Multiobjective intuitionistic fuzzy programming under pessimistic and optimistic applications in multivariate stratified sample allocation problems

• Published in: PloS one Vol. 18; no. 4; p. e0284784
• Main Authors: Raghav, Yashpal Singh, Haq, Ahteshamul, Ali, Irfan
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 21.04.2023; Public Library of Science (PLoS)
• Subjects: Allocations; Approximation; Biology and Life Sciences; Computer and Information Sciences; Computer Simulation; Dynamic programming; Engineering and Technology; Evaluation; Fuzzy Logic; Investment analysis; Lagrange multiplier; Linear programming; Mathematical programming; Multivariate analysis; National planning; Optimization; Optimization techniques; Physical Sciences; Research and Analysis Methods; Sample size; Sample variance; Sampling; Social Sciences; Software; Statistics; Surveys; Wildlife surveys; India
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0284784

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.