TY - GEN
T1 - Heuristic-Search Approaches for the Multi-Objective Shortest-Path Problem
T2 - 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
AU - Salzman, Oren
AU - Felner, Ariel
AU - Hernandez, Carlos
AU - Zhang, Han
AU - Chan, Shao Hung
AU - Koenig, Sven
N1 - Funding Information:
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.
Funding Information:
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.
Publisher Copyright:
© 2023 International Joint Conferences on Artificial Intelligence. All rights reserved.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85170362407&partnerID=8YFLogxK
U2 - 10.24963/ijcai.2023/661
DO - 10.24963/ijcai.2023/661
M3 - Conference contribution
AN - SCOPUS:85170362407
SN - 9781956792034
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 6759
EP - 6768
BT - Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
A2 - Elkind, Edith
PB - International Joint Conferences on Artificial Intelligence
Y2 - 19 August 2023 through 25 August 2023
ER -