Symmetric matrices properties to duality in linear programming problem

Duality is one of the most important topics in optimization either a theoretical and algorithmic perspective. Optimization problem usually involved mathematical model. One of the applications widely used is Linear Programming. Linear functions applications are frequently used in production planning, networks, scheduling, and other application of a linear function subject to linear constraints. Extensive number of papers related with duality in optimization has been published. However, studies about the effect of different characteristics of randomly symmetric matrices in the duality in linear programming have not yet been discussed widely. This study addresses new findings which may contribute to advancement of LP theory and practice, particularly on the effects of various number of variables and different characteristics of matrices in LP problems to duality.