A New Algorithm to Solve Fuzzy Sequential Non-Linear Programming Problem

Abstract

In this paper, an algorithm is proposed to solve a Fuzzy sequential non-linear programming problem. This algorithm applies to the problem when the objective function is non-linear and the constraints are linear. Initially, the Fuzzy sequential linear programming problem is converted into a fuzzy linear programming problem using the fuzzy Frank Wolfe algorithm and then it is solved by the Fourier Motzkin Elimination Method. In nonlinear programming problems, the Sequential quadratic programming (SQP) algorithm is seen as quite possibly the most effective method. Since the 1970s, numerous specialists in China and abroad have explored this kind of algorithm and made some allure results. Through their work, the SQP process has drawn in a basic situation in tackling controlled nonlinear streamlining problems. Notwithstanding, the SQP algorithm realistic so far has a horrid limitation, (i.e.) this sort of strategy necessitates that their quadratic programming sub-problems have limited solutions at every emphasis. Considering that the imperatives of the sub-problems are linear guesses of one of the extraordinary problems, attainable arrangements of such sub-problems might be unfilled. In this way, the surpassing case is difficult to be fulfilled.