Tabu Search-Based Algorithm for Large Scale Crew Scheduling Problems

In this paper, the problem of finding a work schedule for airline crew members in a given time horizon is tackled. This problem is known in the literature as Airline Crew Scheduling. The objective is to define the minimum cost schedules where each crew, associated to a combination of commercial flig...

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Main Author: Marco Caserta
Format: Article
Language:English
Published: Universidad Nacional Autónoma de México (UNAM) 2005-01-01
Series:Contaduría y Administración
Online Access:http://www.redalyc.org/articulo.oa?id=39521504
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spelling doaj-8d13b7e4a775478aa615a8c14225ae8c2020-11-24T20:52:52ZengUniversidad Nacional Autónoma de México (UNAM)Contaduría y Administración0186-10422448-84102005-01-012154970Tabu Search-Based Algorithm for Large Scale Crew Scheduling ProblemsMarco CasertaIn this paper, the problem of finding a work schedule for airline crew members in a given time horizon is tackled. This problem is known in the literature as Airline Crew Scheduling. The objective is to define the minimum cost schedules where each crew, associated to a combination of commercial flights or legs called pairing, is assigned to one or more flights ensuring that the whole set of flights is covered by crew members. The Crew Scheduling Problem can be modeled by using the Set Covering formulation. This paper presents a new algorithm whose centerpiece is a primal-to-dual scheme aimed at linking any primal solution to the dual feasible vector that best reflects the quality of the primal solution. This new mechanism is used to intertwine a tabu search based, primal intensive, scheme with a lagrangian based, dual intensive, scheme to design a primal-dual algorithm that progressively reduces the gap between upper and lower bound. The algorithm has been tested on benchmark problems from the literature. In this paper, results on real-world airline instances are presented: out of six well-known problems, the algorithm is able to match the optimal solution for four of them while for the last two, whose optimal solution is not known, a new best known solution is found.http://www.redalyc.org/articulo.oa?id=39521504
collection DOAJ
language English
format Article
sources DOAJ
author Marco Caserta
spellingShingle Marco Caserta
Tabu Search-Based Algorithm for Large Scale Crew Scheduling Problems
Contaduría y Administración
author_facet Marco Caserta
author_sort Marco Caserta
title Tabu Search-Based Algorithm for Large Scale Crew Scheduling Problems
title_short Tabu Search-Based Algorithm for Large Scale Crew Scheduling Problems
title_full Tabu Search-Based Algorithm for Large Scale Crew Scheduling Problems
title_fullStr Tabu Search-Based Algorithm for Large Scale Crew Scheduling Problems
title_full_unstemmed Tabu Search-Based Algorithm for Large Scale Crew Scheduling Problems
title_sort tabu search-based algorithm for large scale crew scheduling problems
publisher Universidad Nacional Autónoma de México (UNAM)
series Contaduría y Administración
issn 0186-1042
2448-8410
publishDate 2005-01-01
description In this paper, the problem of finding a work schedule for airline crew members in a given time horizon is tackled. This problem is known in the literature as Airline Crew Scheduling. The objective is to define the minimum cost schedules where each crew, associated to a combination of commercial flights or legs called pairing, is assigned to one or more flights ensuring that the whole set of flights is covered by crew members. The Crew Scheduling Problem can be modeled by using the Set Covering formulation. This paper presents a new algorithm whose centerpiece is a primal-to-dual scheme aimed at linking any primal solution to the dual feasible vector that best reflects the quality of the primal solution. This new mechanism is used to intertwine a tabu search based, primal intensive, scheme with a lagrangian based, dual intensive, scheme to design a primal-dual algorithm that progressively reduces the gap between upper and lower bound. The algorithm has been tested on benchmark problems from the literature. In this paper, results on real-world airline instances are presented: out of six well-known problems, the algorithm is able to match the optimal solution for four of them while for the last two, whose optimal solution is not known, a new best known solution is found.
url http://www.redalyc.org/articulo.oa?id=39521504
work_keys_str_mv AT marcocaserta tabusearchbasedalgorithmforlargescalecrewschedulingproblems
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