@inproceedings{2914cdb585fa4fcabaf3e32fd096cd64,
title = "Suboptimal variants of the conflict-based search algorithm for the multi-agent pathfinding problem",
abstract = "The task in the multi-agent path finding problem (MAPF) is to find paths for multiple agents, each with a different start and goal position, such that agents do not collide. A successful optimal MAPF solver is the conflict-based search (CBS) algorithm. CBS is a two level algorithm where special conditions ensure it returns the optimal solution. Solving MAPF optimally is proven to be NP-hard, hence CBS and all other optimal solvers do not scale up. We propose several ways to relax the optimality conditions of CBS trading solution quality for runtime as well as bounded-suboptimal variants, where the returned solution is guaranteed to be within a constant factor from optimal solution cost. Experimental results show the benefits of our new approach; a massive reduction in running time is presented while sacrificing a minor loss in solution quality. Our new algorithms outperform other existing algorithms in most of the cases.",
author = "Max Barer and Guni Sharon and Roni Stern and Ariel Felner",
note = "Publisher Copyright: Copyright {\textcopyright} 2014.; 7th Annual Symposium on Combinatorial Search, SoCS 2014 ; Conference date: 15-08-2014 Through 17-08-2014",
year = "2014",
month = jan,
day = "1",
doi = "10.1609/socs.v5i1.18315",
language = "American English",
series = "Proceedings of the 7th Annual Symposium on Combinatorial Search, SoCS 2014",
pages = "19--27",
editor = "Stefan Edelkamp and Roman Bartak",
booktitle = "Proceedings of the 7th Annual Symposium on Combinatorial Search, SoCS 2014",
}