New benchmark instances for the Capacitated Vehicle Routing Problem

•We show the limitations of existing Capacitated Vehicle Routing Problem instances.•We propose 100 new instances and evaluate recent exact and heuristic methods.•The same generating scheme is used to create an extended benchmark of 600 instances.•Extensive experiments and statistical analyses are do...

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Bibliographic Details
Published in:	European journal of operational research Vol. 257; no. 3; pp. 845 - 858
Main Authors:	Uchoa, Eduardo, Pecin, Diego, Pessoa, Artur, Poggi, Marcus, Vidal, Thibaut, Subramanian, Anand
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 16.03.2017 Elsevier Sequoia S.A
Subjects:	Algorithms Benchmark instances Benchmarks Experimental analysis of algorithms Heuristic Routing Statistical analysis Studies Routing Experimental analysis of algorithms Benchmark instances
ISSN:	0377-2217, 1872-6860
Online Access:	Get full text
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Abstract	•We show the limitations of existing Capacitated Vehicle Routing Problem instances.•We propose 100 new instances and evaluate recent exact and heuristic methods.•The same generating scheme is used to create an extended benchmark of 600 instances.•Extensive experiments and statistical analyses are done on the extended benchmark.•We present a sophisticated website containing all existing and new instances. The recent research on the CVRP is being slowed down by the lack of a good set of benchmark instances. The existing sets suffer from at least one of the following drawbacks: (i) became too easy for current algorithms; (ii) are too artificial; (iii) are too homogeneous, not covering the wide range of characteristics found in real applications. We propose a new set of 100 instances ranging from 100 to 1000 customers, designed in order to provide a more comprehensive and balanced experimental setting. Moreover, the same generating scheme was also used to provide an extended benchmark of 600 instances. In addition to having a greater discriminating ability to identify “which algorithm is better”, these new benchmarks should also allow for a deeper statistical analysis of the performance of an algorithm. In particular, they will enable one to investigate how the characteristics of an instance affect its performance. We report such an analysis on state-of-the-art exact and heuristic methods.
AbstractList	The recent research on the CVRP is being slowed down by the lack of a good set of benchmark instances. The existing sets suffer from at least one of the following drawbacks: (i) became too easy for current algorithms; (ii) are too artificial; (iii) are too homogeneous, not covering the wide range of characteristics found in real applications. We propose a new set of 100 instances ranging from 100 to 1000 customers, designed in order to provide a more comprehensive and balanced experimental setting. Moreover, the same generating scheme was also used to provide an extended benchmark of 600 instances. In addition to having a greater discriminating ability to identify "which algorithm is better", these new benchmarks should also allow for a deeper statistical analysis of the performance of an algorithm. In particular, they will enable one to investigate how the characteristics of an instance affect its performance. We report such an analysis on state-of-the-art exact and heuristic methods. •We show the limitations of existing Capacitated Vehicle Routing Problem instances.•We propose 100 new instances and evaluate recent exact and heuristic methods.•The same generating scheme is used to create an extended benchmark of 600 instances.•Extensive experiments and statistical analyses are done on the extended benchmark.•We present a sophisticated website containing all existing and new instances. The recent research on the CVRP is being slowed down by the lack of a good set of benchmark instances. The existing sets suffer from at least one of the following drawbacks: (i) became too easy for current algorithms; (ii) are too artificial; (iii) are too homogeneous, not covering the wide range of characteristics found in real applications. We propose a new set of 100 instances ranging from 100 to 1000 customers, designed in order to provide a more comprehensive and balanced experimental setting. Moreover, the same generating scheme was also used to provide an extended benchmark of 600 instances. In addition to having a greater discriminating ability to identify “which algorithm is better”, these new benchmarks should also allow for a deeper statistical analysis of the performance of an algorithm. In particular, they will enable one to investigate how the characteristics of an instance affect its performance. We report such an analysis on state-of-the-art exact and heuristic methods.
Author	Pessoa, Artur Vidal, Thibaut Uchoa, Eduardo Pecin, Diego Subramanian, Anand Poggi, Marcus
Author_xml	– sequence: 1 givenname: Eduardo surname: Uchoa fullname: Uchoa, Eduardo email: uchoa@producao.uff.br organization: Departamento de Engenharia de Produção, Universidade Federal Fluminense, Rua Passo da Pátria, 156 São Domingos, Bloco E – 4o andar, Niterói – RJ, 24210-240, Brazil – sequence: 2 givenname: Diego surname: Pecin fullname: Pecin, Diego email: dpecin@inf.puc-rio.br organization: Departamento de Informática, Pontifícia Universidade Católica do Rio de Janeiro, Rua Marquês de São Vicente, 225 Gávea, Rio de Janeiro – RJ, 22451-900, Brazil – sequence: 3 givenname: Artur surname: Pessoa fullname: Pessoa, Artur email: artur@producao.uff.br organization: Departamento de Engenharia de Produção, Universidade Federal Fluminense, Rua Passo da Pátria, 156 São Domingos, Bloco E – 4o andar, Niterói – RJ, 24210-240, Brazil – sequence: 4 givenname: Marcus surname: Poggi fullname: Poggi, Marcus email: poggi@inf.puc-rio.br organization: Departamento de Informática, Pontifícia Universidade Católica do Rio de Janeiro, Rua Marquês de São Vicente, 225 Gávea, Rio de Janeiro – RJ, 22451-900, Brazil – sequence: 5 givenname: Thibaut surname: Vidal fullname: Vidal, Thibaut email: vidalt@inf.puc-rio.br organization: Departamento de Informática, Pontifícia Universidade Católica do Rio de Janeiro, Rua Marquês de São Vicente, 225 Gávea, Rio de Janeiro – RJ, 22451-900, Brazil – sequence: 6 givenname: Anand surname: Subramanian fullname: Subramanian, Anand email: anand@ci.ufpb.br, anandsubraman@gmail.com organization: Departamento de Sistemas de Computação Centro de Informática, Universidade Federal da Paraíba, Rua dos Escoteiros, Mangabeira, João Pessoa – PB, 58058-600, Brazil
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to the vehicle routing problem
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Snippet	•We show the limitations of existing Capacitated Vehicle Routing Problem instances.•We propose 100 new instances and evaluate recent exact and heuristic... The recent research on the CVRP is being slowed down by the lack of a good set of benchmark instances. The existing sets suffer from at least one of the...
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SubjectTerms	Algorithms Benchmark instances Benchmarks Experimental analysis of algorithms Heuristic Routing Statistical analysis Studies
Title	New benchmark instances for the Capacitated Vehicle Routing Problem
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