Abstract: Since facility location decisions are frequently long-term ones in nature, there may be considerable uncertainty regarding the way in which relevant parameters in the location decision will change over time. The uncertainties of flows in flow interception are handled by a set of scenarios. Stochastic A-robust interception location model is proposed, with combination of stochastic optimization and robust optimization. This model has constraints with the relevant regret value smaller than Ain each scenario, which are called A-robust constraints, the objective is to maximize the expected interception flows.This paper formulates this model as a 0-1 linear integer programming, and proposes the improved greedy algorithm and Lagrangian heuristics.Finally, these heuristic algorithms are applied in different scales of computational examples.

Key words: location, flow interception problem, stochastic, robust