The problem of constructing surgery schedules, with limited downstream ward capacity, is formulated as a mathematical model with probabilistic constraints. This exact model becomes computationally intractable for mathematical programming solvers as the number of patients increase. An evolutionary algorithm is used to restrict the size of the search space, making the problem tractable again, effectively guiding the solvers towards an exact and feasible solution. Solutions are validated using Monte Carlo simulations during the evolutionary search. The optimization problem is inspired by real challenges faced by many hospitals today and tested on real-life hospital data.