Two-Stage Heuristic Algorithm for Aircraft Recovery Problem

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...

Full description

Bibliographic Details
Main Author: Cheng Zhang
Format: Article
Language:English
Published: Hindawi Limited 2017-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2017/9575719
id doaj-51161ceee2e44c80a63f5d8399eb64b8
record_format Article
spelling doaj-51161ceee2e44c80a63f5d8399eb64b82020-11-24T21:05:14ZengHindawi LimitedDiscrete Dynamics in Nature and Society1026-02261607-887X2017-01-01201710.1155/2017/95757199575719Two-Stage Heuristic Algorithm for Aircraft Recovery ProblemCheng Zhang0School of Economics & Management, Tongji University, Shanghai 200092, ChinaThis 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.http://dx.doi.org/10.1155/2017/9575719
collection DOAJ
language English
format Article
sources DOAJ
author Cheng Zhang
spellingShingle Cheng Zhang
Two-Stage Heuristic Algorithm for Aircraft Recovery Problem
Discrete Dynamics in Nature and Society
author_facet Cheng Zhang
author_sort Cheng Zhang
title Two-Stage Heuristic Algorithm for Aircraft Recovery Problem
title_short Two-Stage Heuristic Algorithm for Aircraft Recovery Problem
title_full Two-Stage Heuristic Algorithm for Aircraft Recovery Problem
title_fullStr Two-Stage Heuristic Algorithm for Aircraft Recovery Problem
title_full_unstemmed Two-Stage Heuristic Algorithm for Aircraft Recovery Problem
title_sort two-stage heuristic algorithm for aircraft recovery problem
publisher Hindawi Limited
series Discrete Dynamics in Nature and Society
issn 1026-0226
1607-887X
publishDate 2017-01-01
description 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.
url http://dx.doi.org/10.1155/2017/9575719
work_keys_str_mv AT chengzhang twostageheuristicalgorithmforaircraftrecoveryproblem
_version_ 1716769502778097664