SERVER SELECTION ON BASE OF Z-NUMBERS

The paper is devoted to the problem of multi criteria decision making under linguistic uncertainty. Information of different approaches for modeling linguistic uncertainty have been analyzed. The concept of z-numbers proposed by L. Zadeh have been presented. Z-number is presented as cortege of two fuzzy number A and B, where A is analyzed factor, B is reliability of A assessment. The method of conversion z-numbers into generalized fuzzy numbers have been applied. As test have been used server selection problem. As decision making model have been used weighted average method. All calculations and results are presented.The paper is devoted to the problem of multi criteria decision making under linguistic uncertainty. Information of different approaches for modeling linguistic uncertainty have been analyzed. The concept of z-numbers proposed by L. Zadeh have been presented. Z-number is presented as cortege of two fuzzy number A and B, where A is analyzed factor, B is reliability of A assessment. The method of conversion z-numbers into generalized fuzzy numbers have been applied. As test have been used server selection problem. As decision making model have been used weighted average method. All calculations and results are presented

МОДЕЛИРОВАНИЕ ЛИНГВИСТИЧЕСКОЙ НЕОПРЕДЕЛЕННОСТИ НА ОСНОВЕ Z-ЧИСЕЛ В СИСТЕМАХ МНОГОКРИТЕРИАЛЬНОГО ПРИНЯТИЯ РЕШЕНИЙ

The article is devoted to the problem of multi criteria decision making under linguistic uncertainty. Information of different approaches for modelling linguistic uncertainty have been analyzed. The concept of z- numbers proposed by L. Zadeh have been presented. Z-number is presented as cortege of two fuzzy number A and B, where A is analyzed factor, B is reliability of an assessment. The method of conversion z- numbers into generalized fuzzy numbers have been applied. As test problem have been used supplier selection problem. As decision making model have been used group weighted average method. All calculations and results were presented.The article is devoted to the problem of multi criteria decision making under linguistic uncertainty. Information of different approaches for modelling linguistic uncertainty have been analyzed. The concept of z- numbers proposed by L. Zadeh have been presented. Z-number is presented as cortege of two fuzzy number A and B, where A is analyzed factor, B is reliability of an assessment. The method of conversion z- numbers into generalized fuzzy numbers have been applied. As test problem have been used supplier selection problem. As decision making model have been used group weighted average method. All calculations and results were presented

Ranking Causes of Road Accident Occurrence Using Extended Interval Type-2 Fuzzy TOPSIS

Over the past century there has been a dramatic increase in the number of road accidents in Malaysia. Hence, it is necessary to create a decision making method which can consider various preferences and criteria in order to identify the main causes of the accidents. This paper proposes an Interval Type-2 Fuzzy Technique for Order Preference by Similarity to Ideal Solution (IT2FTOPSIS) method which provides a comprehensive valuation from experts. This method is developed based on the aggregation of experts’ opinions on preferred causes of road accidents. The extended IT2FTOPSIS employs a linguistic scales of positive and negative Interval Type-2 Trapezoidal Fuzzy Number (IT2TrFN) and hybrid averaging approach (from an ambiguity and type-reduction methods) to formulate a collective decision environment. Three authorised personnel from three Malaysian Government agencies were interviewed where they were asked to rank the causes. The analysis shows that the linguistic scales of positive and negative Interval Type-2 Trapezoidal Fuzzy Number (IT2TrFN) and hybrid averaging approach are effective in measuring the uncertainties in the interviewees’ responses. Thus this paper concludes that the extended IT2FTOPSIS is more aligned with the users’ decisions compared to the earlier IT2FTOPSIS. Keywords: Multiple criteria decision-making; interval type-2 fuzzy set; IT2FTOPSIS; road accident

Perbandingan Analisis Keputusan dalam Penentuan Lokasi Gudang Angkatan Laut Wilayah Barat

The development of a company is always related to its supporting facilities’ location, for instance, warehouse location. Usually, company choose the most strategic one to minimize its transportation cost, distribution route and time. As the result, it is clear that warehouse location determination is the key to company’s success in delivering consumer needs. Location determination is not only used in manufacturing problem, but it is also can be used in national defense problem, which is the case study of this research: Western Sea Sector Indonesian Navy. In national defense, national and regional development are important factors for maximizing Indonesian Navy’s strength. As an example, logistics capability improvement. Logistics is one of the most important parts to support warships in doing their maritime operations. So, strategy of determinating the best warehouse location is very crucial to make sure the distribution of goods went smoothly. This research uses Multi Criteria Decision Making (MCDM) as a method to solve location determination problem. Using a study case from main literature by Gunawan et al (2018), this research does another two methods for problem solving, they are Fuzzy Simple Additive Weighting (F-SAW) and Fuzzy Analytical Hierarchy Process (F-AHP). The main purpose of this research is to compare Fuzzy MCDM method, which is used by Gunawan et al (2018), with F-SAW and F-AHP which is calculated in this research. Result shows that Naval Base III is the best location from Fuzzy MCDM and F-AHP, but the best location from F-SAW method is Naval Base I

Perbandingan Analisis Keputusan dalam Penentuan Lokasi Gudang Angkatan Laut Wilayah Barat

