An intuitionistic dense fuzzy AHP-TOPSIS method for military robot selection

Swethaa, S.; Felix, A.

doi:10.3233/jifs-223622

Cited by 8 publications

(2 citation statements)

References 27 publications

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“…Among the decision making models, MCDM is one of the most widely used decision methodologies involving both quantitative and qualitative factors in which the ranking of the alternatives are found in relation with various criteria. This technique includes several well-known methods like TOPSIS, 5 VIKOR, 6 AHP, 7,8 COPRAS, 9 Entropy, 10 WASPAS, 11 DEMATEL, [12][13][14] MAUT, 15 etc. Thus, MCDM methods were used in the fuzzy field to select the appropriate robot for a particular application.…”

Section: Introductionmentioning

confidence: 99%

An integrated intuitionistic dense fuzzy Entropy-COPRAS-WASPAS approach for manufacturing robot selection

Sampathkumar

Felix

Kaabar

et al. 2023

Advances in Mechanical Engineering

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Manufacturing robots are used for industrial purposes. Robots used for manufacturing purpose have the power to create products from raw materials and are capable of operating endlessly even in lights-out situations for continuous production. Manufacturing robots can be used in applications like arc welding, spot welding, materials handling, machine tending, painting, machine cutting and so on. Selecting a robot for a given application is complex. However, robot selection is used in selecting a suitable robot for the preferred output with specific application ability. In recent years, many authors used multi-criteria decision-making methods to select a robot that meets the need. This study presents a hybrid model by integrating complex proportional assessment (COPRAS) with the weighted aggregates sum product assessment (WASPAS) methods in intuitionistic dense fuzzy set to select a manufacturing robot for a particular application. Intuitionistic dense fuzzy entropy is used in calculating the weights for the criteria and intuitionistic dense fuzzy COPRAS and WASPAS are used in ranking the best alternatives where in the optimum types of robots are obtained. Here, intuitionistic dense fuzzy sets are used as it is capable of dealing with the intangible factors while selecting a robot. On the basis of the manufacturing robot selection, two comparisons are given. First, the results are compared with various [Formula: see text] values between 0 and 1 and second the results are compared with the fuzzy set, intuitionistic fuzzy set and the dense fuzzy set to show the effectiveness of the proposed methodology with the intuitionistic dense fuzzy set.

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Section: Introductionmentioning

confidence: 99%

An integrated intuitionistic dense fuzzy Entropy-COPRAS-WASPAS approach for manufacturing robot selection

Sampathkumar

Felix

Kaabar

et al. 2023

Advances in Mechanical Engineering

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“…Addressing such complex problems, particularly from multiple perspectives, calls for the application of MCDM methods. These methods, adept at handling inaccuracies and uncertainties in decision-making, have found applications across various sectors [3][4][5][6][7][8][9][10][11][12][13], including the military [14][15][16][17][18][19][20][21][22][23]. A review of existing literature reveals diverse approaches to COA selection using MCDM methods.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Military Decision-Making: Application of the FUCOM– EWAA–COPRAS-G MCDM Model

Tešić,

Božanić

2023

ATAMS

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In contemporary military contexts, the determination of an optimal course of action (COA) in combat operations emerges as a critical challenge. This study delineates a decision support methodology for military applications, employing sophisticated decision analysis techniques. The initial phase entails the identification of pivotal criteria for assessing and ranking COAs, followed by the assignment of weight coefficients to each criterion via the full consistency method (FUCOM). Subsequently, the Einstein weighted arithmetic average operator (EWAA) was utilized for the aggregation of expert opinions, ensuring a consensual evaluation of these criteria and culminating in the final values of their weight coefficients. The ensuing phase focuses on the selection of an optimal COA, incorporating the grey complex proportional assessment (COPRAS-G) method. This method addresses uncertainties and varying criterion values. Expert ratings were again aggregated using the EWAA operator. The findings from this phase are designed to provide military commanders with precise, data-driven guidance for decision-making. To validate and verify the stability of the proposed model, a series of tests were conducted, including a rank reversal test, sensitivity analysis regarding changes in weight coefficients, and a comparative analysis with alternative methods. These assessments uniformly indicated the model's consistency, stability, and validity as a military decision support tool. Emphasizing a high degree of confidence in COA selection, the methodology advocated herein is applicable to decision-making processes in the planning and execution of military operations. The uniform application of professional terms, consistent with the broader context of this research, ensures clarity and coherence in its presentation. The approach outlined in this study stands as a testament to rigorous analytical methodologies in the realm of military strategic planning, offering a robust framework for decision-making under conditions of uncertainty and complexity.

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Centroid and Graded Mean Ranking Methods for Intuitionistic Trapezoidal Dense Fuzzy Set to Solve MCDM Problems of Robot Selection

Sampathkumar,

Augustin,

Narayanamoorthy

et al. 2024

Int. J. Fuzzy Syst.

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An intuitionistic dense fuzzy AHP-TOPSIS method for military robot selection

Cited by 8 publications

References 27 publications

An integrated intuitionistic dense fuzzy Entropy-COPRAS-WASPAS approach for manufacturing robot selection

An integrated intuitionistic dense fuzzy Entropy-COPRAS-WASPAS approach for manufacturing robot selection

Optimizing Military Decision-Making: Application of the FUCOM– EWAA–COPRAS-G MCDM Model

Centroid and Graded Mean Ranking Methods for Intuitionistic Trapezoidal Dense Fuzzy Set to Solve MCDM Problems of Robot Selection

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