Solving large-scale linear multicommodity flow problems with an active set strategy and Proximal-ACCPM
成果类型：
Article
署名作者：
Babonneau, F; du Merle, O; Vial, JP
署名单位：
University of Geneva
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.1050.0262
发表日期：
2006
页码：
184-197
关键词：
摘要：
In this paper, we propose to solve the linear multicommodity flow problem using a partial Lagrangian relaxation. The relaxation is restricted to the set of arcs that are likely to be saturated at the optimum. This set is itself approximated by an active set strategy. The partial Lagrangian dual is solved with Proximal-ACCPM, a variant of the analytic center cutting-plane method. The new approach makes it possible to solve huge problems when few arcs are saturated at the optimum, as appears to be the case in many practical problems.