• Journal of Information Processing Systems
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• v.7 no.3
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• pp.473-518
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• 2011

Software measurement is a key factor in managing, controlling, and improving the software development processes. Software quality is one of the most important factors for assessing the global competitive position of any software company. Thus the quantification of quality parameters and integrating them into quality models is very essential. Software quality criteria are not very easily measured and quantified. Many attempts have been made to exactly quantify the software quality parameters using various models such as ISO/IEC 9126 Quality Model, Boehm's Model, McCall's model, etc. In this paper an attempt has been made to provide a tool for precisely quantifying software quality factors with the help of quality factors stated in ISO/IEC 9126 model. Due to the unpredictable nature of the software quality attributes, the fuzzy multi criteria approach has been used to evolve the quality of the software.

• Smart Structures and Systems
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• v.19 no.3
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• pp.323-333
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• 2017

Waste materials in concrete have been considered as one of the most important issues by the authorities, policy makers and researchers to maintain engineering serviceability in terms of economy, durability and sustainability. Therefore, evaluation and selection of waste materials with respect to multi criteria decision making (MCDM) for the construction industry has been gained importance for recovery and reuse. In this paper, Choquet integral based fuzzy approach is proposed for evaluating the most suitable waste materials with respect to compressive strength, tensile strength, flexural strength, compactness, toughness (resistivity for dynamic loads), water absorption and accessibility. On conclusion, waste tyre and silica fume were determined as the most suitable waste materials for concrete production. The obtained results are recommended to assist the authorities on configuring well designed strategies for construction industry with disposal materials.

• Journal of the Korean Society of Safety
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• v.20 no.1 s.69
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• pp.126-132
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• 2005

The purpose of this study is to propose a method to evaluate task complexity using CIFs(Complexity Influencing Factors). We developed a method that CIFs can be used in the evaluation of task complexity using fuzzy linguistic approach. That is, a fuzzy linguistic multi-criteria method to assess task complexity in a specific task situation was proposed. The CIFs luting was assessed in linguistic terms, which are described by fuzzy numbers with triangular and trapezoidal membership function. A fuzzy weighted average algorithm, based on the extension principle, was employed to aggregate these fuzzy numbers. Finally, the method was validated by experimental approach. In the result, it was validated that TCIM(Tink Complexity Index Method) is an efficient method to evaluate task complexity because the correlation coefficient between task performance time and TCI(Task Complexity Index) was 0.699.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.1-10
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• 2012

Supplier selection is an essential task within the purchasing function of supply chain management because it provides companies with opportunities to reduce various costs and realize stable and reliable production. However, many companies find it difficult to determine which suppliers should be targeted as each of them has varying strengths and weaknesses in performance which require careful screening by the purchaser. Moreover, information required to assess suppliers is not known precisely and typically fuzzy in nature. In this paper, therefore, fuzzy multi-objective linear programming (fuzzy MOLP) is presented under fuzzy goals: cost minimization, service level maximization and purchasing risk. To solve the problem, we introduce an enhanced two-phase approach of fuzzy linear programming for the supplier selection. In formulated problem, Analytical Hierarchy Process (AHP) is used to determine the weights of criteria, and Taguchi Loss Function is employed to quantify purchasing risk. Finally, we provide a set of alternative solution which enables decision maker (DM) to select the best compromise solution based on his/her preference. Numerical experiment is provided to demonstrate our approach.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.7
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• pp.1314-1323
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• 2011

The maintenance of generating units is implicitly related with power system reliability and has a tremendous bearing on the operation of the power system. A technique using a fuzzy search method which is based on fuzzy multi-criteria function has been proposed for GMS (generator maintenance scheduling) in order to consider multi-objective function. In this study, a new technique using combined fuzzy set theory and genetic algorithm(GA) is proposed for generator maintenance scheduling. The genetic algorithm(GA) is expected to make up for that fuzzy search method might search the local solution. The effectiveness of the proposed approach is demonstrated by the simulation results on a practical size test systems.

• Industrial Engineering and Management Systems
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• v.7 no.1
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• pp.99-107
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• 2008

This paper is concerned with scheduling in Flexible Manufacturing Systems (FMS) using a Fuzzy Logic (FL) approach. Four fuzzy input variables: machine allocated processing time, machine priority, machine available time and transportation priority are defined. The job priority is the output fuzzy variable, showing the priority status of a job to be selected for the next operation on a machine. The model will first select the machines and then assign operations based on a multi-criteria scheduling scheme. System/machine utilization, minimizing mean flow time and balancing machine usage will be covered. Experimental and comparative tests indicate the superiority of this fuzzy based scheduling model over the existing approaches.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.662-671
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• 2007

