Business model of aircraft fleet planning using ANN

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.