TY - JOUR
T1 - Speeding Up Dominance Checks in Multi-Objective Search
T2 - 17th International Symposium on Combinatorial Search, SoCS 2024
AU - Zhang, Han
AU - Salzman, Oren
AU - Felner, Ariel
AU - Satish Kumar, T. K.
AU - Ulloa, Carlos Hernández
AU - Koenig, Sven
N1 - Publisher Copyright:
© 2024, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2024/1/1
Y1 - 2024/1/1
N2 - In multi-objective search, given a directed graph where each edge is annotated with multiple cost metrics, a start state, and a goal state, we are interested in computing the Pareto frontier, i.e., the set of all undominated paths from the start state to the goal state. Almost all multi-objective search algorithms use dominance checks to determine if a search node can be pruned. Since dominance checks are performed in the inner loop of the multi-objective search, they are the most timeconsuming part of it. In this paper, we propose (1) two novel techniques to reduce duplicate dominance checks and (2) a simple data structure that enables more efficient dominance checks. Our experimental results show that combining our proposed techniques and data structure speeds up LTMOA*, a state-of-the-art multi-objective search algorithm, by up to an order of magnitude on road network instances.
AB - In multi-objective search, given a directed graph where each edge is annotated with multiple cost metrics, a start state, and a goal state, we are interested in computing the Pareto frontier, i.e., the set of all undominated paths from the start state to the goal state. Almost all multi-objective search algorithms use dominance checks to determine if a search node can be pruned. Since dominance checks are performed in the inner loop of the multi-objective search, they are the most timeconsuming part of it. In this paper, we propose (1) two novel techniques to reduce duplicate dominance checks and (2) a simple data structure that enables more efficient dominance checks. Our experimental results show that combining our proposed techniques and data structure speeds up LTMOA*, a state-of-the-art multi-objective search algorithm, by up to an order of magnitude on road network instances.
UR - http://www.scopus.com/inward/record.url?scp=85196636521&partnerID=8YFLogxK
U2 - 10.1609/socs.v17i1.31564
DO - 10.1609/socs.v17i1.31564
M3 - Conference article
AN - SCOPUS:85196636521
SN - 2832-9171
VL - 17
SP - 228
EP - 232
JO - The International Symposium on Combinatorial Search
JF - The International Symposium on Combinatorial Search
IS - 1
Y2 - 6 June 2024 through 8 June 2024
ER -