Bounded-Suboptimal Weight-Constrained Shortest-Path Search via Efficient Representation of Paths

Han Zhang, Oren Salzman, Ariel Felner, T. K.Satish Kumar, Sven Koenig

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

Abstract

In the Weight-Constrained Shortest-Path (WCSP) problem, given a graph in which each edge is annotated with a cost and a weight, a start state, and a goal state, the task is to compute a minimum-cost path from the start state to the goal state with weight no larger than a given weight limit. While most existing works have focused on solving the WCSP problem optimally, many real-world situations admit a trade-off between efficiency and a suboptimality bound for the path cost. In this paper, we propose the bounded-suboptimal WCSP algorithm WC-A*pex, which is built on the state-of-the-art approximate bi-objective search algorithm A*pex. WC-A*pex uses an approximate representation of paths with similar costs and weights to compute a (1+ε)-suboptimal path, for a given ε. During its search, WC-A*pex avoids storing all paths explicitly and thereby reduces the search effort while still retaining its (1 + ε)-suboptimality bound. On benchmark road networks, our experimental results show that WC-A*pex with ε = 0.01 (i.e., with a guaranteed suboptimality of at most 1%) achieves a speed-up of up to an order of magnitude over WC-A*, a state-of-the-art WCSP algorithm, and its bounded-suboptimal variant.

Original languageEnglish
Title of host publicationProceedings of the 34th International Conference on Automated Planning and Scheduling, ICAPS 2024
EditorsSara Bernardini, Christian Muise
PublisherAssociation for the Advancement of Artificial Intelligence
Pages680-688
Number of pages9
ISBN (Electronic)9781577358893
DOIs
StatePublished - 30 May 2024
Externally publishedYes
Event34th International Conference on Automated Planning and Scheduling, ICAPS 2024 - Banaff, Canada
Duration: 1 Jun 20246 Jun 2024

Publication series

NameProceedings International Conference on Automated Planning and Scheduling, ICAPS
Volume34
ISSN (Print)2334-0835
ISSN (Electronic)2334-0843

Conference

Conference34th International Conference on Automated Planning and Scheduling, ICAPS 2024
Country/TerritoryCanada
CityBanaff
Period1/06/246/06/24

Bibliographical note

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

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