An improved method for satellite emergency mission scheduling scheme group decision-making incorporating PSO and MULTIMOORA

2021 ◽  
pp. 1-17
Author(s):  
Bing Yan ◽  
Yanjun Wang ◽  
Wei Xia ◽  
Xiaoxuan Hu ◽  
Huawei Ma ◽  
...  
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Selection Process ◽  
Evaluation Model ◽  
Information Aggregation ◽  
Pso Algorithm ◽  
Satellite Mission ◽  
Scheduling Scheme ◽  
Multimoora Method

Satellite emergency mission scheduling scheme group decision making (SEMSSGDM) is a key part of satellite mission scheduling research. An appropriate evaluation model can provide a dependable and sustainable improvement and guide the functioning of emergency mission scheduling. Consequently, this research is devoted to proposing a novel decision-making method that employs a novel consensus model with hesitant fuzzy 2-tuple linguistic sets (HF2TLSs) to eliminate disagreements among satellite dispatchers and reach consensus in scheme decision-making. Within the novel method, it proposes a distance measurement function based on Hausdorff distance with HF2TLS to gauge the fit and similarity across satellite dispatchers. Additionally, a consensus reaching process (CRP) is designed to adjust the judgement of satellite dispatchers taking into account the trust degree to improve consensus. Within the selection process, a combination of the particle swarm optimization (PSO) algorithm and the MULTIplicative MOORA (MULTIMOORA) method is applied, where PSO is performed to improve the accuracy of information aggregation, and the MULTIMOORA method is used to develop the robustness of the selection results. Lastly, an applicative example validates the effectiveness of the method based on a mission scheduling intelligent decision simulation system.

Multicriteria Group Decision Making Using Fuzzy Approach for Evaluating Criteria of Electrician

2016 ◽  
Vol 6 (5) ◽  
pp. 2462 ◽  
Author(s):  
Wiwien Hadikurniawati ◽  
Khabib Mustofa
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Selection Process ◽  
Subjective Assessment ◽  
Fuzzy Approach ◽  
Multicriteria Group Decision Making ◽  
Alternative Ranking ◽  
Index Of Optimism

<p>This paper presents an approach of fuzzy multicriteria group decision making in determining alternatives to solve the selection problem of the electrician  through  a competency test.   Fuzzy approach is used to determine the highest priority of alternative electrician who has knowledge and ability that best fits the given parameters. Linguistic variables are presented by triangular fuzzy numbers. They are used to represent a subjective assessment of the decision-makers so that uncertainty and imprecision in the selection process can be minimized. Fuzzy approach require transforming crisp data to fuzzy numbers. Output of the best alternatives is generated by ranking method. Ranking has been made base on eight criteria which make the evaluation basis of each alternative. Ranking of the results is determined using different value of optimism index (). The fuzzy multi criteria decision making (FMCDM) calculation is using the best alternative using three value of optimism index. The result of calculation shows that the same alternative reached from different index of optimism. This alternative is the highest priority of decision making process.</p>

scholarly journals Generalized Ordered Weighted Simplified Neutrosophic Cosine Similarity Measure for Multiple Attribute Group Decision Making

2020 ◽  
Vol 14 (1) ◽  
pp. 51-62 ◽  
Author(s):  
Jun Ye
Keyword(s):  
Decision Making ◽  
Similarity Measure ◽  
Group Decision Making ◽  
Group Decision ◽  
Information Aggregation ◽  
Cosine Similarity ◽  
Weighted Averaging ◽  
Multiple Attribute ◽  
Special Cases ◽  
Cosine Similarity Measure

The paper proposes a generalized ordered weighted simplified neutrosophic cosine similarity (GOWSNCS) measure by combining the cosine similarity measure of simplified neutrosophic sets (SNSs) with the generalized ordered weighted averaging (GOWA) operator and investigates its properties and special cases. Then, the author develops a simplified neutrosophic group decision-making method based on the GOWSNCS measure to handle multiple attribute group decision-making problems with simplified neutrosophic information. The prominent characteristics of the GOWSNCS measure are that it not only is a generalization of the cosine similarity measure but also considers the associated weights for attributes and decision makers in the aggregation of the cosine similarity measures of SNSs to alleviate the influence of unduly large or small similarities in the process of information aggregation. Finally, an illustrative example of investment alternatives is provided to demonstrate the application and effectiveness of the developed approach.

scholarly journals A Multi-Criteria Group Decision-Making Method with Possibility Degree and Power Aggregation Operators of Single Trapezoidal Neutrosophic Numbers

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 590 ◽  
Author(s):  
Xiaohui Wu ◽  
Jie Qian ◽  
Juanjuan Peng ◽  
Changchun Xue
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Practical Problem ◽  
Group Decision ◽  
Information Aggregation ◽  
Aggregation Operators ◽  
Previous Approach ◽  
Complex Information ◽  
Evaluation Information

