The linear optimization methodology is applied to address the issue related to managing trade-offs between project duration and associated costs. While numerous models have been created for solving such problems, a limitation noted is that the majority of models are inclined towards scenarios where projects are restricted by a pre-defined deadline. However, this approach considers both the timeline for completing a particular project and its associated expenses in monetary terms. In this study, it is considered both time uncertainty and financing variability during the scheduling process, considering both the individual and combined effects. The chance-constrained programming (CCP) is utilized to estimate the coefficient of variation for financing feasibility at a desired confidence level and time uncertainty in models is factored in using probabilistic scheduling methods like PERT. This uncertainty can be evaluated by calculating CV at a specified confidence interval. An objective function and a set of constraints is an effective way to minimize direct costs. Excel Solver provides a powerful tool to help with this task. Four different scenarios are adopted to understand the impact of time uncertainty and financing feasibility.