Bi-Objective Search with Bi-Directional A*

Authors Saman Ahmadi , Guido Tack, Daniel Harabor, Philip Kilby

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Author Details

Saman Ahmadi
  • Department of Data Science and AI, Monash University, Clayton, Australia
  • CSIRO Data61, Canberra, Australia
Guido Tack
  • Department of Data Science and AI, Monash University, Clayton, Australia
Daniel Harabor
  • Department of Data Science and AI, Monash University, Clayton, Australia
Philip Kilby
  • CSIRO Data61, Canberra, Australia

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Saman Ahmadi, Guido Tack, Daniel Harabor, and Philip Kilby. Bi-Objective Search with Bi-Directional A*. In 29th Annual European Symposium on Algorithms (ESA 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 204, pp. 3:1-3:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


Bi-objective search is a well-known algorithmic problem, concerned with finding a set of optimal solutions in a two-dimensional domain. This problem has a wide variety of applications such as planning in transport systems or optimal control in energy systems. Recently, bi-objective A*-based search (BOA*) has shown state-of-the-art performance in large networks. This paper develops a bi-directional and parallel variant of BOA*, enriched with several speed-up heuristics. Our experimental results on 1,000 benchmark cases show that our bi-directional A* algorithm for bi-objective search (BOBA*) can optimally solve all of the benchmark cases within the time limit, outperforming the state of the art BOA*, bi-objective Dijkstra and bi-directional bi-objective Dijkstra by an average runtime improvement of a factor of five over all of the benchmark instances.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Search methodologies
  • Theory of computation → Shortest paths
  • Bi-objective search
  • heuristic search
  • shortest path problem


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