Current technologies have made the transition from surface to underground mining methods for mineral extraction feasible and economically viable. Determining the point of transition from one method to the other for deposits that require exploitation with both methods is challenging. The existing research integrates production scheduling optimization with determining the transition depth that maximizes net present value (NPV), making the problem computationally intractable. However, these studies do not consider some realistic operational constraints in the problem setting. Our paper aims to develop an integrated mixed-integer linear programming (MILP) model to investigate the extent to which operational constraints and parameters of transition mines affect the optimal production schedule and NPV of an operation. We developed a computational experiment that evaluates development cost and rate, fleet size, stockpile, production footprint, dilution factor, and crown pillar placement on the model output. A case study is used to validate the model, with a comparative sensitivity analysis to obtain operational insights. The sensitivity of the NPV and computational time to each experimental factor varied significantly. There was no significant difference in NPV (0.15%) when the development cost was incorporated. However, for the fleet size, stockpile, and production footprint, an increase of 4.8%, 10.5 %, and 4.8% in the NPV was observed. We conclude that the extent to which operational parameters and constraints of transition mines are accounted for, has a significant impact on the optimal production schedule and NPV obtained.