A Goal Programming Approach to Solve Multi-objective Chance Constrained Programming in Fuzzy Environment

Authors

DOI:

https://doi.org/10.26713/cma.v14i1.2040

Keywords:

Multi objective fuzzy chance constrained nonlinear programming problem, MOFCCNLPP, Trapezoidal fuzzy numbers, Rayleigh distribution, Goal programming

Abstract

A new solution process is presented to solve multi-objective fuzzy chance constrained nonlinear decision making problems using goal programming techniques. The right sided parameters of probabilistic constraints are assumed to follow Rayleigh distribution with known parameters whereas the constraints coefficients are trapezoidal fuzzy numbers. The stochastic constraints are transformed into fuzzy constraints using CCP technique and \(\alpha\)-cut techniques are applied to obtain the identical crisp nonlinear programming problem. The crisp MONLPP is solved by goal programming by means of membership and non-membership functions. The proposed solution methodology is validated by an example.

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References

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Published

09-05-2023
CITATION

How to Cite

Beaula, T., & Seetha, R. (2023). A Goal Programming Approach to Solve Multi-objective Chance Constrained Programming in Fuzzy Environment. Communications in Mathematics and Applications, 14(1), 203–213. https://doi.org/10.26713/cma.v14i1.2040

Issue

Vol. 14 No. 1 (2023)

Section

Research Article

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