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Öğe Analytical Hierarchy Process (AHP) in Fuzzy Environment(Springer Science and Business Media Deutschland GmbH, 2023) Hosseinzadeh Lotfi, F.; Allahviranloo, T.; Pedrycz, W.; Shahriari, M.; Sharafi, H.; Razipour, GhalehJough, S.This chapter provides an overview of hierarchical decision structures, focusing on the AHP and ANP methods. It explains how these structures break down complex problems and organize criteria, sub-criteria, and alternatives in a hierarchical manner. The Analytic Hierarchy Process (AHP) is explored in detail, including its step-by-step implementation process and practical examples. The chapter then introduces the Analytic Network Process (ANP), which extends AHP to decision problems with interdependencies and feedback loops. The construction of networks, calculation of priority weights, and interpretation of results within the ANP framework are discussed. Finally, Fuzzy AHP is introduced as a method that addresses the limitations of AHP by incorporating fuzzy sets theory, supported by real-world case studies. Fuzzy AHP allows decision-makers to express preferences in a flexible and nuanced manner, capturing uncertainties and ambiguity present in real-world scenarios. Its advantage lies in handling vague and imprecise information systematically, enabling the effective incorporation of subjective assessments and expert opinions © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.Öğe Applications of Preferential Voting in Industry and Society(Springer Science and Business Media Deutschland GmbH, 2023) Soltanifar, M.; Sharafi, H.; Hosseinzadeh Lotfi, F.; Pedrycz, W.; Allahviranloo, T.Preferential voting models as well as hybrid Multi-Attribute Decision Making methods based on these models are widely used as decision support tools in industry and society. In this chapter, the applications that have been presented so far in the industry and society of these models and methods are briefly stated. It should be noted that the application of preferential voting models and hybrid MADM methods presented based on them are not exclusive to the presented cases and the authors hope that this application will be expanded in the future. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Öğe Basic Concepts of Voting(Springer Science and Business Media Deutschland GmbH, 2023) Soltanifar, M.; Sharafi, H.; Hosseinzadeh Lotfi, F.; Pedrycz, W.; Allahviranloo, T.The problem of “election” using the aggregation of voters’ votes is one of the most important problems of group decision-making for which several models have been presented so far. Consider a group of people who need to make a group decision based on voters’ votes. Given that people have different opinions and tastes, how can they make a decision that includes all individual opinions? From such a simple issue to the choice of politicians, all of them require a collective decision. In this chapter, this concept and methods of aggregating individual votes to reach a collective decision are discussed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Öğe The Complex Proportional Assessment (COPRAS) in Uncertainty Environment(Springer Science and Business Media Deutschland GmbH, 2023) Hosseinzadeh Lotfi, F.; Allahviranloo, T.; Pedrycz, W.; Shahriari, M.; Sharafi, H.; Razipour, GhalehJough, S.In this chapter, the algorithm of COmplex PRoportional ASsessment (COPRAS) method with crisp data is explained and then it is applied to select among varied smart phones considering five different attributes. Afterward, Fuzzy COPRAS method is explained in detail. To choose the best investment, Fuzzy COPRAS method has been used, taking into account the conflicting criteria and according to a group of the experts’ opinion. Fuzzy COPRAS provides valuable tools for addressing multi-criteria decision-making challenges and fuzzy decision-making scenarios. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.Öğe The Criteria Importance Through Inter-Criteria Correlation (CRITIC) in Uncertainty Environment(Springer Science and Business Media Deutschland GmbH, 2023) Hosseinzadeh Lotfi, F.; Allahviranloo, T.; Pedrycz, W.; Shahriari, M.; Sharafi, H.; Razipour, GhalehJough, S.The chapter begins by discussing the conventional CRITIC method and its algorithm, providing a foundation for understanding the subsequent introduction of the fuzzy variant. An example scenario is presented to demonstrate the evaluation and prioritization of projects based on seven specific criteria. The CRITIC method is applied, allowing decision-makers to assess the relative importance of each criterion and make informed decisions regarding project selection. Subsequently, the chapter introduces the fuzzy extension of the CRITIC method. The algorithm of the fuzzy CRITIC is explained in detail, highlighting the utilization of fuzzy data to represent uncertain and imprecise information in decision-making. To illustrate the application of the fuzzy CRITIC method, a case study is presented involving the search for an optimal location for a solar farm. Fuzzy trapezoidal data is utilized to capture the inherent uncertainty associated with various location factors. The combination of theoretical explanations, algorithmic discussions, and practical examples offers a comprehensive understanding of the fuzzy CRITIC method's potential for decision-making in complex and uncertain environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.