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Mathematical Optimization models for Air Traffic Flow Management: A review
(2010-02-10) Agustín, Alba; Alonso-Ayuso, Antonio; Escudero, Laureano F.; Pizarro, Celeste
Congestion problems are becoming increasingly acute in many European and American airports and air sectors. To protect Air Traffic Control (ATC) from overload a planning activity called Air Traffic Flow Management (ATFM) tries to anticipate and prevent overload and limit resulting delays. When the traffic expects to exceed the airport arrival and departure capacities or the airsector capacity a delay in the flight arrival (so called-congestion) occurs. The casuistry to be considered in this field is very extensive. In general, most references to be found in the literature written some years ago refer to the simplest models, those which do not take into account airsector. This is so because this work was first studied in USA, where only the problems of congestion in airports basically occur. In the paper we present a state-of-the-art survey on the main optimization models encountered in the literature. They are classified as follows: (1) Single-Airport Ground-Holding Problem (SAGHP). The simplest of the methodologies of planning modelling studied proposes solutions to the problem of deciding the optimal planning for an arrival airport. (2) Multi-Airport Ground-Holding Problem (MAGHP). In this methodology the field of work is extended and the inter-relationship which exists between different airports is included. (3) Air Traffic Flow Management Problem (ATFMP). This methodology attempts to solve real situations that are much more complex than those which can be dealt with using the previous methodologies, since the air sector capacity is also considered. (4) Air Traffic Flow Management Rerouting Problem (ATFMRP). This methodology considers the more realistic situation where the flights can be diverted to alternative routes. (5) Air Traffic Flow Management Rerouting Problem (ATFMRP) with uncertainty. The ATFM problem is especially sensitive to changes in capacity. This leads to generalize the previous methodologies and to include generic uncertainty for these possible unforeseen changes in the parameters of the model, making way for stochastic methodologies. This type of problems are the most difficult ones, but alas the realistic ones.
Medium range optimization of copper extraction planning under uncertainty in future copper prices
(2011-11-24) Alonso-Ayuso, Antonio; Carvallo, Felipe; Escudero, Laureano F; Guignard, Monique; Pi, Jiaxing; Purammalka, Raghav; Weintraub, Andres
Deterministic mine planning models along a time horizon have proved to be very effective in supporting decisions on sequencing the extraction of material in copper mines. Some of these models have been developed for, and used successfully by CODELCO, the Chilean state copper company. These models are extremely large. In this paper, we wish to consider the uncertainty in a very volatile parameter of the problem, namely, the copper price along a given time horizon. We represent the uncertainty by a multistage scenario tree. The resulting stochastic model is then converted into a mixed 0-1 Deterministic Equivalent Model using a compact representation. We first introduce the stochastic model that maximizes the expected profit along the time horizon over all scenarios (i.e., as in a risk neutral environment). We then present several approaches for risk management, in a risk averse environment. Specifically, we consider the maximization of the Value-at-Risk and several variants of the Conditional Value-at-Risk, the maximization of the expected profit minus the weighted probability of having a ``bad" scenario in the solution provided by the model, and the maximization of the expected profit subject to stochastic dominance constraints for a set of profiles given by the pairs of target profits and bounds on either the probability of not reaching them or the expected profit deficit over the targets. We present an extensive computational experience on the actual problem, by comparing the risk neutral approach, the tested risk averse strategies and the performance of the traditional deterministic approach that uses the expected value of the uncertain parameters. The results clearly show the advantage of using any risk neutral strategy over the traditional deterministic approach, as well as the advantage of using the risk averse strategy over the risk neutral one, although the plain use of the MIP solvers should be replaced by decomposition algorithms.
Structuring bilateral energy contract portfolios in competitive markets
(2010) Alonso-Ayuso, Antonio; Domenica, Nico di; Escudero, Laureano F; Pizarro, Celeste

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Examinando Documentos de Trabajo por Autor "Alonso-Ayuso, Antonio"