Since variety of construction projects with their individual specifications could be handled through different procurement systems, selection of the most appropriate project delivery system is a vital step towards more efficient project execution. The appropriate selection of project delivery system may also ensure more competent management of the project. Its impacts are not only limited to the first stages of the project, as it could also influence pre-construction, construction and operational phases of the project. Among different approaches exerted for this purpose, none has taken uncertainty into account, despite the fact that during first stages of the project most of the selection factors are still uncertain and not clearly defined. This paper, hence, aims to provide a fuzzy insight into the project delivery system selection. Through this approach more tangible model of the evaluation process may be presented. Proposed fuzzy method is indeed a multi criteria decision making model, based on the group of criteria, assigned for the evaluation procedure. A case study is also conducted, based on the opinion of an invented group of the experts.

• Industrial Engineering and Management Systems
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• v.13 no.1
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• pp.15-28
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• 2014

Evaluation of the implementation and performance of a firm's green supply chain management (GSCM) is an ongoing process. Balanced scorecard is a multi-criteria evaluation concept that highlights implementation and performance measures. The literature on the framework is abundant literature but scarce on how to build a hierarchical framework under uncertainty with dependence relations. Hence, this study proposes a hybrid approach, which includes applied interpretive structural modeling to build a hierarchical structure and uses the analytic network process to analyze the dependence relations. Additionally, this study applies the fuzzy set theory to determine linguistic preferences. Twenty dependence criteria are evaluated for a GSCM implemented firm in Taiwan. The result shows that the financial aspect and life cycle assessment are the most important performance and weighted criteria.

• Transactions of the Korean hydrogen and new energy society
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• v.20 no.1
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• pp.22-30
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• 2009

Energy environment has been changing rapidly such as the fluctuation of oil prices and the effect on UNFCCC. Oil price change affects Korea's economy heavily due to her poor natural resources and large dependence of consumed energy resources. Korea takes the 4th place of importing the crude oil and 9th place in $CO_2$ emissions with the 1st place of $CO_2$ emissions increasing rate. Considering the current statue of Korea including oil price change and UNFCCC, Korea will be expected to be the Annex I nation due to Korean energy environments and the quantity of $CO_2$ emission. Energy technology development is a crucial key to cope with Korea's national energy security and environments. In this study, we establish the framework, which allocates the relative weights of assessment criteria and sub-criteria, for assessing and selecting R&D programs of energy technologies strategically. We integrated fuzzy theory and analytic hierarchy process (AHP) approach since the fuzzy AHP approach reflects the vagueness of human thoughts and perception effectively as making pairwise comparisons of criteria and alternatives. The fundamental data of this research results will support R&D planning phase for policy-makers and the production of well focused R&D outcomes.

• Membrane and Water Treatment
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• v.14 no.2
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• pp.65-76
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• 2023

Given the limited water resources and the presence of multiple decision makers with different and usually conflicting objectives in the exploitation of water resources systems, especially dam's reservoirs; therefore, the decision to determine the optimal allocation of reservoir water among decision-makers and stakeholders is a difficult task. In this study, by combining a fuzzy VIKOR technique or fuzzy multi-criteria decision making (FMCDM) and the Young's bilateral bargaining model, a new method was developed to determine the optimal quantitative and qualitative water allocation of dam's reservoir water with the aim of increasing the utility of decision makers and stakeholders and reducing the conflicts among them. In this study, by identifying the stakeholders involved in the exploitation of the dam reservoir and determining their utility, the optimal points on trade-off curve with quantitative and qualitative objectives presented by Mojarabi et al. (2019) were ranked based on the quantitative and qualitative criteria, and economic, social and environmental factors using the fuzzy VIKOR technique. In the proposed method, the weights of the criteria were determined by each decision maker using the entropy method. The results of a fuzzy decision-making method demonstrated that the Young's bilateral bargaining model was developed to determine the point agreed between the decisions makers on the trade-off curve. In the proposed method, (a) the opinions of decision makers and stakeholders were considered according to different criteria in the exploitation of the dam reservoir, (b) because the decision makers considered the different factors in addition to quantitative and qualitative criteria, they were willing to participate in bargaining and reconsider their ideals, (c) due to the use of a fuzzy-logic based decision-making approach and considering different criteria, the utility of all decision makers was close to each other and the scope of bargaining became smaller, leading to an increase in the possibility of reaching an agreement in a shorter time period using game theory and (d) all qualitative judgments without considering explicitness of the decision makers were applied to the model using the fuzzy logic. The results of using the proposed method for the optimal exploitation of Iran's 15-Khordad dam reservoir over a 30-year period (1968-1997) showed the possibility of the agreement on the water allocation of the monthly total dissolved solids (TDS)=1,490 mg/L considering the different factors based on the opinions of decision makers and reducing conflicts among them.