Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/209351 
Year of Publication: 
2018
Citation: 
[Editor:] Kersten, Wolfgang [Editor:] Blecker, Thorsten [Editor:] Ringle, Christian M. [Title:] The Road to a Digitalized Supply Chain Management: Smart and Digital Solutions for Supply Chain Management. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 25 [ISBN:] 978-3-7467-6535-8 [Publisher:] epubli GmbH [Place:] Berlin [Year:] 2018 [Pages:] 221-247
Publisher: 
epubli GmbH, Berlin
Abstract: 
The purpose of Aircraft Fleet Planning is to provide the number and type of aircraft for acquisition, its time of acquisition, and trade-in or phase out of fleet. Airlines select a particular type of aircraft from the manufacturer on the basis of optimum cost, considering a number of constraints. Because of existence of several conflicting criteria, the solution approach becomes an NP-hard problem. As such, a traditional linear programming approach cannot optimize the system in a reasonable time frame. This paper aims at developing a model for selecting aircraft using Artificial Neural Networks. Key inputs have been obtained from the major areas of aircraft design characteristics, aircraft physical performance, maintenance needs, operating economics, acquisition cost, operating cost and customer satisfaction. The input values are fuzzy in nature. However, several methods for combined use of fuzzy logic systems and neural networks have been suggested. Experience, which is conventionally used for selecting a particular type of aircraft, has been used for training of the proposed network. Single-layer ANN model provided a good solution with optimality in cost, without sacrificing time constraint and algorithmic complexity. The airline business will be immensely benefited from the solution procedure.
Subjects: 
Aircraft Fleet Planning
ANN
Fuzzy
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-sa Logo
Document Type: 
Conference Paper

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