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

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  • Yashpal Singh Raghav
  • Ahteshamul Haq
  • Irfan Ali

Abstract

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.

Suggested Citation

  • Yashpal Singh Raghav & Ahteshamul Haq & Irfan Ali, 2023. "Multiobjective intuitionistic fuzzy programming under pessimistic and optimistic applications in multivariate stratified sample allocation problems," PLOS ONE, Public Library of Science, vol. 18(4), pages 1-19, April.
    • Handle: RePEc:plo:pone00:0284784
    DOI: 10.1371/journal.pone.0284784
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    References listed on IDEAS

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    1. Rahul Varshney & M. Khan & Ummatul Fatima & M. Ahsan, 2015. "Integer compromise allocation in multivariate stratified surveys," Annals of Operations Research, Springer, vol. 226(1), pages 659-668, March.
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    Cited by:

    1. Qiwen Ye, 2024. "Extended DEMATEL method with intuitionistic fuzzy information: A case of electric vehicles," PLOS ONE, Public Library of Science, vol. 19(12), pages 1-23, December.

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