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The bi-objective stochastic covering tour problem

We formulate a bi-objective covering tour model with stochastic demand where the two objectives are given by (i) cost (opening cost for distribution centers plus routing cost for a fleet of vehicles) and (ii) expected uncovered demand. In the model, it is assumed that depending on the distance, a ce...

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Detalles Bibliográficos
Autores principales: Tricoire, Fabien, Graf, Alexandra, Gutjahr, Walter J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Pergamon Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3587456/
https://www.ncbi.nlm.nih.gov/pubmed/23471203
http://dx.doi.org/10.1016/j.cor.2011.09.009
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author Tricoire, Fabien
Graf, Alexandra
Gutjahr, Walter J.
author_facet Tricoire, Fabien
Graf, Alexandra
Gutjahr, Walter J.
author_sort Tricoire, Fabien
collection PubMed
description We formulate a bi-objective covering tour model with stochastic demand where the two objectives are given by (i) cost (opening cost for distribution centers plus routing cost for a fleet of vehicles) and (ii) expected uncovered demand. In the model, it is assumed that depending on the distance, a certain percentage of clients go from their homes to the nearest distribution center. An application in humanitarian logistics is envisaged. For the computational solution of the resulting bi-objective two-stage stochastic program with recourse, a branch-and-cut technique, applied to a sample-average version of the problem obtained from a fixed random sample of demand vectors, is used within an epsilon-constraint algorithm. Computational results on real-world data for rural communities in Senegal show the viability of the approach.
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spelling pubmed-35874562013-03-05 The bi-objective stochastic covering tour problem Tricoire, Fabien Graf, Alexandra Gutjahr, Walter J. Comput Oper Res Article We formulate a bi-objective covering tour model with stochastic demand where the two objectives are given by (i) cost (opening cost for distribution centers plus routing cost for a fleet of vehicles) and (ii) expected uncovered demand. In the model, it is assumed that depending on the distance, a certain percentage of clients go from their homes to the nearest distribution center. An application in humanitarian logistics is envisaged. For the computational solution of the resulting bi-objective two-stage stochastic program with recourse, a branch-and-cut technique, applied to a sample-average version of the problem obtained from a fixed random sample of demand vectors, is used within an epsilon-constraint algorithm. Computational results on real-world data for rural communities in Senegal show the viability of the approach. Pergamon Press 2012-07 /pmc/articles/PMC3587456/ /pubmed/23471203 http://dx.doi.org/10.1016/j.cor.2011.09.009 Text en © 2012 Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/3.0/ Open Access under CC BY-NC-ND 3.0 (https://creativecommons.org/licenses/by-nc-nd/3.0/) license
spellingShingle Article
Tricoire, Fabien
Graf, Alexandra
Gutjahr, Walter J.
The bi-objective stochastic covering tour problem
title The bi-objective stochastic covering tour problem
title_full The bi-objective stochastic covering tour problem
title_fullStr The bi-objective stochastic covering tour problem
title_full_unstemmed The bi-objective stochastic covering tour problem
title_short The bi-objective stochastic covering tour problem
title_sort bi-objective stochastic covering tour problem
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3587456/
https://www.ncbi.nlm.nih.gov/pubmed/23471203
http://dx.doi.org/10.1016/j.cor.2011.09.009
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