The development of a company is always related to its supporting facilities’ location, for instance, warehouse location. Usually, company choose the most strategic one to minimize its transportation cost, distribution route and time. As the result, it is clear that warehouse location determination is the key to company’s success in delivering consumer needs. Location determination is not only used in manufacturing problem, but it is also can be used in national defense problem, which is the case study of this research: Western Sea Sector Indonesian Navy. In national defense, national and regional development are important factors for maximizing Indonesian Navy’s strength. As an example, logistics capability improvement. Logistics is one of the most important parts to support warships in doing their maritime operations. So, strategy of determinating the best warehouse location is very crucial to make sure the distribution of goods went smoothly. This research uses Multi Criteria Decision Making (MCDM) as a method to solve location determination problem. Using a study case from main literature by Gunawan et al (2018), this research does another two methods for problem solving, they are Fuzzy Simple Additive Weighting (F-SAW) and Fuzzy Analytical Hierarchy Process (F-AHP). The main purpose of this research is to compare Fuzzy MCDM method, which is used by Gunawan et al (2018), with F-SAW and F-AHP which is calculated in this research. Result shows that Naval Base III is the best location from Fuzzy MCDM and F-AHP, but the best location from F-SAW method is Naval Base I

TOPSIS Method for MADM based on Interval Trapezoidal Neutrosophic Number

TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is a very common method for Multiple Attribute Decision Making (MADM) problem in crisp as well as uncertain environment. The interval trapezoidal neutrosophic number can handle incomplete, indeterminate and inconsistent information which are generally occurred in uncertain environment. In this paper, we propose TOPSIS method for MADM, where the rating values of the attributes are interval trapezoidal neutrosophic numbers and the weight information of the attributes are known or partially known or completely unknown. We develop optimization models to obtain weights of the attributes with the help of maximum deviation strategy for partially known and completely unknown cases. Finally, we provide a numerical example to illustrate the proposed approach and make a comparative analysis

Fuzzy Logic in Decision Support: Methods, Applications and Future Trends

During the last decades, the art and science of fuzzy logic have witnessed significant developments and have found applications in many active areas, such as pattern recognition, classification, control systems, etc. A lot of research has demonstrated the ability of fuzzy logic in dealing with vague and uncertain linguistic information. For the purpose of representing human perception, fuzzy logic has been employed as an effective tool in intelligent decision making. Due to the emergence of various studies on fuzzy logic-based decision-making methods, it is necessary to make a comprehensive overview of published papers in this field and their applications. This paper covers a wide range of both theoretical and practical applications of fuzzy logic in decision making. It has been grouped into five parts: to explain the role of fuzzy logic in decision making, we first present some basic ideas underlying different types of fuzzy logic and the structure of the fuzzy logic system. Then, we make a review of evaluation methods, prediction methods, decision support algorithms, group decision-making methods based on fuzzy logic. Applications of these methods are further reviewed. Finally, some challenges and future trends are given from different perspectives. This paper illustrates that the combination of fuzzy logic and decision making method has an extensive research prospect. It can help researchers to identify the frontiers of fuzzy logic in the field of decision making

Fuzzy belief structure based VIKOR method: an application for ranking delay causes of Tehran metro system by FMEA criteria

Public transport is a critical part of civilization in this decade. The amount of money invested and the criticality of transferring people in an acceptable time and without any conflict made it a challenging problem for managers, especially in metropolises. Absolutely, making effective decisions in this area requires considering different aspects. Waiting time is a key criterion in apprising quality of public transport. In this paper, a real world case study of ranking causes of delay in Tehran (Iran) metro system is solved by developing multi attribute group decision-making VIšeKriterijumska Optimizacija I KOmpromisno Rešenje (in Serbian, VIKOR) method under uncertainty, where this uncertainty is captured by Fuzzy Belief Structures (FBS). The obtained results are then compared with a previously proposed Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method with FBSs. The results show that human related issues, along with the problems related to line and transportation system are the most important causes of delay. The obtained results of the problem seem acceptable for decision makers

MULTI-ATTRIBUTE DECISION MAKING METHOD BASED ON BONFERRONI MEAN OPERATOR AND POSSIBILITY DEGREE OF INTERVAL TYPE-2 TRAPEZOIDAL FUZZY SETS

Abstract. This paper proposes a new approach based on Bonferroni mean operator and possibility degree to solve fuzzy multi-attribute decision making (FMADM) problems in which the attribute value takes the form of interval type-2 fuzzy numbers. We introduce the concepts of interval possibility mean value and present a new method for calculating the possibility degree of two interval trapezoidal type-2 fuzzy sets (IT2 TrFSs). Then, we develop two aggregation techniques, which are called the interval type-2 trapezoidal fuzzy Bonferroni mean (IT2TFBM) operator and the interval type-2 trapezoidal fuzzy weighted Bonferroni mean (IT2TFWBM) operator. We study their properties and discuss their special cases. Based on the IT2TFWBM operator and the possibility degree, a new method of multi-attribute decision making with interval type-2 trapezoidal fuzzy information is proposed. Finally, an illustrative example is given to verify the developed approaches and to demonstrate their practicality and effectiveness