Abstract
Given a set of radio broadcast programs, the radio broadcast scheduling problem is to allocate a set of devices to transmit the programs to achieve the optimal sound quality. In this article, we propose a complete algorithm to solve the problem, which is based on a branch-and-bound (BnB) algorithm. We formulate the problem with a new model, called constrained maximum weighted bipartite matching (CMBM), i.e., the maximum matching problem on a weighted bipartite graph with constraints. For the reduced matching problem, we propose a novel BnB algorithm by introducing three new strategies, including the highest quality first, the least conflict first and the more edge first. We also establish an upper bound estimating function for pruning the search space of the algorithm. The experimental results show that our new algorithm can quickly find the optimal solution for the radio broadcast scheduling problem at small scales, and has higher scalability for the problems at large scales than the existing complete algorithm.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Li Y, Nie F, Huang H, et al. Large-scale multi-view spectral clustering via bipartite graph. In: Proceedings of the 29th AAAI Conference on Artificial Intelligence, Austin, 2015. 2750–2756
Gu T L, Chang L, Xu Z B. A novel symbolic algorithm for maximum weighted matching in bipartite graphs. Int J Commun Netw Syst Sci, 2011, 4: 111–121
Beale S. Using branch-and-bound with constraint satisfaction in optimization problems. In: Proceedings of the 14th National Conference on Artificial Intelligence and 9th Innovative Applications of Artificial Intelligence Conference, Providence, 1997. 209–214
Lelis L H S, Otten L, Dechter R. Predicting the size of depth-first branch and bound search trees. In: Proceedings of the 23rd International Joint Conference on Artificial Intelligence, Beijing, 2013
Zhan C, Xiao F. Coding based wireless broadcast scheduling in real time applications. J Network Comput Appl, 2016, 64: 194–203
Kuhn H W. The Hungarian method for the assignment problem. Naval Res Log, 1955, 2: 83–97
Munkres J. Algorithms for the assignment and transportation problems. J Soc Industrial Appl Math, 1957, 5: 32–38
Mitchell D G. A sat solver primer. Bull EATCS, 2005, 85: 112–132
Ma F, Gao X, Yin M, et al. Optimizing shortwave radio broadcast resource allocation via pseudo-boolean constraint solving and local search. In: Proceedings of the 22nd International Conference on Principles and Practice of Constraint Programming, Toulouse, 2016. 650–665
Pan L, Jin J, Gao X, et al. Integrating ILP and SMT for shortwave radio broadcast resource allocation and frequency assignment. In: Proceedings of the 23rd International Conference on Principles and Practice of Constraint Programming, Melbourne, 2017. 405–413
Li C M, Quan Z. An efficient branch-and-bound algorithm based on maxsat for the maximum clique problem. In: Proceedings of the 24th AAAI Conference on Artificial Intelligence, Atlanta, 2010
Acknowledgements
This work was supported by National Natural Science Foundation of China (Grant No. 61772503) and National Basic Research Program of China (Grant No. 2014CB340302).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Wang, S., Wu, T., Yao, Y. et al. Constrained maximum weighted bipartite matching: a novel approach to radio broadcast scheduling. Sci. China Inf. Sci. 62, 72102 (2019). https://doi.org/10.1007/s11432-017-9324-0
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11432-017-9324-0