Single valued trapezoidal neutrosophic numbers (SVTNNs) are very useful tools for describing complex information, because of their advantage in describing the information completely, accurately and comprehensively for decision-making problems. In the paper, a method based on SVTNNs is proposed for dealing with multi-criteria group decision-making (MCGDM) problems. Firstly, the new operations SVTNNs are developed for avoiding evaluation information aggregation loss and distortion. Then the possibility degrees and comparison of SVTNNs are proposed from the probability viewpoint for ranking and comparing the single valued trapezoidal neutrosophic information reasonably and accurately. Based on the new operations and possibility degrees of SVTNNs, the single valued trapezoidal neutrosophic power average (SVTNPA) and single valued trapezoidal neutrosophic power geometric (SVTNPG) operators are proposed to aggregate the single valued trapezoidal neutrosophic information. Furthermore, based on the developed aggregation operators, a single valued trapezoidal neutrosophic MCGDM method is developed. Finally, the proposed method is applied to solve the practical problem of the most appropriate green supplier selection and the rank results compared with the previous approach demonstrate the proposed method's effectiveness.

scholarly journals Methods for Multiple-Attribute Group Decision Making with q-Rung Interval-Valued Orthopair Fuzzy Information and Their Applications to the Selection of Green Suppliers

Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 56 ◽  
Author(s):  
Jie Wang ◽  
Hui Gao ◽  
Guiwu Wei ◽  
Yu Wei
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Information Aggregation ◽  
Aggregation Operators ◽  
Uncertain Information ◽  
Multiple Attribute ◽  
Green Suppliers ◽  
Interval Valued ◽  
Selection Of

In the practical world, there commonly exist different types of multiple-attribute group decision making (MAGDM) problems with uncertain information. Symmetry among some attributes’ information that is already known and unknown, and symmetry between the pure attribute sets and fuzzy attribute membership sets, can be an effective way to solve this type of MAGDM problem. In this paper, we investigate four forms of information aggregation operators, including the Hamy mean (HM) operator, weighted HM (WHM) operator, dual HM (DHM) operator, and the dual-weighted HM (WDHM) operator with the q-rung interval-valued orthopair fuzzy numbers (q-RIVOFNs). Then, some extended aggregation operators, such as the q-rung interval-valued orthopair fuzzy Hamy mean (q-RIVOFHM) operator; q-rung interval-valued orthopairfuzzy weighted Hamy mean (q-RIVOFWHM) operator; q-rung interval-valued orthopair fuzzy dual Hamy mean (q-RIVOFDHM) operator; and q-rung interval-valued orthopair fuzzy weighted dual Hamy mean (q-RIVOFWDHM) operator are presented, and some of their precious properties are studied in detail. Finally, a real example for green supplier selection in green supply chain management is provided, to demonstrate the proposed approach and to verify its rationality and scientific nature.

scholarly journals Interval-Valued Hesitant Fuzzy Multiattribute Group Decision Making Based on Improved Hamacher Aggregation Operators and Continuous Entropy

2017 ◽  
Vol 2017 ◽  
pp. 1-20 ◽  
Author(s):  
Jun Liu ◽  
Ning Zhou ◽  
Li-Hua Zhuang ◽  
Ning Li ◽  
Fei-Fei Jin
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Information Aggregation ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Fuzzy Information ◽  
Ordered Weighted Averaging ◽  
Cowa Operator ◽  
Interval Valued

Under the interval-valued hesitant fuzzy information environment, we investigate a multiattribute group decision making (MAGDM) method with continuous entropy weights and improved Hamacher information aggregation operators. Firstly, we introduce the axiomatic definition of entropy for interval-valued hesitant fuzzy elements (IVHFEs) and construct a continuous entropy formula on the basis of the continuous ordered weighted averaging (COWA) operator. Then, based on the Hamachert-norm andt-conorm, the adjusted operational laws for IVHFEs are defined. In order to aggregate interval-valued hesitant fuzzy information, some new improved interval-valued hesitant fuzzy Hamacher aggregation operators are investigated, including the improved interval-valued hesitant fuzzy Hamacher ordered weighted averaging (I-IVHFHOWA) operator and the improved interval-valued hesitant fuzzy Hamacher ordered weighted geometric (I-IVHFHOWG) operator, the desirable properties of which are discussed. In addition, the relationship among these proposed operators is analyzed in detail. Applying the continuous entropy and the proposed operators, an approach to MAGDM is developed. Finally, a numerical example for emergency operating center (EOC) selection is provided, and comparative analyses with existing methods are performed to demonstrate that the proposed approach is both valid and practical to deal with group decision making problems.

scholarly journals An Extension of the MULTIMOORA Method for Multiple Criteria Group Decision Making Based upon Hesitant Fuzzy Sets

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Zhi-Hui Li
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Distance Measure ◽  
Group Decision ◽  
Multiple Criteria Decision Making ◽  
Score Function ◽  
Multiple Criteria ◽  
Hesitant Fuzzy Set ◽  
Multiple Objective Optimization ◽  
Multimoora Method

