Uncertainty analysis involves assessing uncertainty in input parameters, models, and simulations to provide a range of possible outcomes or predictions along with their associated probabilities or confidence intervals. This allows decision-makers to make informed choices, considering the inherent uncertainties, and to better manage risks. Uncertainty analysis is indeed a valuable technique with numerous applications in various fields, but effective communication of optimization under uncertainty results is essential to influence decision-making. Here visualization plays a crucial role in communicating uncertainty in a clear and understandable manner. The current landscape of research in the field of visualization, particularly concerning uncertainty quantification and constraint interaction in optimization problem, reveals a notable gap in present tools designed for visualizing the design space. This gap signifies a critical need for advancements in visualization techniques that can accurately represent complex, multidimensional feasible design spaces while incorporating and visualizing uncertainties associated with various parameters and around constraint boundaries. In this work, the authors tried to bridge this gap in visualization tools, by proposing a novel way of visualizing uncertainty in design space and near constraint boundaries in high-dimensional design space, which is essential for advancing research and practical applications involving uncertainty quantification and optimization.