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Discrete Dynamics in Nature and Society
Volume 2017 (2017), Article ID 9575719, 12 pages
https://doi.org/10.1155/2017/9575719
Research Article

Two-Stage Heuristic Algorithm for Aircraft Recovery Problem

School of Economics & Management, Tongji University, Shanghai 200092, China

Correspondence should be addressed to Cheng Zhang; nc.ude.ijgnot@6111351

Received 26 January 2017; Revised 31 May 2017; Accepted 10 July 2017; Published 24 August 2017

Academic Editor: Aura Reggiani

Copyright © 2017 Cheng Zhang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This study focuses on the aircraft recovery problem (ARP). In real-life operations, disruptions always cause schedule failures and make airlines suffer from great loss. Therefore, the main objective of the aircraft recovery problem is to minimize the total recovery cost and solve the problem within reasonable runtimes. An aircraft recovery model (ARM) is proposed herein to formulate the ARP and use feasible line of flights as the basic variables in the model. We define the feasible line of flights (LOFs) as a sequence of flights flown by an aircraft within one day. The number of LOFs exponentially grows with the number of flights. Hence, a two-stage heuristic is proposed to reduce the problem scale. The algorithm integrates a heuristic scoring procedure with an aggregated aircraft recovery model (AARM) to preselect LOFs. The approach is tested on five real-life test scenarios. The computational results show that the proposed model provides a good formulation of the problem and can be solved within reasonable runtimes with the proposed methodology. The two-stage heuristic significantly reduces the number of LOFs after each stage and finally reduces the number of variables and constraints in the aircraft recovery model.