criteria, and the interval-valued triangular fuzzy additive ratio assessment (ARAS) method is used for the ranking of alternatives i.e., e-learning courses. The suitability of the proposed integrated model is demonstrated through a numerical case study. [ABSTRACT FROM AUTHOR]