lmaxRPCls: An Algorithm Utilizing Light Symmetry for Approximating maxRPC in Constraint Programming
- DOI
- 10.2991/caai-17.2017.87How to use a DOI?
- Keywords
- constraint programming; symmetry; maxRPC
- Abstract
Constraint satisfaction problem (CSP) can be widely applied in many areas. This paper investigates the maximum restricted path consistency algorithm. There is a large quantity of useless checks in the process of searching for a PC-support with the most popular algorithm lmaxRPC3rm. Since lmaxRPC3rm has to examine the whole domain of a variable to ascertain whether a PC-support exists. The efficiency of the search can be improved by eliminating such useless checks. Firstly, this paper analyses the features which accounts for the existence of these ineffective checks. And then, this paper discusses some methods of solving these problems. Afterwards, a new data structure is put forward to strengthen residual supports and weaken the use of multidirectionality to narrow the range of search. A new algorithm, lmaxRPCls, which exploits the results above is proposed and it is proved that lmaxRPCls is correct and complete. It is also proved that the time complexity of this new algorithm is better than that of lmaxRPC3rm. Experimental results show that lmaxRPCls performs better in most benchmark instances and it can improve the performance by 65% in the best case.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Zhiying Xu AU - Shihui Song AU - Zhanshan Li PY - 2017/06 DA - 2017/06 TI - lmaxRPCls: An Algorithm Utilizing Light Symmetry for Approximating maxRPC in Constraint Programming BT - Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017) PB - Atlantis Press SP - 382 EP - 385 SN - 1951-6851 UR - https://doi.org/10.2991/caai-17.2017.87 DO - 10.2991/caai-17.2017.87 ID - Xu2017/06 ER -