Öğe Elimination Choice Translating Reality (ELECTRE) in Uncertainty Environment(Springer Science and Business Media Deutschland GmbH, 2023) Hosseinzadeh Lotfi, F.; Allahviranloo, T.; Pedrycz, W.; Shahriari, M.; Sharafi, H.; Razipour, GhalehJough, S.This chapter explores the application of the ELECTRE method in both precise and fuzzy modes for decision-making. It discusses the concepts, strengths, and weaknesses of the method. The chapter covers the precise mode, addressing issues such as score assignment and rank reversal. It also introduces the fuzzy mode, incorporating fuzzy logic and sets for handling uncertainty. Practical examples demonstrate the effectiveness of ELECTRE in various domains. This chapter serves as a valuable resource for researchers and practitioners seeking to utilize ELECTRE for informed decision-making. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.Öğe Foundations of Decision(Springer Science and Business Media Deutschland GmbH, 2023) Hosseinzadeh Lotfi, F.; Allahviranloo, T.; Pedrycz, W.; Shahriari, M.; Sharafi, H.; Razipour, GhalehJough, S.Decisions unfold, guided by science’s light, in choices, science’s wisdom resides, for Guiding paths with less clarity. In this enlightening chapter on the Foundations of Decision Making, readers will embark on a journey through the intricate web of decision theory and decision science. Delving into the profound philosophy that underlies these concepts, we'll unravel the fundamental principles that guide human choices. With a systematic exploration of reputable domains and practical applications, readers will witness the transformative power of these principles in diverse contexts, from economics to psychology and beyond. We'll navigate through the Hierarchy of Decisions, dissecting the layers of choices from the mundane to the monumental, and in the process, gain invaluable insights into the art and science of decision-making. As we traverse this intellectual landscape, readers will acquire the skills to evaluate options with precision and make well-informed decisions based on robust reasoning. By the end of this chapter, readers will be able to comprehend and appreciate the fundamental principles and concepts that form the foundation of decision-making. They will develop a solid understanding of key components such as decision theory, rationality, and cognitive biases. With this knowledge, readers will acquire the necessary analytical skills to effectively recognize the complexity of decision-making scenarios, evaluate alternative options, and make informed decisions based on sound reasoning and evidence. Moreover, readers will gain a broader perspective on the significance of decision-making across various aspects of life, including personal, professional, and societal contexts. This chapter will lay a strong groundwork for readers’ journey towards becoming more confident and adept decision-makers © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.Öğe Fuzzy Introductory Concepts(Springer Science and Business Media Deutschland GmbH, 2023) Hosseinzadeh Lotfi, F.; Allahviranloo, T.; Pedrycz, W.; Shahriari, M.; Sharafi, H.; Razipour, GhalehJough, S.This chapter explores the fundamentals of fuzzy theory and introduces the concept of fuzzy type-2. Fuzzy sets, which allow for handling uncertainty and vagueness in data, are discussed as an extension of traditional binary set theory. Arithmetic operations on fuzzy sets, such as union, intersection, and complement, enable logical reasoning and informed decision-making based on fuzzy information. The chapter also covers triangular and trapezoidal fuzzy numbers, which provide a means to represent imprecise and uncertain quantities. These fuzzy numbers are essential for quantifying and reasoning with fuzzy data, with applications in various domains for modeling real-world phenomena. Furthermore, the chapter focuses on the ranking of fuzzy numbers using different functions. Techniques and tools for ranking fuzzy numbers are examined, offering insights into comparing and ordering fuzzy data based on their degrees of membership and uncertainty. This information is valuable for decision-making processes when dealing with fuzzy information. Overall, the chapter provides a comprehensive introduction to fuzzy theory and its practical applications, particularly in fuzzy type-2. By understanding fuzzy sets, arithmetic operations, triangular and trapezoidal fuzzy numbers, and the ranking of fuzzy numbers, readers gain a solid foundation in utilizing fuzzy logic and reasoning. This knowledge empowers them to make more informed decisions in domains where imprecise and uncertain data are prevalent. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.Öğe Group Preferential Voting(Springer Science and Business Media Deutschland GmbH, 2023) Soltanifar, M.; Sharafi, H.; Hosseinzadeh Lotfi, F.; Pedrycz, W.; Allahviranloo, T.What increases the power of a decision-making method as a decision support tool is the degree of satisfaction of its results. In many real-world issues, voters do not have an equal level of expertise. Since the classic voting models consider equal value for the votes of all the voters, it cannot give satisfactory results. This will reduce the power of preferential voting methods. In this chapter, group preferential voting methods are presented to handle the difference in the value of votes. