The α‐reliable mean‐excess regret model for stochastic facility location modeling

In this paper, we study a strategic facility location problem under uncertainty. The uncertainty associated with future events is modeled by defining alternative future scenarios with probabilities. We present a new model called the α‐reliable mean‐excess model that minimizes the expected regret with respect to an endogenously selected subset of worst‐case scenarios whose collective probability of occurrence is no more than 1 − α. Our mean‐excess risk measure is coherent and computationally efficient. Computational experiments also show that the α‐reliable mean‐excess criterion matches the α‐reliable minimax criterion closely.