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Recently, with the development in technology and increase in population, the waste generated becomes an important issue for countries. Some regulations of recently updated through Ministry of Environment and Urbanisation in Turkey; it is essential to use environmentally compatible physical, chemical, or biological technologies to ensure the recovery of municipal waste in accordance with the zero-waste management system. Currently, there is one pre-treatment facility at the Anatolian Side of Istanbul and a pre-treatment facility is needed to use waste recycling facilities more efficiently. In this research, a combined fuzzy multi-criteria decision-making (MCDM) methodology is developed for the mechanical biological treatment (MBT) location selection problem. The proposed method comprises of geographic information system (GIS), fuzzy best worst method (BWM), and hierarchical fuzzy MCDM approach. First, alternatives for the site selection problem were determined using expert opinions and web-based GIS. Second, the criteria determined for the literature and expert opinions were weighted using the fuzzy best worst method. Finally, most suitable alternative was determined using hierarchical fuzzy MCDM approach. This study creates a roadmap for the MBT facility needed in the Anatolian Side of Istanbul, and according to the literature survey, there is no other study conducted on this subject. The proposed method handles vagueness and uncertainty employing fuzzy set theory. Fuzzy BWM, which does not need to conduct pairwise comparison among all criteria, is employed to determine the criteria weights. Web-based GIS that presents spatial data on web environment offers ease of use and provides the opportunity to evaluate over ready data. [ABSTRACT FROM AUTHOR]

Today, transportation systems are seen as a significant component of people's daily routines. It was stated that nearly forty percent of the world's population passes approximately one hour out each day. Sustainable transportation systems aims to contribute economy and diminish environmental affects by ensuring various benefits as effective city management, energy efficiency, road safety and decreased fuel consumption. Also, sustainable transportation has a key status in logistics and supply chain management. It constructs the principals of sustainable supply chain management. Identification of the most appropriate sustainable transportation service provider needs to consider various factors that are yielded in a hierarchical structure. In this paper, best-worst method (BWM) integrated hierarchical distance based intuitionistic decision making approach to valuate transportation service providers regarding the sustainability factors from social, environmental, economic and operational perspectives. The developed framework manages vague and uncertain data and it enables to present hesitation via intuitionistic fuzzy numbers. Intuitionistic BWM, which do not require to make a pairwise comparisons among criteria is utilized to determine the criteria weights. Moreover, the hierarchical representation of the criteria ensures to conduct an effective analysis. [ABSTRACT FROM AUTHOR]

Supply chain agility is an indispensable way for the companies to quickly response to the demands of the customers. For this reason, agility of supply chain is indispensable in dynamic markets that have high scale of diversity and subjective needs. Supply chain agility needs a systemic procedure that gives priority to feedbacks of customers and follows the changes of competitors in the sector. An efficient supplier evaluation procedure is indispensable for reaching supply chain agility. Agile supplier selection needs to take into account various criteria that incorporate vagueness and uncertainty, obtaining general a multiple level hierarchical system that allows conducting a more efficient decision analysis. Thus, in this paper an integrated fuzzy multi-criteria group decision making procedure based on quantifier-guided ordered weighted average (OWA) method and fuzzy integral, which allows incorporating uncertain data expressed as linguistic terms into the analysis, is proposed for identifying the most suitable agile supplier alternative. In group decision making issues, aggregating experts'opinions is vital to achieve more robust results. As quantifier-guided OWA method is appropriate for decision making problems under uncertain environments, it is employed for the aggregation of experts'evaluations. The developed decision procedure is illustrated via a case study performed in a dye producer in Turkish dye sector. [ABSTRACT FROM AUTHOR]

Industrial robots, which enable manufacturing firms to produce high-quality products in a cost-effective manner, are important components of advanced manufacturing technologies. The performance of industrial robots is determined by multiple and conflicting criteria that have to be simultaneously considered in a robust selection study. In this study, a decision model based on fuzzy linear regression is presented for industrial robot selection. Fuzzy linear regression provides an alternative approach to statistical regression for modelling situations where the relationships are vague or the data set cannot satisfy the assumptions of statistical regression. The results obtained by employing fuzzy linear regression are compared with those of earlier studies applying different analytical methods to a previously reported robot selection problem. [ABSTRACT FROM PUBLISHER]

