An Optimization Algorithm to Solve Imprecisely Defined Unconstrainted Optimization Problem

Many optimal solution driven engineering problems are operated through various parameters which are uncertain in nature. Therefore, for better understanding of the system and estimation of the field variables, the problem can be considered with epistemic type of uncertainties. Here, Trapezoidal Fuzzy Number is considered to visualize the epistemic constants and coefficients. A parametric concept is adopted here to model the governing imprecise algebraic equations to a fuzzy unconstrainted optimization problem. Then a search algorithm is implemented to handle the fuzzy unconstrained minimization problem. Moreover, to quantify the uncertainty, the algorithm with fuzzy theory is discussed in various cases. The different cases are discussed in details through couple of test electrical network problems. Finally, a comparative study of the present approach with others is presented.