In order to determine the membership of an element to a set owing to ambiguity between a few different values, the hesitant fuzzy set (HFS) has been proposed and widely diffused to deal with vagueness and uncertainty involved in the process of multiple criteria group decision making (MCGDM) problems. In this paper, we develop novel definitions of score function and distance measure for HFSs. Some examples are given to illustrate that the proposed definitions are more reasonable than the traditional ones. Furthermore, our study extends the MULTIMOORA (Multiple Objective Optimization on the basis of Ratio Analysis plus Full Multiplicative Form) method with HFSs. The proposed method thus provides the means for multiple criteria decision making (MCDM) regarding uncertain assessments. Utilization of hesitant fuzzy power aggregation operators also enables facilitating the process of MCGDM. A numerical example of software selection demonstrates the possibilities of application of the proposed method.

A CONSENSUS MODEL FOR GROUP DECISION-MAKING PROBLEMS WITH INTERVAL FUZZY PREFERENCE RELATIONS

2012 ◽  
Vol 11 (04) ◽  
pp. 709-725 ◽  
Author(s):  
J. M. TAPIA GARCÍA ◽  
M. J. DEL MORAL ◽  
M. A. MARTÍNEZ ◽  
E. HERRERA-VIEDMA
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Selection Process ◽  
Preference Relation ◽  
Feedback Mechanism ◽  
Consensus Model ◽  
Preference Relations ◽  
Fuzzy Preference Relations ◽  
Fuzzy Preference

Interval fuzzy preference relations can be useful to express decision makers' preferences in group decision-making problems. Usually, we apply a selection process and a consensus process to solve a group decision situation. In this paper, we present a consensus model for group decision-making problems with interval fuzzy preference relations. This model is based on two consensus criteria, a consensus measure and a proximity measure, and also on the concept of coincidence among preferences. We compute both consensus criteria in the three representation levels of a preference relation and design an automatic feedback mechanism to guide experts in the consensus reaching process. We show an application example in social work.

scholarly journals Rough-Number-Based Multiple-Criteria Group Decision-Making Method by Combining the BWM and Prospect Theory

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Fan Jia ◽  
Xingyuan Wang
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Group Decision Making ◽  
Group Decision ◽  
Programming Model ◽  
Weighting Function ◽  
Information Aggregation ◽  
Criteria Weights ◽  
Multicriteria Group Decision Making ◽  
Novel Method

Multicriteria group decision-making (MCGDM) problems have been a research hotspot in recent years, and prospect theory is introduced to cope with the risk and imprecision in the process of decision-making. To guarantee the effectiveness of information aggregation and extend the feasibility of prospect theory, this paper proposes a novel decision-making approach based on rough numbers and prospect theory to solve risky and uncertain MCGDM problems. Firstly by combining rough numbers and the best-worst method (BWM), we construct a linear programming model to calculate rough criteria weights, which are defined by lower limitations and upper limitations. Then for the imprecision of value function and weighting function in prospect theory, we propose a novel method with the aid of combining rough numbers and prospect theory to handle the risk in decision-making problems. Finally, a numerical example involving investment is introduced to illustrate the application and validity of the proposed method.

Multi-Criteria Project Selection Using an Extended VIKOR Method with Interval Type-2 Fuzzy Sets

2015 ◽  
Vol 14 (05) ◽  
pp. 993-1016 ◽  
Author(s):  
Mehdi Keshavarz Ghorabaee ◽  
Maghsoud Amiri ◽  
Jamshid Salehi Sadaghiani ◽  
Edmundas Kazimieras Zavadskas
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Selection Process ◽  
Project Selection ◽  
Real Problem ◽  
Vikor Method ◽  
Criteria Weights ◽  
Interval Type

Project selection can be a real problem of the multi-criteria group decision making if a group of decision makers express their preferences depending on the nature of the alternatives and different criteria with respect to their knowledge about them. The purpose of the project selection process is to analyze project viability and to approve or reject project proposals based on established criteria. Such decisions are often complex, because they require the identification, consideration and analysis of many tangible and intangible factors. This paper presents a multi-criteria group decision-making approach for project selection problem in the type-2 fuzzy environment. The proposed method is an extended version of Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method with interval type-2 fuzzy numbers; it is called type-2 fuzzy VIKOR (T2F-VIKOR). A stepwise procedure is used for ranking and evaluating the alternatives in the developed method, and the best solution is selected considering both the beneficial and nonbeneficial criteria. An illustrative example is presented to show the applicability of the proposed approach in the project selection problems, and the results are analyzed. The results are compared with some existing methods to show the validity of the extended method. We also utilize six sets of criteria weights for analyzing the stability of the proposed method. These analyses show that the obtained results of the proposed method are relatively consistent with other methods and have good stability in different criteria weights.

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