(untitled) (Journal of Advances and Scholarly Researches in Allied Education, 2021)
Nonlinear problems like this one can have a lot of different types of goals, but they all have onething in common the goal is to get the rate of two quadratic objective functions, which are both subject tolinear constraints, to be as high as possible. When a lot of rates have to be done at the same time for theoptimization, there are problems. Among these are financial and corporate planning, planning for ahospital and health care plan as well as for production. In the literature, quadratic fractional optimizationhas been getting a lot of attention. It is the most important problem in both optimization theory andpractise. There were a lot of different results on quadratic fractional optimization. Ranking function isused to make the nonlinear problem into a crisp one, and then fuzzy programming is used to solve thecrisp problem. 2014 was the year that Lachhwani looked into a multi-objective quadratic fuzzyoptimization problem. This is a way to make sure that you’re getting the best out of a lot of di fferent goalfunctions, in the form of a numerator and denominator function. Abdulrahim (2013) looked into how tosolve a quadratic fuzzy optimization problem through feasible direction development and a modifiedsimplex method. Sen (2013) came up with a piecewise linear approximation method that could help solvea Fuzzy separable quadratic optimization problem.