 |
Conference papers
Bidirectional Preference-based Search for Multiobjective State Space Graph Problems
Abstract : In multiobjective state space graph problems, each solution-path is evaluated by a cost vector. These cost vectors can be partially or completely ordered using a preference relation compatible with Pareto dominance. In this context, multiobjective preference-based search (MOPBS) aims at computing the preferred feasible solutions according to a predefined preference model, these preferred solutions being a subset (possibly the entire set) of Pareto optima. Standard algorithms for MOPBS perform a unidirectional search developing the search tree forward from the initial state to a goal state. Instead, in this paper, we focus on bidirectional search algorithms developing simultaneously one forward and one backward search tree. Although bi-directional search has been tested in various single objective problems, its efficiency in a multiobjective setting has never been studied. In this paper, we present several implementations of bidirectional preference-based search convenient for the multiobjective case and investigate their efficiency.
Cited literature [27 references]
https://hal.archives-ouvertes.fr/hal-01388530
Contributor : Christine Okret-Manville <>
Submitted on : Wednesday, December 14, 2016 - 4:26:59 PM
Last modification on : Thursday, January 21, 2021 - 11:38:01 AM
Long-term archiving on: : Wednesday, March 15, 2017 - 1:46:49 PM
Contributor : Christine Okret-Manville <>
Submitted on : Wednesday, December 14, 2016 - 4:26:59 PM
Last modification on : Thursday, January 21, 2021 - 11:38:01 AM
Long-term archiving on: : Wednesday, March 15, 2017 - 1:46:49 PM
File
7238-30162-1-PB.pdf
Publisher files allowed on an open archive