The Dial-a-Ride Problem with Split Requests and Profits

Detalhes bibliográficos
Autor(a) principal: Parragh,SN
Data de Publicação: 2015
Outros Autores: Jorge Pinho de Sousa, Bernardo Almada-Lobo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.inesctec.pt/handle/123456789/6365
http://dx.doi.org/10.1287/trsc.2014.0520
Resumo: In this paper we introduce the dial-a-ride problem with split requests and profits (DARPSRP). Users place transportation requests, specifying a pickup location, a delivery location, and a time window for either of the two. Based on maximum user ride time considerations, the second time window is generated. A given fleet of vehicles, each with a certain capacity, is available to serve these requests, and maximum route duration constraints have to be respected. Each request is associated with a revenue and the objective is to maximize the total profit, that is, the total revenue minus the total costs. Transportation requests involving several persons may be split if it is beneficial to do so. We formulate the DARPSRP as a mixed-integer program using position variables and in terms of a path-based formulation. For the solution of the latter, we design a branch-and-price algorithm. The largest instance solved to optimality, when applied to available instances from the literature, has 40 requests; when applied to newly generated instances, the largest instance solved to optimality consists of 24 requests. To solve larger instances a variable neighborhood search algorithm is developed. We investigate the impact of request splitting under different geographical settings, assuming favorable settings for request splitting in terms of the number of people per request. The largest benefits from request splitting are obtained for problem settings exhibiting clustered customer locations.
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spelling The Dial-a-Ride Problem with Split Requests and ProfitsIn this paper we introduce the dial-a-ride problem with split requests and profits (DARPSRP). Users place transportation requests, specifying a pickup location, a delivery location, and a time window for either of the two. Based on maximum user ride time considerations, the second time window is generated. A given fleet of vehicles, each with a certain capacity, is available to serve these requests, and maximum route duration constraints have to be respected. Each request is associated with a revenue and the objective is to maximize the total profit, that is, the total revenue minus the total costs. Transportation requests involving several persons may be split if it is beneficial to do so. We formulate the DARPSRP as a mixed-integer program using position variables and in terms of a path-based formulation. For the solution of the latter, we design a branch-and-price algorithm. The largest instance solved to optimality, when applied to available instances from the literature, has 40 requests; when applied to newly generated instances, the largest instance solved to optimality consists of 24 requests. To solve larger instances a variable neighborhood search algorithm is developed. We investigate the impact of request splitting under different geographical settings, assuming favorable settings for request splitting in terms of the number of people per request. The largest benefits from request splitting are obtained for problem settings exhibiting clustered customer locations.2018-01-16T14:37:01Z2015-01-01T00:00:00Z2015info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/6365http://dx.doi.org/10.1287/trsc.2014.0520engParragh,SNJorge Pinho de SousaBernardo Almada-Loboinfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:58Zoai:repositorio.inesctec.pt:123456789/6365Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:51.651561Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv The Dial-a-Ride Problem with Split Requests and Profits
title The Dial-a-Ride Problem with Split Requests and Profits
spellingShingle The Dial-a-Ride Problem with Split Requests and Profits
Parragh,SN
title_short The Dial-a-Ride Problem with Split Requests and Profits
title_full The Dial-a-Ride Problem with Split Requests and Profits
title_fullStr The Dial-a-Ride Problem with Split Requests and Profits
title_full_unstemmed The Dial-a-Ride Problem with Split Requests and Profits
title_sort The Dial-a-Ride Problem with Split Requests and Profits
author Parragh,SN
author_facet Parragh,SN
Jorge Pinho de Sousa
Bernardo Almada-Lobo
author_role author
author2 Jorge Pinho de Sousa
Bernardo Almada-Lobo
author2_role author
author
dc.contributor.author.fl_str_mv Parragh,SN
Jorge Pinho de Sousa
Bernardo Almada-Lobo
description In this paper we introduce the dial-a-ride problem with split requests and profits (DARPSRP). Users place transportation requests, specifying a pickup location, a delivery location, and a time window for either of the two. Based on maximum user ride time considerations, the second time window is generated. A given fleet of vehicles, each with a certain capacity, is available to serve these requests, and maximum route duration constraints have to be respected. Each request is associated with a revenue and the objective is to maximize the total profit, that is, the total revenue minus the total costs. Transportation requests involving several persons may be split if it is beneficial to do so. We formulate the DARPSRP as a mixed-integer program using position variables and in terms of a path-based formulation. For the solution of the latter, we design a branch-and-price algorithm. The largest instance solved to optimality, when applied to available instances from the literature, has 40 requests; when applied to newly generated instances, the largest instance solved to optimality consists of 24 requests. To solve larger instances a variable neighborhood search algorithm is developed. We investigate the impact of request splitting under different geographical settings, assuming favorable settings for request splitting in terms of the number of people per request. The largest benefits from request splitting are obtained for problem settings exhibiting clustered customer locations.
publishDate 2015
dc.date.none.fl_str_mv 2015-01-01T00:00:00Z
2015
2018-01-16T14:37:01Z
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dc.identifier.uri.fl_str_mv http://repositorio.inesctec.pt/handle/123456789/6365
http://dx.doi.org/10.1287/trsc.2014.0520
url http://repositorio.inesctec.pt/handle/123456789/6365
http://dx.doi.org/10.1287/trsc.2014.0520
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