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Column generation decomposition with the degenerate constraints in the subproblem

机译:在子问题中具有退化约束的列生成分解

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In this paper, we propose a new Dantzig-Wolfe decomposition for degenerate linear programs with the non degenerate constraints in the master problem and the degenerate ones in the subproblem. We propose three algorithms. The first one, where some set of variables of the original problem are added to the master problem, corresponds to the Improved Primal Simplex algorithm (IPS) presented recently by Elhallaoui et al. [7]. In the second one, some extreme points of the subproblem are added as columns in the master problem. The third algorithm is a mixed implementation that adds some original variables and some extreme points of a subproblem to the master problem. Experimental results on some degenerate instances show that the proposed algorithms yield computational times that are reduced by an average factor ranging from 3.32 to 13.16 compared to the primal simplex of CPLEX.
机译:在本文中,我们为退化线性程序提出了一种新的Dantzig-Wolfe分解,该线性程序在主问题中具有非退化约束,在子问题中具有非退化约束。我们提出了三种算法。第一个将原始问题的某些变量集添加到主问题中,第一个对应于Elhallaoui等人最近提出的改进的原始单纯形算法(IPS)。 [7]。在第二篇中,将子问题的某些极端点作为列添加到主问题中。第三种算法是混合实现,它向母版问题添加了一些原始变量和子问题的某些极端点。在一些退化实例上的实验结果表明,与CPLEX的原始单纯形相比,所提出的算法产生的计算时间减少了3.32至13.16的平均因子。

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