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Öğe Hybrid Multi-attribute Decision-Making Methods Based on Preferential Voting(Springer Science and Business Media Deutschland GmbH, 2023) Soltanifar, M.; Sharafi, H.; Hosseinzadeh Lotfi, F.; Pedrycz, W.; Allahviranloo, T.In addition to the direct application of preferential voting models in a voting process, these models can be combined with other Multi-Attribute Decision Making (MADM) methods to improve them and achieve new hybrid models. In this chapter, some hybrid MADM methods based on preferential voting models are presented. New hybrid models with the help of preferential voting models have become more powerful tools for decision support. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Öğe Introduction to Data Envelopment Analysis(Springer Science and Business Media Deutschland GmbH, 2023) Soltanifar, M.; Sharafi, H.; Hosseinzadeh Lotfi, F.; Pedrycz, W.; Allahviranloo, T.Efficiency is a management concept that has a long history in management science. Efficiency shows that an organization has used its resources in a good way in order to produce the best performance at a point in time. One of the appropriate and efficient tools in the field of efficiency measurement and evaluation is Data Envelopment Analysis (DEA), which is used as a non-parametric method to calculate the efficiency of decision-making units. In fact, DEA is based on a series of optimizations using linear programming, which is used to evaluate the efficiency of Decision-Making Units (DMUs) that have multiple inputs and multiple outputs. This method is based on an optimistic policy that can evaluate DMUs in the best conditions. In this chapter, the basic methods and basic principles of DEA are discussed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Öğe Introduction to Fuzzy Logic(Springer Science and Business Media Deutschland GmbH, 2023) Soltanifar, M.; Sharafi, H.; Hosseinzadeh Lotfi, F.; Pedrycz, W.; Allahviranloo, T.In real world, we sometimes face situations where we don’t know which decision is right or wrong, and the correct action is hidden from view. At this time, “fuzzy logic” offers a flexible and valuable proposition. In this way, the amount of uncertainty can be determined for each situation. For this reason, fuzzy logic is sometimes called doubtful logic because its results are created with doubts. In this chapter, this logic begins with the presentation of fuzzy sets and continues with the definitions of fuzzy numbers. Finally, one of the applications of fuzzy numbers, i.e. converting linguistic terms into fuzzy numbers for decision making in fuzzy logic, is presented. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Öğe The Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) in Uncertainty Environment(Springer Science and Business Media Deutschland GmbH, 2023) Hosseinzadeh Lotfi, F.; Allahviranloo, T.; Pedrycz, W.; Shahriari, M.; Sharafi, H.; Razipour, GhalehJough, S.This chapter introduces the Fuzzy MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) method. It begins by providing an overview of the MACBETH method, emphasizing its principles and applications in decision-making contexts. Then proceeds to outline the six-step algorithm of the MACBETH method, offering a comprehensive understanding of its systematic process. This algorithm serves as a guide for readers to grasp the practical implementation of MACBETH in evaluating alternatives based on multiple criteria. The fuzzy MACBETH method is discussed in detail, emphasizing its ability to handle uncertainty and vagueness in decision-making situations. To illustrate its practicality, the method is applied to choose a manager for the Research and Development (R&D) department of a company. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.Öğe Multi Attributive Border Approximation Area Comparison (MABAC) in Uncertainty Environment(Springer Science and Business Media Deutschland GmbH, 2023) Hosseinzadeh Lotfi, F.; Allahviranloo, T.; Pedrycz, W.; Shahriari, M.; Sharafi, H.; Razipour, GhalehJough, S.This chapter introduces the concept of Fuzzy MABAC (Multi-Attributive Border Approximation Area Comparison), an innovative Multiple Attribute Decision Making (MADM) method. The chapter begins by providing a comprehensive overview of the MABAC method. To illustrate the practical implementation of MABAC, a numerical example is presented, utilizing crisp data. Building upon the understanding of MABAC, the chapter then explore the intricacies of fuzzy MABAC. The algorithm for fuzzy MABAC is elucidated and its handling in decision-making problems involving imprecise or uncertain data is demonstrated. To illustrate the efficacy of fuzzy MABAC, the method is applied to rank bank clerks according to four criteria. The step-by-step process of employing fuzzy MABAC to determine rankings is discussed. By the end of this chapter, readers will have a comprehensive understanding of both MABAC and fuzzy MABAC, and their practical applications in MADM. The numerical example and the real-life application in ranking bank clerks highlight the potential of fuzzy MABAC as an effective decision-making tool in complex scenarios. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.