Heuristic-Search Approaches for the Multi-Objective Shortest-Path Problem: Progress and Research Opportunities

Oren Salzman, Ariel Felner, Carlos Hernandez, Han Zhang, Shao Hung Chan, Sven Koenig

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

7 Scopus citations

Abstract

In the multi-objective shortest-path problem we are interested in computing a path, or a set of paths that simultaneously balance multiple cost functions. This problem is important for a diverse range of applications such as transporting hazardous materials considering travel distance and risk. This family of problems is not new with results dating back to the 1970's. Nevertheless, the significant progress made in the field of heuristic search resulted in a new and growing interest in the sub-field of multi-objective search. Consequently, in this paper we review the fundamental problems and techniques common to most algorithms and provide a general overview of the field. We then continue to describe recent work with an emphasis on new challenges that emerged and the resulting research opportunities.

Original languageEnglish
Title of host publicationProceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
EditorsEdith Elkind
PublisherInternational Joint Conferences on Artificial Intelligence
Pages6759-6768
Number of pages10
ISBN (Electronic)9781956792034
StatePublished - 2023
Externally publishedYes
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
ISSN (Print)1045-0823

Conference

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

Bibliographical note

Publisher Copyright:
© 2023 International Joint Conferences on Artificial Intelligence. All rights reserved.

Funding

This research was supported by the United States-Israel Bi-national Science Foundation (BSF) grants no. 2019703 and 2021643 and by the Israeli Ministry of Science & Technology grants No. 3-16079 and 3-17385. The research at the University of Southern California was supported by the National Science Foundation (NSF) under grant number 2121028. The research at Universidad San Sebastián was supported by the National Center for Artificial Intelligence CENIA FB210017, Basal ANID, and the Centro Ciencia & Vida, FB210008, Financiamiento Basal ANID. This research was supported by the United States-Israel Binational Science Foundation (BSF) grants no. 2019703 and 2021643 and by the Israeli Ministry of Science & Technology grants No. 3-16079 and 3-17385. The research at the University of Southern California was supported by the National Science Foundation (NSF) under grant number 2121028. The research at Universidad San Sebastián was supported by the National Center for Artificial Intelligence CENIA FB210017, Basal ANID, and the Centro Ciencia & Vida, FB210008, Fi-nanciamiento Basal ANID.

FundersFunder number
Centro Ciencia & VidaFB210008
Financiamiento Basal ANID
National Center for Artificial Intelligence CENIAFB210017
United States–Israel Bi-National Science Foundation
National Science Foundation2121028
United States-Israel Binational Science Foundation2019703, 2021643
Ministry of science and technology, Israel3-16079, 3-17385

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