An Analytical Hierarchy Process-Based Approach to Solve the Multi-Objective Multiple Traveling Salesman Problem
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.22/12448 |
Resumo: | We consider the problem of assigning a team of autonomous robots to target locations in the context of a disaster management scenario while optimizing several objectives. This problem can be cast as a multiple traveling salesman problem, where several robots must visit designated locations. This paper provides an analytical hierarchy process (AHP)-based approach to this problem, while minimizing three objectives: the total traveled distance, the maximum tour, and the deviation rate. The AHP-based approach involves three phases. In the first phase, we use the AHP process to define a specific weight for each objective. The second phase consists in allocating the available targets, wherein we define and use three approaches: market-based, robot and task mean allocation-based, and balanced-based. Finally, the third phase involves the improvement in the solutions generated in the second phase. To validate the efficiency of the AHP-based approach, we used MATLAB to conduct an extensive comparative simulation study with other algorithms reported in the literature. The performance comparison of the three approaches shows a gap between the market-based approach and the other two approaches of up to 30%. Further, the results show that the AHP-based approach provides a better balance between the objectives, as compared to other state-of-the-art approaches. In particular, we observed an improvement in the total traveled distance when using the AHP-based approach in comparison with the distance traveled when using a clustering-based approach. |
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An Analytical Hierarchy Process-Based Approach to Solve the Multi-Objective Multiple Traveling Salesman ProblemAssignmentMTSPMultiple depotsMulti-objective problemAHPWe consider the problem of assigning a team of autonomous robots to target locations in the context of a disaster management scenario while optimizing several objectives. This problem can be cast as a multiple traveling salesman problem, where several robots must visit designated locations. This paper provides an analytical hierarchy process (AHP)-based approach to this problem, while minimizing three objectives: the total traveled distance, the maximum tour, and the deviation rate. The AHP-based approach involves three phases. In the first phase, we use the AHP process to define a specific weight for each objective. The second phase consists in allocating the available targets, wherein we define and use three approaches: market-based, robot and task mean allocation-based, and balanced-based. Finally, the third phase involves the improvement in the solutions generated in the second phase. To validate the efficiency of the AHP-based approach, we used MATLAB to conduct an extensive comparative simulation study with other algorithms reported in the literature. The performance comparison of the three approaches shows a gap between the market-based approach and the other two approaches of up to 30%. Further, the results show that the AHP-based approach provides a better balance between the objectives, as compared to other state-of-the-art approaches. In particular, we observed an improvement in the total traveled distance when using the AHP-based approach in comparison with the distance traveled when using a clustering-based approach.Springer Berlin HeidelbergRepositório Científico do Instituto Politécnico do PortoTrigui, SaharCheikhrouhou, OmarKoubâa, AnisZarrad, AnisYoussef, Habib20182119-01-01T00:00:00Z2018-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/12448eng1861-278410.1007/s11370-018-0259-8metadata only accessinfo: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:RCAAP2023-03-13T12:54:27Zoai:recipp.ipp.pt:10400.22/12448Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:32:47.774929Repositório 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 |
An Analytical Hierarchy Process-Based Approach to Solve the Multi-Objective Multiple Traveling Salesman Problem |
title |
An Analytical Hierarchy Process-Based Approach to Solve the Multi-Objective Multiple Traveling Salesman Problem |
spellingShingle |
An Analytical Hierarchy Process-Based Approach to Solve the Multi-Objective Multiple Traveling Salesman Problem Trigui, Sahar Assignment MTSP Multiple depots Multi-objective problem AHP |
title_short |
An Analytical Hierarchy Process-Based Approach to Solve the Multi-Objective Multiple Traveling Salesman Problem |
title_full |
An Analytical Hierarchy Process-Based Approach to Solve the Multi-Objective Multiple Traveling Salesman Problem |
title_fullStr |
An Analytical Hierarchy Process-Based Approach to Solve the Multi-Objective Multiple Traveling Salesman Problem |
title_full_unstemmed |
An Analytical Hierarchy Process-Based Approach to Solve the Multi-Objective Multiple Traveling Salesman Problem |
title_sort |
An Analytical Hierarchy Process-Based Approach to Solve the Multi-Objective Multiple Traveling Salesman Problem |
author |
Trigui, Sahar |
author_facet |
Trigui, Sahar Cheikhrouhou, Omar Koubâa, Anis Zarrad, Anis Youssef, Habib |
author_role |
author |
author2 |
Cheikhrouhou, Omar Koubâa, Anis Zarrad, Anis Youssef, Habib |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico do Porto |
dc.contributor.author.fl_str_mv |
Trigui, Sahar Cheikhrouhou, Omar Koubâa, Anis Zarrad, Anis Youssef, Habib |
dc.subject.por.fl_str_mv |
Assignment MTSP Multiple depots Multi-objective problem AHP |
topic |
Assignment MTSP Multiple depots Multi-objective problem AHP |
description |
We consider the problem of assigning a team of autonomous robots to target locations in the context of a disaster management scenario while optimizing several objectives. This problem can be cast as a multiple traveling salesman problem, where several robots must visit designated locations. This paper provides an analytical hierarchy process (AHP)-based approach to this problem, while minimizing three objectives: the total traveled distance, the maximum tour, and the deviation rate. The AHP-based approach involves three phases. In the first phase, we use the AHP process to define a specific weight for each objective. The second phase consists in allocating the available targets, wherein we define and use three approaches: market-based, robot and task mean allocation-based, and balanced-based. Finally, the third phase involves the improvement in the solutions generated in the second phase. To validate the efficiency of the AHP-based approach, we used MATLAB to conduct an extensive comparative simulation study with other algorithms reported in the literature. The performance comparison of the three approaches shows a gap between the market-based approach and the other two approaches of up to 30%. Further, the results show that the AHP-based approach provides a better balance between the objectives, as compared to other state-of-the-art approaches. In particular, we observed an improvement in the total traveled distance when using the AHP-based approach in comparison with the distance traveled when using a clustering-based approach. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018 2018-01-01T00:00:00Z 2119-01-01T00:00:00Z |
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/10400.22/12448 |
url |
http://hdl.handle.net/10400.22/12448 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1861-2784 10.1007/s11370-018-0259-8 |
dc.rights.driver.fl_str_mv |
metadata only access info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
metadata only access |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Springer Berlin Heidelberg |
publisher.none.fl_str_mv |
Springer Berlin Heidelberg |
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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799131420314042368 |