Fast scaling algorithms for M-convex function minimization with application to the resource allocation problem

被引:22
|
作者
Shioura, A [1 ]
机构
[1] Tohoku Univ, Grad Sch Informat Sci, Sendai, Miyagi 9808579, Japan
关键词
discrete optimization; convex function; minimization; base polyhedron; resource allocation;
D O I
10.1016/S0166-218X(03)00255-5
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
M-convex functions, introduced by Murota (Adv. Math. 124 (1996) 272; Math. Prog. 83 (1998) 313), enjoy various desirable properties as "discrete convex functions." In this paper, we propose two new polynomial-time scaling algorithms for the minimization of an M-convex function. Both algorithms apply a scaling technique to a greedy algorithm for M-convex function minimization, and run as fast as the previous minimization algorithms. We also specialize our scaling algorithms for the resource allocation problem which is a special case of M-convex function minimization. (C) 2003 Elsevier B.V. All rights reserved.
引用
收藏
页码:303 / 316
页数:14
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