Compromise optimum allocation in neutrosophic multi-character survey under stratified random sampling using neutrosophic fuzzy programming
Survey sampling has wide range of applications in social and scientific investigation to draw inference about the unknown parameter of interest. In complex surveys, the sample information about the study variable cannot be expressed by a precise number under uncertain environment due fuzziness and i...
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| Format: | Article |
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Elsevier
2024-04-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024043585 |
| _version_ | 1797242941020831744 |
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| author | Atta Ullah Javid Shabbir Abdullah Mohammed Alomair Fawaz Khaled Alarfaj |
| author_facet | Atta Ullah Javid Shabbir Abdullah Mohammed Alomair Fawaz Khaled Alarfaj |
| author_sort | Atta Ullah |
| collection | DOAJ |
| description | Survey sampling has wide range of applications in social and scientific investigation to draw inference about the unknown parameter of interest. In complex surveys, the sample information about the study variable cannot be expressed by a precise number under uncertain environment due fuzziness and indeterminacy. Therefore, this information is expressed by neutrosophic numbers rather than the classical numbers. The neutrosophic statistics, which is generalization of classical statistics, deals with the neutrosophic data that has some degree of indeterminacy and fuzziness. In this study, we investigate the compromise optimum allocation problem for estimating the population means of the neutrosophic study variables in a multi-character stratified random sampling under uncertain per unit measurement cost. We proposed the intuitionistic fuzzy cost function, modeling the fuzzy uncertainty in stratum per unit measurement cost. The compromise optimum allocation problem is formulated as a multi-objective intuitionistic fuzzy optimization problem. The solution methodology is suggested using neutrosophic fuzzy programming and intuitionistic fuzzy programming approaches. A numerical study includes the means estimation of atmospheric variables is presented to explore the real-life application, explain the mathematical formulation, and efficiency comparison with some existing methods. The results show that the suggested methods produce more precise estimates with less utilization of survey resources as compared to some existing methods. The Python is used for statistical analysis, graphical designing and numerical optimization problems are solved using GAMS. |
| first_indexed | 2024-04-24T18:47:13Z |
| format | Article |
| id | doaj.art-35c8a65c774d4f3698f00c50223b2434 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-24T18:47:13Z |
| publishDate | 2024-04-01 |
| publisher | Elsevier |
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| series | Heliyon |
| spelling | doaj.art-35c8a65c774d4f3698f00c50223b24342024-03-27T04:52:34ZengElsevierHeliyon2405-84402024-04-01107e28327Compromise optimum allocation in neutrosophic multi-character survey under stratified random sampling using neutrosophic fuzzy programmingAtta Ullah0Javid Shabbir1Abdullah Mohammed Alomair2Fawaz Khaled Alarfaj3Department of Statistics, Quaid-i-Azam University, Islamabad 45320, Pakistan; Department of Mathematics, COMSATS University Islamabad, Attock Campus 43600, Pakistan; Corresponding authors.Department of Statistics, Quaid-i-Azam University, Islamabad 45320, Pakistan; Department of Statistics, University of Wah, Wah Cant 47040, PakistanDepartment of Quantitative Methods, School of Business, King Faisal University, Al-Ahsa 31982, Saudi Arabia; Corresponding authors.Department of Management Information Systems (MIS), School of Business, King Faisal University, Al-Ahsa 31982, Saudi ArabiaSurvey sampling has wide range of applications in social and scientific investigation to draw inference about the unknown parameter of interest. In complex surveys, the sample information about the study variable cannot be expressed by a precise number under uncertain environment due fuzziness and indeterminacy. Therefore, this information is expressed by neutrosophic numbers rather than the classical numbers. The neutrosophic statistics, which is generalization of classical statistics, deals with the neutrosophic data that has some degree of indeterminacy and fuzziness. In this study, we investigate the compromise optimum allocation problem for estimating the population means of the neutrosophic study variables in a multi-character stratified random sampling under uncertain per unit measurement cost. We proposed the intuitionistic fuzzy cost function, modeling the fuzzy uncertainty in stratum per unit measurement cost. The compromise optimum allocation problem is formulated as a multi-objective intuitionistic fuzzy optimization problem. The solution methodology is suggested using neutrosophic fuzzy programming and intuitionistic fuzzy programming approaches. A numerical study includes the means estimation of atmospheric variables is presented to explore the real-life application, explain the mathematical formulation, and efficiency comparison with some existing methods. The results show that the suggested methods produce more precise estimates with less utilization of survey resources as compared to some existing methods. The Python is used for statistical analysis, graphical designing and numerical optimization problems are solved using GAMS.http://www.sciencedirect.com/science/article/pii/S2405844024043585Neutrosophic statisticsStratified samplingCost functionOptimum allocationIntuitionistic fuzzy programmingNeutrosophic fuzzy programming |
| spellingShingle | Atta Ullah Javid Shabbir Abdullah Mohammed Alomair Fawaz Khaled Alarfaj Compromise optimum allocation in neutrosophic multi-character survey under stratified random sampling using neutrosophic fuzzy programming Heliyon Neutrosophic statistics Stratified sampling Cost function Optimum allocation Intuitionistic fuzzy programming Neutrosophic fuzzy programming |
| title | Compromise optimum allocation in neutrosophic multi-character survey under stratified random sampling using neutrosophic fuzzy programming |
| title_full | Compromise optimum allocation in neutrosophic multi-character survey under stratified random sampling using neutrosophic fuzzy programming |
| title_fullStr | Compromise optimum allocation in neutrosophic multi-character survey under stratified random sampling using neutrosophic fuzzy programming |
| title_full_unstemmed | Compromise optimum allocation in neutrosophic multi-character survey under stratified random sampling using neutrosophic fuzzy programming |
| title_short | Compromise optimum allocation in neutrosophic multi-character survey under stratified random sampling using neutrosophic fuzzy programming |
| title_sort | compromise optimum allocation in neutrosophic multi character survey under stratified random sampling using neutrosophic fuzzy programming |
| topic | Neutrosophic statistics Stratified sampling Cost function Optimum allocation Intuitionistic fuzzy programming Neutrosophic fuzzy programming |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024043585 |
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