An efficient solution to a multiple non-linear regression model with interaction effect using TORA and LINDO

Abstract

Goal programming (GP) has been proven a valuable mathematical programming form in a number of venues. GP model serves a valuable purpose of cross-checking answers from other methodologies. Different software packages are used to solve these GP models. Likewise, multiple regression models can also be used to more accurately combine multiple criteria measures that can be used in GP model parameters. Those parameters can include the relative weighting and the goal constraint parameters. A comparative study on the solutions using TORA, LINDO, and least square method has been made in this paper. The objective of this paper is to find out a method that gives most accurate result to a nonlinear multiple regression model.