Companies should cope with uncertain and unpredictable changes while improving responsiveness capability to survive in dynamic market conditions. In recent years, agility concept becomes more and more popular to meet these requirements in management as well as manufacturing. From supply chain viewpoint, collaborating with agile suppliers is principal for constructing an agile supply chain, which is flexible, quick, and responsive. This paper aims to identify the most suitable agile supplier alternative by introducing a novel distance based hierarchical intuitionistic decision making procedure. The proposed methodology, which deals with uncertain and vague data, allows to represent hesitation by using intuitionistic fuzzy numbers rather than fuzzy numbers that fail to take into account hesitancy. The causal links among evaluation criteria are expressed with intuitionistic fuzzy cognitive map tool that enables to yield the importance degree of each criterion. Moreover, the hierarchical representation of the decision making problem provides an effective analysis with the presence of numerous criteria that are to be considered. The distance based framework is to minimize the distance to the ideal solution while maximizing the distance from the anti-ideal solution in order to determine the most appropriate agile supplier alternative. The case study is conducted in a dye manufacturer that performs in Turkish dye industry. [ABSTRACT FROM AUTHOR]

Wastewater management is seen as an important environmental problem faced by the developing countries. Untreated wastewater has serious effects on human health and natural environment. For this reason, selection of the appropriate wastewater treatment (WWT) alternative is vital for sustainable development. The aim of this paper is to propose a fuzzy multi-criteria decision making (MCDM) approach based on 2-tuple fuzzy linguistic representation model, decision making trial and evaluation laboratory (DEMATEL) method and fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. The weights of criteria considered for alternative evaluation are calculated by decision making trial and evaluation laboratory (DEMATEL) method, and then fuzzy TOPSIS method is used to rank the alternatives. The proposed framework enables managers to deal with multi-granular information, and thus, allows for the use of different semantic types by decision-makers. The application of the proposed methodology is illustrated through a case study for evaluation of wastewater treatment alternatives. [ABSTRACT FROM AUTHOR]

Supplier selection is considered to be one of the most critical activities of purchasing management in a supply chain. Selecting the right suppliers significantly reduces the purchasing cost and improves corporate competitiveness. Diverse methods have been developed to date, which address the needs of the supplier selection process. This article presents a review of non-deterministic analytical methods reported in the literature for supporting the supplier selection decision. The review is based on an extensive search in the academic literature from 2001 to 2013. A taxonomy of the supplier selection methods is presented by classifying the published supplier selection studies into two major categories as stochastic methods and fuzzy methods. These methods are further divided into individual approaches and integrated approaches. The objective of this research is threefold. First, it classifies the existing supplier selection literature according to the methods employed and determines the most prevalently used approaches, and also highlights main advantages and shortcomings of these approaches. Second, recent trends in supplier evaluation and selection methodologies are examined. Finally, this study identifies the most widely used decision criteria for supplier selection. [ABSTRACT FROM PUBLISHER]

Abstract: Many individual attributes considered for personnel selection such as organizing ability, creativity, personality, and leadership exhibit vagueness and imprecision. The fuzzy set theory appears as an essential tool to provide a decision framework that incorporates imprecise judgments inherent in the personnel selection process. In this paper, a fuzzy multi-criteria decision making (MCDM) algorithm using the principles of fusion of fuzzy information, 2-tuple linguistic representation model, and technique for order preference by similarity to ideal solution (TOPSIS) is developed. The proposed method is apt to manage information assessed using both linguistic and numerical scales in a decision making problem with multiple information sources. Furthermore, it enables managers to deal with heterogeneous information. The decision making framework presented in this paper employs ordered weighted averaging (OWA) operator that encompasses several operators as the aggregation operator since it can implement different aggregation rules by changing the order weights. The aggregation process is based on the unification of information by means of fuzzy sets on a basic linguistic term set (BLTS). Then, the unified information is transformed into linguistic 2-tuples in a way to rectify the problem of loss information of other fuzzy linguistic approaches. The computational procedure of the proposed framework is illustrated through a personnel selection problem reported in an earlier study. [Copyright &y& Elsevier]