Towards solving linear programming with uncertainty using neutrosophic parameters

The optimal objective value of a linear programming problem (lp-problem) may be affected significantly, when a number of relevant parameters are additionally acted upon the corresponding system. So, to have a fair outcome, this study develops a structure of lp-problem and its solution approach in a distinct style with the effect of all possible parameters and the provided constraints. Each parameter admits one objective function and thus the lp-problem turns into a multi-objective problem. The coefficients of all objective functions are set as a variable quantity instead of conventional way to address a specific problem in several atmosphere. Also taking into account the nature of today’s uncertain scenario, parameters are designed by three types of single valued triangular neutrosophic numbers to cultivate the indeterminacy and inconsistency more precisely in a decision making. The solution approach merges component wise optimization technique and Zimmermann’s principle. The optimality test has been done theoretically. A real life example of a manufacturing industry is considered to verify the efficiency of the proposed method.