Uncertainty is present in most production processes. Estimating demand, managing resources and preparing to face the risks inherent to market fluctuations is essential for the company's permanence in the current competitive scenario. In recent years, the scientific community has shown interest in aspects related to the prediction of the behavior of stochastic parameters in optimization systems. Thus, in order to understand the importance that researchers and journals give to the subject and which areas of greatest application, the Systematic Literature Review was chosen as the research method. From this, as a general objective of the research, we sought to understand how Monte Carlo Simulation (SMC), incorporated into Linear Programming (PL), can contribute to the perception and incorporation of variability in production processes. 113 articles were identified, published between 2015 and 2019, which were analyzed in order to estimate in which problems these tools are most used. It was also identified how the phenomena produced by randomness are understood and which tools can be incorporated into the optimization process for a more comprehensive understanding. Finally, the analysis of the selected articles revealed that the areas that most use SMC incorporated into PL are related to research on renewable energy and sustainability.