Öğe The Multi-Objective Optimization Ratio Analysis (MOORA) in Uncertainty Environment(Springer Science and Business Media Deutschland GmbH, 2023) Hosseinzadeh Lotfi, F.; Allahviranloo, T.; Pedrycz, W.; Shahriari, M.; Sharafi, H.; Razipour, GhalehJough, S.This chapter explores the MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) method as a powerful tool for solving multi-criteria problems. The MOORA method provides a systematic approach to decision-making by considering multiple criteria and their relative importance. Through an example from the real world, the application of the MOORA method is demonstrated, highlighting its effectiveness in ranking alternatives and aiding decision-making processes. Furthermore, this chapter discusses the extension of the MOORA method in fuzzy environment. Incorporating fuzzy sets and fuzzy numbers, enables the MOORA method accommodate vague and subjective assessments of criteria and alternatives. A real-world example is presented to showcase the application of the fuzzy MOORA method and illustrate its advantages and limitations in dealing with fuzzy data. Additionally, preferential voting has been used for aggregating the rankings. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.Öğe Non-Compensatory Methods in Uncertainty Environment(Springer Science and Business Media Deutschland GmbH, 2023) Hosseinzadeh Lotfi, F.; Allahviranloo, T.; Pedrycz, W.; Shahriari, M.; Sharafi, H.; Razipour, GhalehJough, S.This chapter discusses non-compensatory methods with fuzzy indicator values. These methods are applicable to problems where we want to select an alternative among the available choices. The methods discussed in this chapter include fuzzy Lexicographic, fuzzy Dominance, fuzzy Max–Min, fuzzy Conjunctive Satisfying, and fuzzy Disjunctive Satisfying. In all methods, the assumption is that all indicator values are fuzzy. Non-compensatory methods have been developed using fuzzy ranking functions, and examples are provided for each method. Different ranking functions are used to solve the examples. In all examples, the results depend not only on the fuzzy values of the indicators but also on the ranking function. All non-compensatory methods are utilized in a fuzzy environment to choose one alternative from the available choices. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.Öğe Preferential Voting Based on Data Envelopment Analysis(Springer Science and Business Media Deutschland GmbH, 2023) Soltanifar, M.; Sharafi, H.; Hosseinzadeh Lotfi, F.; Pedrycz, W.; Allahviranloo, T.Voting is always considered as one of the best group decision making methods in decision science. How voters’ votes are aggregated in the preferential voting process has a direct impact on the final voting results and is a very important issue. In this chapter, a suitable voting model is presented using the technique of Data Envelopment Analysis (DEA), which makes the voting results more justified and logical. The use of weight restrictions and the use of the concept of discrimination intensity functions increase the interaction with the decision maker in the presented model and turn the model into a powerful tool for decision support. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Öğe Preferential Voting Based on the Logic of Uncertainty(Springer Science and Business Media Deutschland GmbH, 2023) Soltanifar, M.; Sharafi, H.; Hosseinzadeh Lotfi, F.; Pedrycz, W.; Allahviranloo, T.Considering the logic of uncertainty in operations research methods usually makes the results of these methods more justified. In this chapter, the preferential voting model with fuzzy logic is presented. Linguistic term is used in this model. In addition to presenting the application of the presented model, the presented fuzzy preferential voting model will also be used to present a hybrid method of fuzzy multi-attribute decision making. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Öğe Preferential Voting Based on Undesirable Voters(Springer Science and Business Media Deutschland GmbH, 2023) Soltanifar, M.; Sharafi, H.; Hosseinzadeh Lotfi, F.; Pedrycz, W.; Allahviranloo, T.The idea that voters are divided into desirable and undesirable categories, and desirable category votes have a positive effect and undesirable category votes have a negative effect on candidate evaluation is a theory that may not seem very logical at first glance. But proposing this theory and presenting models for handling the preferential voting process in the presence of desirable and undesirable voters will eventually lead to the proposal of a method to solve MADM problems, which has many advantages. In this chapter, preferential voting and group preferential voting in the presence of desirable and undesirable voters are examined and models for handling such voters are presented. Then, using the presented models, a MADM method will be presented to determine the weights of alternatives and criteria, where there is no need to change the nature of the criteria in the process of normalizing the decision matrix. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Öğe Ranking Models in Preferential Voting(Springer Science and Business Media Deutschland GmbH, 2023) Soltanifar, M.; Sharafi, H.; Hosseinzadeh Lotfi, F.; Pedrycz, W.; Allahviranloo, T.Vote aggregation models in preferential voting that use DEA policy use an optimistic view in candidate evaluation. This increases the number of efficient candidates. Basic models do not allow discrimination between efficient candidates. Therefore, researchers presented ranking models from different perspectives. Some of these models focus on vote structure and some on weight restrictions. In this chapter, some of these models and ideas are presented. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
