Bi-objective Search with Bi-directional A*
Saman Ahmadi, Guido Tack, Daniel Harabor, Philip Kilby

TL;DR
This paper introduces BOBA*, a bi-directional, parallel bi-objective A* algorithm with heuristics, significantly improving solution times for large bi-objective search problems across diverse benchmarks.
Contribution
It develops a novel bi-directional, parallel variant of BOA* with heuristics, achieving substantial speed-ups over existing methods.
Findings
BOBA* solves all benchmark cases within time limits.
BOBA* outperforms BOA*, bi-objective Dijkstra, and bi-directional bi-objective Dijkstra.
Average runtime improvement is fivefold.
Abstract
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.
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