Beware of the classical benchmark instances for the Traveling Salesman Problem with Time Windows

Autores
Soulignac, Francisco Juan
Año de publicación
2026
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We propose a simple and exact method for the Traveling Salesman Problem with Time Windows and Makespan objective (TSPTW-M) that solves all instances of the classical benchmark with 50 or more customers in less than ten seconds each. Applying this algorithm as an off-the-shelf method, we also solve all but one of these instances for the Duration objective. Our main conclusion is that these instances alone are no longer representative for evaluating the TSPTW-M and its Duration variant: their structure can be exploited to yield results that seem outstanding at first glance. Additionally, caution is advised when designing hard training sets for machine learning algorithms.
Fil: Soulignac, Francisco Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina
Materia
TRAVELING SALESMAN PROBLEM WITH TIME WINDOWS
MAKESPAN OBJECTIVE
DURATION OBJECTIVE
INFORMED SEARCH
BENCHMARK INSTANCES
TRAINING DATASETS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/291151
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/291151
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Beware of the classical benchmark instances for the Traveling Salesman Problem with Time WindowsSoulignac, Francisco JuanTRAVELING SALESMAN PROBLEM WITH TIME WINDOWSMAKESPAN OBJECTIVEDURATION OBJECTIVEINFORMED SEARCHBENCHMARK INSTANCESTRAINING DATASETShttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1We propose a simple and exact method for the Traveling Salesman Problem with Time Windows and Makespan objective (TSPTW-M) that solves all instances of the classical benchmark with 50 or more customers in less than ten seconds each. Applying this algorithm as an off-the-shelf method, we also solve all but one of these instances for the Duration objective. Our main conclusion is that these instances alone are no longer representative for evaluating the TSPTW-M and its Duration variant: their structure can be exploited to yield results that seem outstanding at first glance. Additionally, caution is advised when designing hard training sets for machine learning algorithms.Fil: Soulignac, Francisco Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaPergamon-Elsevier Science Ltd2026-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/291151Soulignac, Francisco Juan; Beware of the classical benchmark instances for the Traveling Salesman Problem with Time Windows; Pergamon-Elsevier Science Ltd; Computers & Operations Research; 191; 3-2026; 1-150305-0548CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S0305054826000791info:eu-repo/semantics/altIdentifier/doi/10.1016/j.cor.2026.107461info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2026-08-25T15:05:33Zoai:ri.conicet.gov.ar:11336/291151instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982026-08-25 15:05:34.073CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Beware of the classical benchmark instances for the Traveling Salesman Problem with Time Windows
title Beware of the classical benchmark instances for the Traveling Salesman Problem with Time Windows
spellingShingle Beware of the classical benchmark instances for the Traveling Salesman Problem with Time Windows
Soulignac, Francisco Juan
TRAVELING SALESMAN PROBLEM WITH TIME WINDOWS
MAKESPAN OBJECTIVE
DURATION OBJECTIVE
INFORMED SEARCH
BENCHMARK INSTANCES
TRAINING DATASETS
title_short Beware of the classical benchmark instances for the Traveling Salesman Problem with Time Windows
title_full Beware of the classical benchmark instances for the Traveling Salesman Problem with Time Windows
title_fullStr Beware of the classical benchmark instances for the Traveling Salesman Problem with Time Windows
title_full_unstemmed Beware of the classical benchmark instances for the Traveling Salesman Problem with Time Windows
title_sort Beware of the classical benchmark instances for the Traveling Salesman Problem with Time Windows
dc.creator.none.fl_str_mv Soulignac, Francisco Juan
author Soulignac, Francisco Juan
author_facet Soulignac, Francisco Juan
author_role author
dc.subject.none.fl_str_mv TRAVELING SALESMAN PROBLEM WITH TIME WINDOWS
MAKESPAN OBJECTIVE
DURATION OBJECTIVE
INFORMED SEARCH
BENCHMARK INSTANCES
TRAINING DATASETS
topic TRAVELING SALESMAN PROBLEM WITH TIME WINDOWS
MAKESPAN OBJECTIVE
DURATION OBJECTIVE
INFORMED SEARCH
BENCHMARK INSTANCES
TRAINING DATASETS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv We propose a simple and exact method for the Traveling Salesman Problem with Time Windows and Makespan objective (TSPTW-M) that solves all instances of the classical benchmark with 50 or more customers in less than ten seconds each. Applying this algorithm as an off-the-shelf method, we also solve all but one of these instances for the Duration objective. Our main conclusion is that these instances alone are no longer representative for evaluating the TSPTW-M and its Duration variant: their structure can be exploited to yield results that seem outstanding at first glance. Additionally, caution is advised when designing hard training sets for machine learning algorithms.
Fil: Soulignac, Francisco Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina
description We propose a simple and exact method for the Traveling Salesman Problem with Time Windows and Makespan objective (TSPTW-M) that solves all instances of the classical benchmark with 50 or more customers in less than ten seconds each. Applying this algorithm as an off-the-shelf method, we also solve all but one of these instances for the Duration objective. Our main conclusion is that these instances alone are no longer representative for evaluating the TSPTW-M and its Duration variant: their structure can be exploited to yield results that seem outstanding at first glance. Additionally, caution is advised when designing hard training sets for machine learning algorithms.
publishDate 2026
dc.date.none.fl_str_mv 2026-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/291151
Soulignac, Francisco Juan; Beware of the classical benchmark instances for the Traveling Salesman Problem with Time Windows; Pergamon-Elsevier Science Ltd; Computers & Operations Research; 191; 3-2026; 1-15
0305-0548
CONICET Digital
CONICET
url http://hdl.handle.net/11336/291151
identifier_str_mv Soulignac, Francisco Juan; Beware of the classical benchmark instances for the Traveling Salesman Problem with Time Windows; Pergamon-Elsevier Science Ltd; Computers & Operations Research; 191; 3-2026; 1-15
0305-0548
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S0305054826000791
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.cor.2026.107461
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.265058

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