---------- Forwarded message ----------
Date: Wed, 13 May 2009 14:59:47 +0000
From: yadira isabel silva soto <yadis76(a)hotmail.com>
To: pisis-l(a)lists.uanl.mx
Subject: [PISIS-L] Seminario jueves 14 de mayo
Hola comunidad PISIS.
El programa de Posgrado de Ingenier�a de Sistemas tiene el honor de invitar a la comunidad y p�blico en general al seminario de esta semana, en el cual tendremos de ponente al Dr. Michael Hanowsky.
Tema: Por confirmar
Resumen:
A Ground Delay Program, or GDP, is a technique used by the Federal Aviation Administration to allocate scarce arrival capacity at airports during periods of inclement weather. The optimal allocation of capacity is complicated in practice by uncertainty in the actual capacity, a disparity between the time at which actions can be taken and knowledge is available, non-linear cost functions in regards to delays experienced by flights scheduled to use the airport, and a variety of stakeholders, each which may make different claims on the available resource. This presentation discusses two analyses in regards to the design of a GDP. The first analysis proposes a stochastic mixed-integer programming (MIP) model model that solves for the optimal assignment of ground delay to aircraft for a stochastic and dynamic forecast of the airport arrival capacity, with non-linear delay cost functions, and a capacity of the airborne arrival queue. The model identifies an allocation of forecast capacity that minimizes the total expected aircraft delay cost, assuming that aircraft priority to use the capacity is first-come-first-serve (FCFS). The model is applied to several hypothetical examples and, in comparison to prior models from the literature, identifies solutions with a lower total expected cost, a smaller maximum observed arrival queue, or both. The second analysis is a MIP that allows for aircraft to be assigned different priorities to use available capacity in proportion to the number of passengers that each carries. This second model identifies a capacity allocation that minimizes the total expected passenger delay cost; a comparison of these results to those of the first model show that the total cost of delays to passengers could be reduced by more than 30% if the FAA were to directly consider the cost of delays to passengers during the design of a GDP and allocate forecast capacity based on passenger counts rather than FCFS.
Biograf�a breve:
Dr. Michael Hanowsky is a Fulbright-Garc�a Robles Scholar and a Fellow with the Centro de Estudios y Programas Interamericanos at the Instituto Tecnol�gico Aut�nomo de M�xico. His research in Mexico is examining the development of federal policies regarding the intersection of transport, economic development, and climate change. In 2008, he graduated with a doctorate in Engineering Systems from the Massachusetts Institute of Technology, where his research focused on techniques to reduce air traffic congestion in the U.S. Michael also holds masters degrees in Transportation and Operations Research and worked previously as a consultant for the pharmaceutical industry.
Fecha: Jueves 14 de mayo de 2009.
Hora: 12:30 p.m.
Lugar: Auditorio Dr. Ra�l G. Quintero Flores.
Este jueves, despu�s del seminario, SI nos quedaremos una hora m�s los inscritos a seminario.
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