Application of the ant colony optimization in the resolution of the bridge inspection routing problem

Shan Huen Huang, Ying Hua Huang, Carola A. Blazquez, Germán Paredes-Belmar

Resultado de la investigación: Article

6 Citas (Scopus)

Resumen

This paper presents a study on routing problems associated with bridge inspection tasks. In the evaluated problems, a bridge inspection team must depart from the depot, visit bridges, and eventually return to the depot. Since a single inspection team may require several days to perform this task, the inspectors must find lodging accommodations during the inspection period. This problem becomes a special type of vehicle routing problem (VRP). Two types of scenarios are established for the bridge inspection problem. In the first scenario, only one inspection team is evaluated, and in the second scenario, more than one inspection team and a specific inspection duration are assessed. The goal of this study is to determine optimal routes and to find accommodations that minimize the total inspection cost, including the travel and lodging costs. The problem is solved using an ant colony optimization (ACO) algorithm. In addition, a local search method is proposed for improving the quality of the solutions. Three benchmark datasets are generated to estimate the performance of the proposed method. First, a combination of the ACO parameter values that yielded overall good results is determined, and subsequently the proposed method is applied to the benchmarks. The results indicate that the proposed process yield promising solutions within a reasonable time frame.

Idioma originalEnglish
Páginas (desde-hasta)443-461
Número de páginas19
PublicaciónApplied Soft Computing Journal
Volumen65
DOI
EstadoPublished - 1 abr 2018

Huella dactilar

Ant colony optimization
Inspection
Vehicle routing
Costs

ASJC Scopus subject areas

  • Software

Citar esto

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abstract = "This paper presents a study on routing problems associated with bridge inspection tasks. In the evaluated problems, a bridge inspection team must depart from the depot, visit bridges, and eventually return to the depot. Since a single inspection team may require several days to perform this task, the inspectors must find lodging accommodations during the inspection period. This problem becomes a special type of vehicle routing problem (VRP). Two types of scenarios are established for the bridge inspection problem. In the first scenario, only one inspection team is evaluated, and in the second scenario, more than one inspection team and a specific inspection duration are assessed. The goal of this study is to determine optimal routes and to find accommodations that minimize the total inspection cost, including the travel and lodging costs. The problem is solved using an ant colony optimization (ACO) algorithm. In addition, a local search method is proposed for improving the quality of the solutions. Three benchmark datasets are generated to estimate the performance of the proposed method. First, a combination of the ACO parameter values that yielded overall good results is determined, and subsequently the proposed method is applied to the benchmarks. The results indicate that the proposed process yield promising solutions within a reasonable time frame.",
keywords = "Ant colony optimization, Bridge inspection, Routing problem",
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AU - Huang, Shan Huen

AU - Huang, Ying Hua

AU - Blazquez, Carola A.

AU - Paredes-Belmar, Germán

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N2 - This paper presents a study on routing problems associated with bridge inspection tasks. In the evaluated problems, a bridge inspection team must depart from the depot, visit bridges, and eventually return to the depot. Since a single inspection team may require several days to perform this task, the inspectors must find lodging accommodations during the inspection period. This problem becomes a special type of vehicle routing problem (VRP). Two types of scenarios are established for the bridge inspection problem. In the first scenario, only one inspection team is evaluated, and in the second scenario, more than one inspection team and a specific inspection duration are assessed. The goal of this study is to determine optimal routes and to find accommodations that minimize the total inspection cost, including the travel and lodging costs. The problem is solved using an ant colony optimization (ACO) algorithm. In addition, a local search method is proposed for improving the quality of the solutions. Three benchmark datasets are generated to estimate the performance of the proposed method. First, a combination of the ACO parameter values that yielded overall good results is determined, and subsequently the proposed method is applied to the benchmarks. The results indicate that the proposed process yield promising solutions within a reasonable time frame.

AB - This paper presents a study on routing problems associated with bridge inspection tasks. In the evaluated problems, a bridge inspection team must depart from the depot, visit bridges, and eventually return to the depot. Since a single inspection team may require several days to perform this task, the inspectors must find lodging accommodations during the inspection period. This problem becomes a special type of vehicle routing problem (VRP). Two types of scenarios are established for the bridge inspection problem. In the first scenario, only one inspection team is evaluated, and in the second scenario, more than one inspection team and a specific inspection duration are assessed. The goal of this study is to determine optimal routes and to find accommodations that minimize the total inspection cost, including the travel and lodging costs. The problem is solved using an ant colony optimization (ACO) algorithm. In addition, a local search method is proposed for improving the quality of the solutions. Three benchmark datasets are generated to estimate the performance of the proposed method. First, a combination of the ACO parameter values that yielded overall good results is determined, and subsequently the proposed method is applied to the benchmarks. The results indicate that the proposed process yield promising solutions within a reasonable time frame.

KW - Ant colony optimization

KW - Bridge inspection

KW - Routing problem

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