Stochastic optimization models for ground delay program planning with equity–efficiency tradeoffs

Bad weather is a major contributor to air traffic delays. The ration-by-distance algorithm was proposed to increase the efficiency of ground delay program (GDP) planning in situations where there is uncertainty regarding the duration of the weather conditions that motivated the GDP. This algorithm, however, can treat shorter flights unfairly. We describe a two-stage stochastic, multi-objective integer program for GDP planning. This multi-objective approach allows one to balance equity and efficiency. We provide experimental evidence showing the effectiveness of the solutions generated.

► This paper addresses objectives in assigning slots under a ground delay program. ► The Ration-by-Distance algorithm maximizes efficiency by prioritizing longer flights. ► The first-scheduled-first-served principle is accepted as equitable. ► We model this problem as a linear program optimizing both equity and efficiency. ► We show that this model is able to achieve results which outperform previous work.