We view Multicriteria Decision Making (MCDM) as the conjunction of three components: search, preference tradeoffs, and interactive visualization. The first MCDM component is the search process over the space of possible solutions to identify the non-dominated solutions that compose the Pareto set. The second component is the preference tradeoff process to select a single solution (or a small subset of solutions) from the Pareto set. The third component is the interactive visualization process to embed the decisionmaker in the solution refinement and selection loop. We focus on the intersection of these three components and we highlight some research challenges, representing gaps in the intersection. We introduce a requirement framework to compare most MCDM problems, their solutions, and analyze their performances. We focus on two research challenges and illustrate them with three case studies in electric power management, financial portfolio rebalancing, and air traffic planning.

Next Generation air traffic management needs a collaborative traffic flow planning system to better meet stakeholder objectives and make air travel more efficient and convenient. As a step toward fulfilling this need, a Lockheed Martin research team has prototyped NextGen traffic flow planning services. The flow planning services supports Federal Aviation Administration (FAA) objective of collaborative air traffic management (CATM), which specifies strategic interactions to mitigate situations when the system cannot accommodate the desired use of capacity. CATM solutions include programs and collaborations on procedures that will establish balance by shifting demand to alternate resources (e.g. routing solutions). The service provides an integrated traffic flow management solution as it combines rerouting solutions along with time based strategies. The emphasis is on better automation capabilities that support sounder and faster decisions. In this paper we present a brief description of the flow services, a set of decision support algorithms designed to support collaborative air traffic planning, and results from a study designed to assess the potential of this approach.

In view of current projections that the demand for air transport will double if not triple in the next 20 years, and recognizing that the current systems both in Europe and the USA are already pushing the limits of available capacity, we recognize an urgent need to review ATM operations in the near to mid term future. The Federal Aviation Administration in its Operational Evolution Partnership (OEP) stresses the need for collaborative flow planning based on a philosophy to support users own operating preferences with restriction imposed only when a real operational need exists to meet the foreseen demand. One of the key objectives of the Next Generation Air Transportation System (NextGen) is to try to ensure that flight operator objectives are best balanced against the National Airspace System (NAS) performance. To support a user-oriented flow planning capability it is imperative to incorporate technological and innovative planning solutions that increase the available capacity to meet future demand, whilst maintaining and improving safety, enhancing efficiency and offering flexibility to the airline operators. Moreover, all of this should be achieved to ensure the equitable consideration of multiple stakeholder needs in this complex dynamic system. This paper presents our research into the design of a scalable enterprise framework for multiple-stakeholder and multiple-objective model-based planning and optimization in support of future Air Traffic Flow Management. The approach is based on an intelligent evaluation and optimization at the strategic and flight route levels. Our approach not only considers system-level objectives, but also regards the impact of decisions on the principal stakeholders within the US National Airspace System and proposes a novel approach to concerns about equitable solutions.

The U.S. national Air Traffic Management (ATM) system is today operating at the edge of its capabilities, handling the real-time planning and coordination of over 50,000 flights per day. This situation will only worsen in the years to come, as it is expected that U.S. air traffic will nearly double by the year 2025. There is a pressing need therefore for increasing capacity to meet future demand, improving safety, enhancing efficiency, providing additional flexibility to airline operators, and equitable consideration of multiple stakeholder needs in this complex dynamic system. In this paper, we present a scalable enterprise framework for multi-stakeholder, multi-objective model-based planning and optimization of air traffic in the national airspace system (NAS). The approach is based on an intelligent evaluation and optimization at the strategic and flight route levels. At the strategic level, we focus on separations between flights to improve airspace system performance. At the flight route level, we focus on identifying an optimal portfolio of flight paths within a planning horizon that trades-off a reduction in miles flown and a reduction in congestion. This framework not only considers system-level objectives, but also regards the impact of decisions on the principal stakeholders within the NAS. It is expected that this system will serve as a key decision-support tool to address future NAS scalability and reliability needs.