Convex programming;
Interior point methods;
Linear ascending constraints;
ALGORITHMS;
D O I:
10.1016/j.orl.2020.04.001
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:
Efficient methods for convex resource allocation problems usually exploit algebraic properties of the objective function. For problems with nested constraints, we show that constraint sparsity structure alone allows rapid solution with a general interior point method. The key is a special-purpose linear system solver requiring only linear time in the problem dimensions. Computational tests show that this approach outperforms the previous best algebraically specialized methods. (C) 2020 Elsevier B.V. All rights reserved.