A nonlinear separable quadratic objective function with linear constraints: a least squares approach to optimisation problems

Abstract

A least square technique of tackling optimization problems with nonlinear separable quadratic objective functions with linear constraints was developed by the study. Two problem sets were computed to confirm the efficiency of the developed approach. To confirm the authenticity of the solution, the Wolfram Mathematica programming software was employed to solve the examples illustrated in this study and the results obtained were in agreement as achieved using the least squares method. It was concluded that the algorithms of solving optimization problems with nonlinear separable quadratic objective function with linear constraints stated in this study were quite explicit, efficient and very easy to employ