Multi-objective Search via Lazy and Efficient Dominance Checks

Carlos Hernández, William Yeoh, Jorge A. Baier, Ariel Felner, Oren Salzman, Han Zhang, Shao Hung Chan, Sven Koenig

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Multi-objective search can be used to model many real-world problems that require finding Pareto-optimal paths from a specified start state to a specified goal state, while considering different cost metrics such as distance, time, and fuel. The performance of multi-objective search can be improved by making dominance checking-an operation necessary to determine whether or not a path dominates another-more efficient. This was shown in practice by BOA*, a state-of-the-art bi-objective search algorithm, which outperforms previously existing bi-objective search algorithms in part because it adopts a lazy approach towards dominance checking. EMOA*, a recent multi-objective search algorithm, generalizes BOA* to more-than-two objectives using AVL trees for dominance checking. In this paper, we first propose Linear-Time Multi-Objective A* (LTMOA*), a multi-objective search algorithm that implements more efficient dominance checking than EMOA* using simple data structures like arrays. We then propose LazyLTMOA*, which employs a lazier approach by removing dominance checking during node generation. Our experimental results show that LazyLTMOA* outperforms EMOA* by up to an order of magnitude in terms of runtime.

Original languageEnglish
Title of host publicationProceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
EditorsEdith Elkind
Pages7223-7230
Number of pages8
ISBN (Electronic)9781956792034
StatePublished - 1 Jan 2023
Event32nd International Joint Conference on Artificial Intelligence, IJCAI 2023 - Macao, China
Duration: 19 Aug 202325 Aug 2023

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
Volume2023-August

Conference

Conference32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
Country/TerritoryChina
CityMacao
Period19/08/2325/08/23

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Multi-objective Search via Lazy and Efficient Dominance Checks'. Together they form a unique fingerprint.

Cite this