Bi-objective Search with Bi-directional A*
This work addresses the problem of efficient bi-objective search for applications like transport planning or energy control, representing an incremental improvement over existing methods.
The paper tackled the bi-objective search problem by developing a bi-directional and parallel variant of BOA* with speed-up heuristics, resulting in an average runtime improvement of a factor of five over state-of-the-art methods on 1,000 benchmark cases.
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.