Geodesic
Interactive Fuzzy Goal Programming Approach in Multi-Response Stratified Sample Surveys
Yugoslav journal of operations research, Tome 26 (2016) no. 2, p. 243 .

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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.
Classification : 62D05
Keywords: Compromise Allocation, Coefficient of Variation, Interactive Fuzzy Goal Programming, Optimum Allocation. 
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     author = {Neha Gupta and Irfan Ali and Abdul Bari},
     title = {Interactive {Fuzzy} {Goal} {Programming} {Approach} in {Multi-Response} {Stratified} {Sample} {Surveys}},
     journal = {Yugoslav journal of operations research},
     pages = {243 },
     publisher = {mathdoc},
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     number = {2},
     year = {2016},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/YJOR_2016_26_2_a6/}
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Neha Gupta; Irfan Ali; Abdul Bari. Interactive Fuzzy Goal Programming Approach in Multi-Response Stratified Sample Surveys. Yugoslav journal of operations research, Tome 26 (2016) no. 2, p. 243 . http://geodesic.mathdoc.fr/item/YJOR_2016_26_2_a6/