Interactive Fuzzy Goal Programming approach in multi-response stratified sample surveys

Authors

  • Neha Gupta Aligarh Muslim University, Department of Statistics & Operations Research, Aligarh, India
  • Irfan Ali Aligarh Muslim University, Department of Statistics & Operations Research, Aligarh, India
  • Abdul Bari Aligarh Muslim University, Department of Statistics & Operations Research, Aligarh, India

DOI:

https://doi.org/10.2298/YJOR141021005G

Keywords:

compromise allocation, coefficient of variation, Interactive Fuzzy Goal Programming, optimum allocation

Abstract

In this paper, we applied an Interactive Fuzzy Goal Programming (IFGP) approach with linear, exponential and hyperbolic membership functions, which focuses on maximizing the minimum membership values to determine the preferred compromise solution for the multi-response stratified surveys problem, formulated as a Multi- Objective Non Linear Programming Problem (MONLPP), and by linearizing the nonlinear objective functions at their individual optimum solution, the problem is approximated to an Integer Linear Programming Problem (ILPP). A numerical example based on real data is given, and comparison with some existing allocations viz. Cochran’s compromise allocation, Chatterjee’s compromise allocation and Khowaja’s compromise allocation is made to demonstrate the utility of the approach.

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Published

2016-05-01

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Research Articles