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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.
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Contributor : Christine Okret-Manville <>
Submitted on : Wednesday, December 14, 2016 - 4:26:59 PM
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  • HAL Id : hal-01388530, version 1


Lucie Galand, Anisse Ismaili, Patrice Perny, Olivier Spanjaard. Bidirectional Preference-based Search for Multiobjective State Space Graph Problems. 6th Annual Symposium on Combinatorial Search (SoCS 2013), Jul 2013, Leavenworth, Washington, United States. pp.80-88. ⟨hal-01388530⟩



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