A Distributed Method for Optimal Capacity Reservation

被引：3

作者：

Moehle, Nicholas ^{[1
]}

Shen, Xinyue ^{[2
]}

Luo, Zhi-Quan ^{[3
]}

Boyd, Stephen ^{[4
]}

机构：

[1] Stanford Univ, Dept Mech Engn, Stanford, CA 94305 USA

[2] Tsinghua Univ, Dept Elect Engn, Beijing, Peoples R China

[3] Univ Minnesota, Elect & Comp Engn, St Paul, MN USA

[4] Stanford Univ, Dept Elect Engn, Stanford, CA 94305 USA

来源：

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS | 2019年 / 182卷 / 03期

关键词：

Convex optimization; Network flow; ADMM; Robust optimization; ROBUST NETWORK DESIGN;

D O I：

10.1007/s10957-019-01528-5

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

We consider the problem of reserving link capacity in a network in such a way that any of a given set of flow scenarios can be supported. In the optimal capacity reservation problem, we choose the reserved link capacities to minimize the reservation cost. This problem reduces to a large linear program, with the number of variables and constraints on the order of the number of links times the number of scenarios. We develop a scalable, distributed algorithm for the problem that alternates between solving (in parallel) one-flow problem per scenario, and coordination steps, which connect the individual flows and the reservation capacities.

引用

页码：1130 / 1149

页数：20

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