Enhanced Stochastic Optimization Model (ESOM) for Setting Flow Rates in Collaborative Trajectory Options Programs (CTOP)

We present a stochastic optimization model for setting flow rates during a new type of traffic management initiative known as a Collaborative Trajectory Options Program (CTOP). CTOP allows traffic managers to restrict traffic flow through a network of flow constrained areas (FCAs). FCAs can be lines or polygonal regions of airspace that traffic managers may have tailored to the traffic flow situation at hand. As of yet, there is no guidance for traffic managers to set the maximum flow rates (flights per unit time period) at each of the FCAs. This is compounded by the stochasticity of the problem: the FCA capacities are usually a function of weather, which is not known in advance. Traffic demand levels at the FCAs are also stochastic, since they depend on the routing and delay tradeoff preferences that airlines submit during the CTOP process. The optimization model we present provides to the traffic managers time-varying flow rates at the FCAs that minimize total expected delay costs, taking into account forecasted traffic demand, airline routing preferences, and forecasted probabilistic weather. Because the model is aggregate, it allows the resource allocation algorithm in CTOP to make final flight-to-route and flight delay assignments. In this respect, the model is highly consistent with CTOP functionality and the collaborative decision making (CDM) paradigm in traffic flow management. In this paper, we explore important characteristics of the model, such as hedging across a range of possible weather outcomes and convergence with airline routing preferences. We demonstrate its use on a realistic air traffic scenario.