Multiobjective intuitionistic fuzzy programming under pessimistic and optimistic applications in multivariate stratified sample allocation problems
This study investigates the compromise allocation of multivariate stratified sampling with complete response and nonresponse. We have formulated a multivariate stratified sampling problem as a mathematical programming problem to estimate p-population means with complete response and nonresponse for...
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Published in | PloS one Vol. 18; no. 4; p. e0284784 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
United States
Public Library of Science
21.04.2023
Public Library of Science (PLoS) |
Subjects | |
Online Access | Get full text |
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Summary: | This study investigates the compromise allocation of multivariate stratified sampling with complete response and nonresponse. We have formulated a multivariate stratified sampling problem as a mathematical programming problem to estimate p-population means with complete response and nonresponse for a fixed cost. Then, the compromise allocations for sample designs are determined by implementing intuitionistic fuzzy programming using optimistic and pessimistic solution strategies. A simulation study is carried out using the Stratify R software program to demonstrate the complete solution process. In wildlife, agricultural and marketing-related surveys, the study could be helpful. Also, the national planning policies related to surveys in such cases this study could be helpful. This study is an attempt to solve the sampling optimization problem using the Lingo-18 optimization program. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Current address: Department of Mathematics & Statistics, Integral University, Lucknow, India Competing Interests: The authors have declared that no competing interests exist. |
ISSN: | 1932-6203 1932-6203 |
DOI: | 10.1371/journal.pone.0284784 |