fuzzy approximating functions and its application in solving fuzzy multi-choice linear programming models

This article considers a particular type of fuzzy multi-choice linear programming (fmclp) model in which there are several choices for the fuzzy parameters on the right-hand side (rhs) of problem constraints. we first construct the fuzzy polynomials to solve this model using the fuzzy multi-choice parameters on the rhs of constraints. we construct the fuzzy polynomials by approximating fuzzy functions, including the binary variable approach, lagrange, and newton's interpolating polynomials. also, we use the least squares approach to construct the approximating fuzzy polynomial. then we solve the resulting model. finally, we will examine the above techniques in numerical examples.