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Published in: Structural and Multidisciplinary Optimization 4/2015

01-04-2015 | RESEARCH PAPER

System-of-systems approach to air transportation design using nested optimization and direct search

Authors: Gautam Marwaha, Michael Kokkolaras

Published in: Structural and Multidisciplinary Optimization | Issue 4/2015

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Abstract

Aircraft sizing, route network design, demand estimation and allocation of aircraft to routes are different facets of the air transportation optimization problem that can be viewed as individual “systems,” since they can be conducted independently. In fact, there is a large body of literature that investigates each of these as a stand-alone problem. In this regard, the air transportation design optimization problem can be viewed as an optimal system-of-systems (SoS) design problem. The resulting mixed variable programming problem may not be solvable using an all-in-one (AiO) approach because its size and complexity grow rapidly with increasing number of network nodes. In this work, we use a decomposition-based nested formulation and the Mesh Adaptive Direct Search (MADS) optimization algorithm to solve the optimal SoS design problem. The two-stage expansion of an regional Canadian airline’s network to enable national operations is considered as a demonstrating example.

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Footnotes
1
We assume that flights between cities are reciprocal.
 
2
We use MADS to solve the network design optimization problem as well.
 
3
We ignore Halifax otherwise the number of feasible routes for aircraft X falls to 45.
 
4
As mentioned earlier, we could not solve the problem using the AiO approach (which took 80 minutes for the 7-city problem) despite several attempts as computations were exceeding 24 hours and Matlab was crashing due to memory allocation problems.
 
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Metadata
Title
System-of-systems approach to air transportation design using nested optimization and direct search
Authors
Gautam Marwaha
Michael Kokkolaras
Publication date
01-04-2015
Publisher
Springer Berlin Heidelberg
Published in
Structural and Multidisciplinary Optimization / Issue 4/2015
Print ISSN: 1615-147X
Electronic ISSN: 1615-1488
DOI
https://doi.org/10.1007/s00158-014-1180-1

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