Abstarct: From the distant past, information and decision-making on most real world problems have not been completely certain. All the sciences, and in particular, the science of mathematical linear programming have not been excluded from this because we have a lot of data and information. Therefore, it is not appropriate to use definitive methods and solutions to work on such problems that have uncertain parameters. For this reason, various researchers and scientists have come to develop systems and methods to deal with this uncertainty. The theory of grey systems was introduced by Deng in 1982 Most of the real world processes in decision-making problems due to lack of information and uncertainty are in the grey environment. Grey optimization provides useful tools for decision -making under such uncertainty. Gray planning is capable of dealing with weak, incomplete, or uncertain problems associated with systems and extensively many areas such as economics, agriculture, medicine, geography, industry and so on have been used. In this thesis, we try to reduce the uncertainties of the linear program problem by combining linear programming and grey systems theory and seeking to optimize the solution.