Efficient Set Dominance Checks in Multi-Objective Shortest-Path Algorithms via Vectorized Operations

Carlos Hernández Ulloa, Han Zhang, Sven Koenig, Ariel Felner, Oren Salzman

Research output: Contribution to journalConference articlepeer-review


In the multi-objective shortest-path problem (MOSP) we are interested in finding paths between two vertices of a graph while considering multiple objectives. A key procedure, which dominates the running time of many state-ofthe-art (SOTA) algorithms for MOSP is set dominance checks (SDC). In SDC, we are given a set X of N-dimensional tuples and a new N-dimensional tuple p and we need to determine whether there exists a tuple q ∈ X such that q dominates p (i.e., if every element in q is lower or equal than the corresponding element in p). In this work, we offer a simple-yet-effective approach to perform SDC in a parallel manner, an approach that can be seamlessly integrated with most SOTA MOSP algorithms. Specifically, by storing states in memory dimension-wise and not state-wise, we can exploit vectorized operations offered by “Single Instruction/Multiple Data” (SIMD) instructions to efficiently perform SDC on ubiquitous consumer CPUs. Integrating our approach for SDC allows to dramatically improve the runtime of existing MOSP algorithms.

Original languageEnglish
Pages (from-to)208-212
Number of pages5
JournalThe International Symposium on Combinatorial Search
Issue number1
StatePublished - 2024
Externally publishedYes
Event17th International Symposium on Combinatorial Search, SoCS 2024 - Kananaskis, Canada
Duration: 6 Jun 20248 Jun 2024

Bibliographical note

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© 2024, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.


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