Publicação
A new ranking path algorithm for the multi-objective shortest path problem
| Resumo: | In this paper, we present a new algorithm for solving the multi-objective shortest path problem (MSPP) which consists of finding all the non-dominated paths between two nodes s and t (ND s-t paths), on a network where a multiple criteria function is defined over the set of arcs. The main feature of the algorithm is that, contrarily to the previous most efficient approaches for the MSPP, not all of the ND sub-paths on the network need to be found. Additionally, the algorithm fully exploits the fact that ND s-t paths are generated at a very early stage of the ranking procedure. The computational experience reported in the paper shows that, for large size general type networks, the new algorithm clearly outperforms the labelling approach. |
|---|---|
| Autores principais: | Paixão, José Manuel |
| Outros Autores: | Santos, José Luis |
| Assunto: | Multiple objective programming Combinatorial optimization Shortest path problem Ranking algorithm Labelling algorithm Non-dominated path |
| Ano: | 2008 |
| País: | Portugal |
| Tipo de documento: | preprint |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Coimbra |
| Idioma: | inglês |
| Origem: | Estudo Geral - Universidade de Coimbra |
| Resumo: | In this paper, we present a new algorithm for solving the multi-objective shortest path problem (MSPP) which consists of finding all the non-dominated paths between two nodes s and t (ND s-t paths), on a network where a multiple criteria function is defined over the set of arcs. The main feature of the algorithm is that, contrarily to the previous most efficient approaches for the MSPP, not all of the ND sub-paths on the network need to be found. Additionally, the algorithm fully exploits the fact that ND s-t paths are generated at a very early stage of the ranking procedure. The computational experience reported in the paper shows that, for large size general type networks, the new algorithm clearly outperforms the labelling approach. |
|---|
Atividades financiadas
Não foram encontrados projetos financiados.