scholarly journals Application of Improved Best Worst Method (BWM) in Real-World Problems

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1342 ◽  
Author(s):  
Dragan Pamučar ◽  
Fatih Ecer ◽  
Goran Cirovic ◽  
Melfi A. Arlasheedi

The Best Worst Method (BWM) represents a powerful tool for multi-criteria decision-making and defining criteria weight coefficients. However, while solving real-world problems, there are specific multi-criteria problems where several criteria exert the same influence on decision-making. In such situations, the traditional postulates of the BWM imply the defining of one best criterion and one worst criterion from within a set of observed criteria. In this paper, an improvement of the traditional BWM that eliminates this problem is presented. The improved BWM (BWM-I) offers the possibility for decision-makers to express their preferences even in cases where there is more than one best and worst criterion. The development enables the following: (1) the BWM-I enables us to express experts’ preferences irrespective of the number of the best/worst criteria in a set of evaluation criteria; (2) the application of the BWM-I reduces the possibility of making a mistake while comparing pairs of criteria, which increases the reliability of the results; and (3) the BWM-I is characterized by its flexibility, which is expressed through the possibility of the realistic processing of experts’ preferences irrespective of the number of the criteria that have the same significance and the possibility of the transformation of the BWM-I into the traditional BWM (should there be a unique best/worst criterion). To present the applicability of the BWM-I, it was applied to defining the weight coefficients of the criteria in the field of renewable energy and their ranking.

2013 ◽  
Vol 14 (5) ◽  
pp. 957-978 ◽  
Author(s):  
Abdolreza Yazdani-Chamzini ◽  
Mohammad Majid Fouladgar ◽  
Edmundas Kazimieras Zavadskas ◽  
S. Hamzeh Haji Moini

Renewable energies are well-known as one of the most important energy resources not only due to limited other energy resources, but also due to environmental problems associated with air pollutants and greenhouse gas emissions. Renewable energy project selection is a multi actors and sophisticated problem because it is a need to incorporate social, economic, technological, and environmental considerations. Multi criteria decision making (MCDM) methods are powerful tools to evaluate and rank the alternatives among a pool of alternatives and select the best one. COPRAS (COmplex PRoportional ASsessment) is an MCDM technique which determines the best alternative by calculating the ratio to the ideal solution and the negative ideal solution. On the other hand, analytical hierarchy process (AHP) is widely used in order to calculate the importance weights of evaluation criteria. In this paper an integrated COPRAS-AHP methodology is proposed to select the best renewable energy project. In order to validate the output of the proposed model, the model is compared with five MCDM tools. The results of this paper demonstrate the capability and effectiveness of the proposed model in selecting the most appropriate renewable energy option among the existing alternatives.


Author(s):  
Onur Önay

In the study, The Nomenclature of Territorial Units for Statistics (NUTS) Level 1 regions of Turkey are evaluated with MULTIMOORA Method according to banking sector using hypothetical data which are adapted from real world data. There are 12 regions as alternatives which are assessed with 6 objectives. Calculations are made by using MS Excel which is powerful spreadsheet software. This application is an example how multi criteria decision making methods can use when a manager making decision. Results are given as lists of regions ranking and commented. By this way, it is shown that how the multi criteria decision making methods can help to decision makers.


2018 ◽  
Vol 24 (2) ◽  
pp. 739-764 ◽  
Author(s):  
Kajal CHATTERJEE ◽  
Samarjit KAR

In recent era of globalization, the world is perceiving an alarming rise in its energy consumption resulting in shortage of fossil fuels in near future. Developing countries like India, with fast growing population and economy, is planning to explore among its existing renewable energy sources to meet the acute shortage of overall domestic energy supply. For balancing diverse ecological, social, technical and economic features, selection among alternative renewable energy must be addressed in a multi-criteria context considering both subjective and objective criteria weights. In the proposed COPRAS-Z methodology, Z-number model fuzzy numbers with reliability degree to represents imprecise judgment of decision makers’ in evaluating the weights of criteria and selection of renewable energy alternatives. The fuzzy numbers are defuzzified and renewable energy alternatives are prioritized as per COmplex PropoRtional ASsessment (COPRAS) decision making method in terms of significance and utility degree. A sensitivity analysis is done to observe the variation in ranking of the criteria, by altering the coefficient of both subjective and objective weight. Also, the proposed methodology is compared with existing multi-criteria decision making (MCDM) methods for checking validity of the obtained ranking result.


