Mitigating overtime risk in tactical surgical scheduling

•We formulate a stochastic programming model for a tactical surgery scheduling problem.•Our decision criterion is able to mitigate both the probability of overtime and its magnitude.•We show the computational complexities of several models for the problem.•We develop an efficient hill-climbing algorithm to solve our model.•We use real data simulation to illustrate the effectiveness of our approach against existing ones.