Solving Dynamic Delivery Services Using Ant Colony Optimization

Detalhes bibliográficos
Autor(a) principal: Martins, M.
Data de Publicação: 2020
Outros Autores: Coito, T., Firme, B., Viegas, J., Sousa, J., Figueiredo, Joao, Vieira, S.
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10174/28812
https://doi.org/MARTINS, M., COITO, T., FIRME, B., VIEGAS, J., SOUSA, J., FIGUEIREDO, J., VIEIRA, S. [2020] “Solving Dynamic Delivery Services Using Ant Colony Optimization”. In: Lesot MJ. et al. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2020. Communications in Computer and Information Science, vol 1237. Springer, https://doi.org/10.1007/978-3-030-50146-4_25
https://doi.org/10.1007/978-3-030-50146-4_25
Resumo: This article presents a model for courier services designed to guide a fleet of vehicles over a dynamic set of requests. Motivation for this problem comes from a real-world scenario in an ever-changing environment, where the time to solve such optimization problem is constrained instead of endlessly searching for the optimal solution. First, a hybrid method combining Ant Colony Optimization with Local Search is proposed, which is used to solve a given static instance. Then, a framework to handle and adapt to dynamic changes over time is defined. A new method pairing nearest neighbourhood search with subtractive clustering is proposed to improve initial solutions and accelerate the convergence of the optimization algorithm. Overall, the proposed strategy presents good results for the dynamic environment and is suitable to be applied on real-world scenarios.
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spelling Solving Dynamic Delivery Services Using Ant Colony OptimizationPickup delivery problemAnt Colony OptimizationLocal SearchTime windowsDynamic requestsThis article presents a model for courier services designed to guide a fleet of vehicles over a dynamic set of requests. Motivation for this problem comes from a real-world scenario in an ever-changing environment, where the time to solve such optimization problem is constrained instead of endlessly searching for the optimal solution. First, a hybrid method combining Ant Colony Optimization with Local Search is proposed, which is used to solve a given static instance. Then, a framework to handle and adapt to dynamic changes over time is defined. A new method pairing nearest neighbourhood search with subtractive clustering is proposed to improve initial solutions and accelerate the convergence of the optimization algorithm. Overall, the proposed strategy presents good results for the dynamic environment and is suitable to be applied on real-world scenarios.Lesot MJ. et al. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2020. Communications in Computer and Information Science, vol 1237. Springer2021-01-25T12:28:22Z2021-01-252020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/28812https://doi.org/MARTINS, M., COITO, T., FIRME, B., VIEGAS, J., SOUSA, J., FIGUEIREDO, J., VIEIRA, S. [2020] “Solving Dynamic Delivery Services Using Ant Colony Optimization”. In: Lesot MJ. et al. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2020. Communications in Computer and Information Science, vol 1237. Springer, https://doi.org/10.1007/978-3-030-50146-4_25https://doi.org/10.1007/978-3-030-50146-4_25http://hdl.handle.net/10174/28812https://doi.org/10.1007/978-3-030-50146-4_25porndndndndndjfig@uevora.ptndMartins, M.Coito, T.Firme, B.Viegas, J.Sousa, J.Figueiredo, JoaoVieira, S.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T19:25:04Zoai:dspace.uevora.pt:10174/28812Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:18:29.580391Repositório 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 Solving Dynamic Delivery Services Using Ant Colony Optimization
title Solving Dynamic Delivery Services Using Ant Colony Optimization
spellingShingle Solving Dynamic Delivery Services Using Ant Colony Optimization
Martins, M.
Pickup delivery problem
Ant Colony Optimization
Local Search
Time windows
Dynamic requests
title_short Solving Dynamic Delivery Services Using Ant Colony Optimization
title_full Solving Dynamic Delivery Services Using Ant Colony Optimization
title_fullStr Solving Dynamic Delivery Services Using Ant Colony Optimization
title_full_unstemmed Solving Dynamic Delivery Services Using Ant Colony Optimization
title_sort Solving Dynamic Delivery Services Using Ant Colony Optimization
author Martins, M.
author_facet Martins, M.
Coito, T.
Firme, B.
Viegas, J.
Sousa, J.
Figueiredo, Joao
Vieira, S.
author_role author
author2 Coito, T.
Firme, B.
Viegas, J.
Sousa, J.
Figueiredo, Joao
Vieira, S.
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Martins, M.
Coito, T.
Firme, B.
Viegas, J.
Sousa, J.
Figueiredo, Joao
Vieira, S.
dc.subject.por.fl_str_mv Pickup delivery problem
Ant Colony Optimization
Local Search
Time windows
Dynamic requests
topic Pickup delivery problem
Ant Colony Optimization
Local Search
Time windows
Dynamic requests
description This article presents a model for courier services designed to guide a fleet of vehicles over a dynamic set of requests. Motivation for this problem comes from a real-world scenario in an ever-changing environment, where the time to solve such optimization problem is constrained instead of endlessly searching for the optimal solution. First, a hybrid method combining Ant Colony Optimization with Local Search is proposed, which is used to solve a given static instance. Then, a framework to handle and adapt to dynamic changes over time is defined. A new method pairing nearest neighbourhood search with subtractive clustering is proposed to improve initial solutions and accelerate the convergence of the optimization algorithm. Overall, the proposed strategy presents good results for the dynamic environment and is suitable to be applied on real-world scenarios.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01T00:00:00Z
2021-01-25T12:28:22Z
2021-01-25
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10174/28812
https://doi.org/MARTINS, M., COITO, T., FIRME, B., VIEGAS, J., SOUSA, J., FIGUEIREDO, J., VIEIRA, S. [2020] “Solving Dynamic Delivery Services Using Ant Colony Optimization”. In: Lesot MJ. et al. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2020. Communications in Computer and Information Science, vol 1237. Springer, https://doi.org/10.1007/978-3-030-50146-4_25
https://doi.org/10.1007/978-3-030-50146-4_25
http://hdl.handle.net/10174/28812
https://doi.org/10.1007/978-3-030-50146-4_25
url http://hdl.handle.net/10174/28812
https://doi.org/MARTINS, M., COITO, T., FIRME, B., VIEGAS, J., SOUSA, J., FIGUEIREDO, J., VIEIRA, S. [2020] “Solving Dynamic Delivery Services Using Ant Colony Optimization”. In: Lesot MJ. et al. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2020. Communications in Computer and Information Science, vol 1237. Springer, https://doi.org/10.1007/978-3-030-50146-4_25
https://doi.org/10.1007/978-3-030-50146-4_25
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language por
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dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Lesot MJ. et al. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2020. Communications in Computer and Information Science, vol 1237. Springer
publisher.none.fl_str_mv Lesot MJ. et al. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2020. Communications in Computer and Information Science, vol 1237. Springer
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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