Author(s):  
Mehdi Keshavarz Ghorabaee ◽  
Edmundas Kazimieras Zavadskas ◽  
Maghsoud Amiri ◽  
Zenonas Turskis

In the real-world problems, we are likely confronted with some alternatives that eed to be evaluated with respect to multiple conflicting criteria. Multi-criteria ecision-making (MCDM) refers to making decisions in such a situation. There are any methods and techniques available for solving MCDM problems. The evaluation ased on distance from average solution (EDAS) method is an efficient multi-criteria ecision-making method. Because the uncertainty is usually an inevitable part of he MCDM problems, fuzzy MCDM methods can be very useful for dealing with the eal-world decision-making problems. In this study, we extend the EDAS method o handle the MCDM problems in the fuzzy environment. A case study of supplier election is used to show the procedure of the proposed method and applicability of t. Also, we perform a sensitivity analysis by using simulated weights for criteria to xamine the stability and validity of the results of the proposed method. The results f this study show that the extended fuzzy EDAS method is efficient and has good tability for solving MCDM problems.


2013 ◽  
Vol 3 (3) ◽  
Author(s):  
Milica Stojanovic

Multi-criteria analysis involves defining each criterion using attributes, based on a suitable alternative for achieving objectives. The method used in multi-criteria analysis is Analytical Hierarchy Process. Analytical hierarchical process (AHP) is a tool in the analysis of decision making, created in order to assist decision-makers in solving complex decision problems involving large number of decision makers, large number of criteria and in multiple time periods. AHP method is used for selecting the best renewable energy systems. The aim is to, by using the method of AHP, demonstrate which of the analyzed renewable sources of energy is the most convenient to be used in a sustainable system. Key words:energy, multi-criteria decision making, analytical hierarchy process


Author(s):  
Merve Cengiz Toklu

Decision-making process is the selection of the most appropriate one among the alternatives. Different selection criteria are considered in the decision-making process. Simultaneous assessment of different evaluation criteria may not always be possible. Multi-criteria decision-making techniques provide an easily applicable mathematical solution in this respect. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is one of the multi-criteria decision-making techniques. This method is used in many problems in literature and allows multiple decision makers to choose the most suitable alternative by evaluating them together with different criteria. Assessments of decision makers may include linguistic statements. In this case, the Fuzzy Logic approach can be used. In this chapter, Fuzzy TOPSIS method is explained with a detailed numerical example.


Author(s):  
Mehdi Keshavarz-Ghorabaee

Multi-criteria decision-making (MCDM) methods and techniques have been applied to many real-world problems in different fields of engineering science and technology. The evaluation based on distance from average solution (EDAS) method is a new and efficient MCDM method. The aim of this study is to propose a modification to address two exceptional cases in which the EDAS method fails to solve an MCDM problem.


Author(s):  
Jian Li ◽  
Li-li Niu ◽  
Qiongxia Chen ◽  
Zhong-xing Wang

AbstractHesitant fuzzy preference relations (HFPRs) have been widely applied in multicriteria decision-making (MCDM) for their ability to efficiently express hesitant information. To address the situation where HFPRs are necessary, this paper develops several decision-making models integrating HFPRs with the best worst method (BWM). First, consistency measures from the perspectives of additive/multiplicative consistent hesitant fuzzy best worst preference relations (HFBWPRs) are introduced. Second, several decision-making models are developed in view of the proposed additive/multiplicatively consistent HFBWPRs. The main characteristic of the constructed models is that they consider all the values included in the HFBWPRs and consider the same and different compromise limit constraints. Third, an absolute programming model is developed to obtain the decision-makers’ objective weights utilizing the information of optimal priority weight vectors and provides the calculation of decision-makers’ comprehensive weights. Finally, a framework of the MCDM procedure based on hesitant fuzzy BWM is introduced, and an illustrative example in conjunction with comparative analysis is provided to demonstrate the feasibility and efficiency of the proposed models.


2021 ◽  
pp. 1-21
Author(s):  
Muhammad Shabir ◽  
Rimsha Mushtaq ◽  
Munazza Naz

In this paper, we focus on two main objectives. Firstly, we define some binary and unary operations on N-soft sets and study their algebraic properties. In unary operations, three different types of complements are studied. We prove De Morgan’s laws concerning top complements and for bottom complements for N-soft sets where N is fixed and provide a counterexample to show that De Morgan’s laws do not hold if we take different N. Then, we study different collections of N-soft sets which become idempotent commutative monoids and consequently show, that, these monoids give rise to hemirings of N-soft sets. Some of these hemirings are turned out as lattices. Finally, we show that the collection of all N-soft sets with full parameter set E and collection of all N-soft sets with parameter subset A are Stone Algebras. The second objective is to integrate the well-known technique of TOPSIS and N-soft set-based mathematical models from the real world. We discuss a hybrid model of multi-criteria decision-making combining the TOPSIS and N-soft sets and present an algorithm with implementation on the selection of the best model of laptop.


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