Prioritized Information Fusion Method for Triangular Fuzzy Information and Its Application to Multiple Attribute Decision Making

Verma, Rajkumar; Sharma, Bhudev

doi:10.1142/s0218488516500136

Cited by 14 publications

(4 citation statements)

References 20 publications

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“…By using the QOWA operator as an expected value of decision maker, we will able to calculate the deviation measure from minimum value to maximum value of the data set. Corresponding to (10) and (11), we propose the following deviation measures with QOWA as i. Type-1 deviation measure with QOWA operator:…”

Section: Decision Attitudes Weightsmentioning

confidence: 99%

“…Aggregation operators are used for fusing several input values into a single output value and have been used throughout various fields including mathematics, computer and engineering sciences, economics and finance, physics and natural sciences. In the literature, different aggregation operators are developed by many researchers for aggregating the information . In 1988, Yager introduced the ordered weighted average (OWA) operator for considering the attitudinal character of the decision makers in the aggregation process.…”

Section: Introductionmentioning

confidence: 99%

“…In the literature, different aggregation operators are developed by many researchers for aggregating the information. [3][4][5][6][7][8][9][10][11] In 1988, Yager 12 introduced the ordered weighted average (OWA) operator for considering the attitudinal character of the decision makers in the aggregation process. A basic feature of the OWA operator is the reordering step of input arguments in descending order.…”

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confidence: 99%

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Variance measures with ordered weighted aggregation operators

Verma

Merigó

2019

Int J Intell Syst

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The variance is a statistical measure widely used in many real‐life application areas. This article makes an extensive investigation on variance measure in the case when the uncertainty is not of a probabilistic nature. It generalizes the notion of variance as well as the theory of ordered weighted aggregation operators. First, we extend the idea of representative value/expected value of a decision maker and develop some new deviation measures based on ordered weighted geometric (OWG) average and ordered weighted harmonic average (OWHA) operators. These measures are developed with the consideration that decision maker can represent his/her attitudinal expected value by using any one of the ordered weighted aggregation (OWA) operators. Further, this study proposes some deviation measures by using the generalized‐OWA (GOWA) and Quasi‐OWA as an expected value of decision maker and discusses their particular cases. Second, a number of generalized deviation measures are introduced by taking the generalized arithmetic mean and quasi‐arithmetic means for aggregation of the individual dispersion. This approach provides an ability to the user for considering the deviation under different realistic‐scenario. These measures lead to many interesting particular and limiting cases and enrich the use of ordered weighted aggregation operators in the variance.

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Section: Decision Attitudes Weightsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Variance measures with ordered weighted aggregation operators

Verma

Merigó

2019

Int J Intell Syst

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“…Here prioritization is existent between the criteria "safety" and "cost", and safety has a higher priority. Although the kind of criteria-interdependences has just been proposed in recent years, the corresponding problems have been validated to be existent and corresponding methods have been perfectly applied into the problems of information retrieval (da Costa Pereira et al 2011;Verma, Sharma 2016), preference voting (Amin, Sadeghi 2010), threat evaluation of aerial targets (Huang et al 2010) and target type recognition (Xu et al 2010). At present, almost all relevant researchers contribute themselves to how to aggregate evaluating information of multiple criteria with prioritizations among them.…”

Section: Introductionmentioning

confidence: 99%

Systematic Decision Making: A Extended Multi-Criteria Decision Making Model

Zhang

Liu

2017

Technological and Economic Development of Economy

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Considering some complex multi-criteria decision making (MCDM) problems, in which decision environment is dynamic, there are various interdependences among criteria, and plans (systematized alternatives) consisting of multiple time sequential interdependent actions, cannot be well handled by means of the existing MCDM methods, therefore, we develop a systematic decision making (SDM) as an improvement and supplement of the classic MCDM in this paper. The SDM is for prescribing methods of evaluating and selecting the most favourite plan (a system) from a group of feasible ones concerning influences of time-varying criteria system under dynamic external environment. Through detailed analysis, we separate a SDM problem into multi-period MCDM subproblems, and then a plan can be a combination of time sequential strategies in which each strategy (a subset of actions) is a feasible decision choice of corresponding MCDM sub-problem. After clarifying variety of interdependences, interactions and interrelationships in the SDM problems, such as criteria-interdependences, action-interdependences, interactions between criteria and criteria system, interactions between actions and strategies, interactions between strategies and plans, interactions between internal environment (criteria system) and external environment, feedbacks from external environment to the corresponding MCDM sub-problems, and interrelationships among MCDM sub-problems and so on, we transform the SDM into multi-period interrelated MCDM model which can be dealt with more easily by using multiple optimization models. At the end of the paper, three typical properties of the SDM are proposed and most of the existing MCDM models are pointed out as special cases of the SDM.

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Water Policies and Conflict Resolution of Public Participation Decision-Making Processes Using Prioritized Ordered Weighted Averaging (OWA) Operators

Llopis-Albert

Merigó

Liao

et al. 2017

Water Resour Manage

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There is a growing interest in environmental policies about how to implement public participation engagement in the context of water resources management. This paper presents a robust methodology, based on ordered weighted averaging (OWA) operators, to conflict resolution decision-making problems under uncertain environments due to both information and stakeholders' preferences. The methodology allows integrating heterogeneous interests of the general public and stakeholders on account of their different degree of acceptance or preference and level of influence or power regarding the measures and policies to be adopted, and also of their level of involvement (i.e., information supply, consultation and active involvement). These considerations lead to different environmental and socioeconomic outcomes, and levels of stakeholders' satisfaction. The methodology establishes a prioritization relationship over the stakeholders. The individual stakeholders' preferences are aggregated through their associated weights, which depend on the satisfaction of the higher priority decision maker. The methodology ranks the optimal management strategies to maximize the stakeholders' satisfaction. It has been successfully applied to a real case study, providing greater fairness, transparency, social equity and consensus among actors. Furthermore, it provides support to environmental policies, such as the EU Water Framework Directive(WFD), improving integrated water management while covering a wide range of objectives, management alternatives and stakeholders.

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Prioritized Information Fusion Method for Triangular Fuzzy Information and Its Application to Multiple Attribute Decision Making

Cited by 14 publications

References 20 publications

Variance measures with ordered weighted aggregation operators

Variance measures with ordered weighted aggregation operators

Systematic Decision Making: A Extended Multi-Criteria Decision Making Model

Water Policies and Conflict Resolution of Public Participation Decision-Making Processes Using Prioritized Ordered Weighted Averaging (OWA) Operators

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