In this paper, the concept of fuzzy Non-Linear Programming Technique is
applied to solve an economic order quantity (EOQ) model for restricted
budget and space. Since various types of uncertainties and imprecision are
inherent in real inventory problems, they are classically modeled using the
approaches from the probability theory. However, there are uncertainties
that cannot be appropriately treated by the usual probabilistic models. The
questions are how to define inventory optimization tasks in such environment
and how to interpret the optimal solutions. This paper allow the
modification of the Single item EOQ model in presence of fuzzy decision
making process where demand is related to the unit price, and the setup cost
varies with the quantity produced/Purchased. The modification of objective
function, budget, and storage area in the presence of imprecisely estimated
parameters are considered. The model is developed by employing different
approaches over an infinite planning horizon. It incorporates all the
concepts of a fuzzy arithmetic approach and comparative analysis with other
non linear models. Investigation of the properties of an optimal solution
allows developing an algorithm whose validity is illustrated by an example
problem, and two and three dimensional diagrams are represented to this
application through MATL(R2009a) software. Sensitivity analysis of the
optimal solution is studied with respect to the changes of different
parameter values for obtaining managerial insights of the decision problem.
Security Constrained Unit Commitment in a Power System based on Benders Decomposition and Mixed Integer Non-linear Programming