A push-relabel framework for submodular function minimization and applications to parametric optimization

被引:69
作者
Fleischer, L
Iwata, S
机构
[1] Carnegie Mellon Univ, Grad Sch Ind Adm, Pittsburgh, PA 15213 USA
[2] Univ Tokyo, Grad Sch Informat Sci & Technol, Tokyo 1138656, Japan
关键词
submodular function; parametric optimization;
D O I
10.1016/S0166-218X(02)00458-4
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Recently, the first combinatorial strongly polynomial algorithms for submodular function minimization have been devised independently by Iwata, Fleischer, and Fujishige and by Schrijver. In this paper, we improve the running time of Schrijver's algorithm by designing a push-relabel framework for submodular function minimization (SFM). We also extend this algorithm to carry out parametric minimization for a strong map sequence of submodular functions in the same asymptotic running time as a single SFM. Applications include an efficient algorithm for finding a lexicographically optimal base. (C) 2003 Elsevier B.V. All rights reserved.
引用
收藏
页码:311 / 322
页数:12
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