Abstract
Linear programming is the optimization of a linear function under constraints of linear equations or inequalities. Since much of the information in the real world is unknown, linear programming does not produce acceptable results due to the need for accurate information and data in many real-world decisions. The grey system is one of the most efficient approaches to dealing with uncertainty and incomplete data. Accordingly, the present study is an attempt to propose a novel method for solving grey linear programming problems. The linear programming with grey information methods presented to date have drawbacks, such as the weakness of solving linear programming with grey information in constraints, inappropriate lower bound results than high bound, a high volume of operations, and high complexity. To address these drawbacks, the present study proposes a novel method of linear programming with grey parameters. As opposed to the other existing methods, which include several steps, the proposed method in this study is much smaller and has only five simple steps. It is easy to work and applicable to any grey linear programming problem.
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More From: International Journal of Applied and Computational Mathematics
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