MODELS AND SOLUTION ALGORITHMS FOR EQUITABLE RESOURCE ALLOCATION IN AIR TRAFFIC FLOW MANAGEMENT

Population growth and economic development lead to increasing demand for travel and pose mobility challenges on capacity-limited air traffic networks. The U.S. National Airspace System (NAS) has been operated near the capacity, and air traffic congestion is expected to remain as a top concern for the related system operators, passengers and airlines. This dissertation develops a number of model reformulations and efficient solution algorithms to address resource allocation problems in air traffic flow management, while explicitly accounting for equitable objectives in order to encourage further collaborations by different stakeholders. This dissertation first develops a bi-criteria optimization model to offload excess demand from different competing airlines in the congested airspace when the predicted traffic demand is higher than available capacity. Computationally efficient network flow models with side constraints are developed and extensively tested using datasets obtained from the Enhanced Traffic Management System (ETMS) database (now known as the Traffic Flow Management System). Representative Pareto-optimal tradeoff frontiers are consequently generated to allow decision-makers to identify best-compromising solutions based on relative weights and systematical considerations of both efficiency and equity. This dissertation further models and solves an integrated flight re-routing problem on an airspace network. Given a network of airspace sectors with a set of waypoint entries and a set of flights belonging to different air carriers, the optimization model aims to minimize the total flight travel time subject to a set of flight routing equity, operational and safety requirements. A time-dependent network flow programming formulation is proposed with stochastic sector capacities and rerouting equity for each air carrier as side constraints. A Lagrangian relaxation based method is used to dualize these constraints and decompose the original complex problem into a sequence of single flight rerouting/scheduling problems. Finally, within a multi-objective utility maximization framework, the dissertation proposes several practically useful heuristic algorithms for the long-term airport slot assignment problem. Alternative models are constructed to decompose the complex model into a series of hourly assignment sub-problems. A new paired assignment heuristic algorithm is developed to adapt the round robin scheduling principle for improving fairness measures across different airlines. Computational results are presented to show the strength of each proposed modeling approach

Bimodal compensatory tracking and attention

Subjects performed visual and auditory compensatory tracking separately as well as in dual task combination. In a third condition Ss tracked one signal and copied with his other hand the control movement, thus emitting two identical responses to one input. Normalized mean squared error (NMSE) was lowest in single task, highest in bimodal dual task, with copying/tracking NMSE falling somewhere in between. NMSE was also found to vary as a function of input bandwidth, order of control, and input/plant bandwidth and order of control combinations. The error signal in each loop was sampled once every 100 msec and the samples were then compared. The absolute magnitude of the error in one channel at any given instance was found to be independent of the magnitude of the error in the other loop. This relationship held even when the information processing rate was increased by increasing the input bandwidth. The results do not support single-channel, information processing theories of attention. Moreover, they indicate a revision of current undifferentiated capacity models of attention (i.e., Kahneman, 1973; Moray, 1967). It was found that the performance of either one of two concurrently performed tracking tasks was a function of the informational content of the other. This result implies that attentional resources are not allocated freely to the various tasks, but rather, it suggests that the amount of attention allocated to a given task depends and is a weighted function of the concurrent informational content of other, unrelated and distracting, tasks and events. Although, it was fairly evident from the results that subjects could perform continuous tracking tasks simultaneously the observed task interference effects do indicate that the human controller of two, otherwise parallel, multiple single-loop systems does not behave either as a true parallel, or as a serial, information processor. It is suggested that one of the key functions of man's attentional process is the modulation of stimulus information to enable more or less optimal input to more or less permanent structures in the brain. Thus it is argued, a general undifferentiated capacity theory of attention may not be incompatible with current multiprocessor theories of attention, (Allport, Antonis and Reynolds, 1972). Moreover, in view of supportive existing evidence, it is also suggested that one other functional role played by attention is to enable the establishment in memory of an internal representation of task invariant descriptions than can actively be drawn upon (resources) and implemented to reduce the magnitude of task-related information. Hence, the amount of information, or uncertainty, associated with the performance of a given task is conceived to be the magnitude of discrepancy, or mismatch, between expected and actual task dependent events. Within such an undifferentiated capacity framework, it is possible, therefore, to account for time-sharing decrements of performance arising directly from either (1) changes in processing linearity, or (2) response delay, or both of these factors without having to appeal to discrete, serial, human information processing models of attention