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Constraint programming approaches for the discretizable molecular distance geometry problem
Networks ( IF 2.1 ) Pub Date : 2021-07-01 , DOI: 10.1002/net.22068
Moira MacNeil 1 , Merve Bodur 1
Affiliation  

The Distance Geometry Problem (DGP) seeks to find positions for a set of points in geometric space when some distances between pairs of these points are known. The so-called discretization assumptions allow us to discretize the search space of DGP instances. In this paper, we focus on a key subclass of DGP, namely the Discretizable Molecular DGP, and study its associated graph vertex ordering problem, the Contiguous Trilateration Ordering Problem (CTOP), which helps solve DGP. We propose the first constraint programming formulations for CTOP, as well as a set of checks for proving infeasibility, domain reduction techniques, symmetry breaking constraints, and valid inequalities. Our computational results on random and pseudo-protein instances indicate that our formulations outperform the state-of-the-art integer programming formulations.

中文翻译:

离散分子距离几何问题的约束规划方法

距离几何问题 (DGP) 试图在几何空间中的一组点的位置已知时,这些点对之间的距离是已知的。所谓的离散化假设允许我们离散化 DGP 实例的搜索空间。在本文中,我们关注 DGP 的一个关键子类,即离散分子 DGP,并研究其相关的图顶点排序问题,即连续三边排序问题(CTOP),这有助于解决 DGP。我们为 CTOP 提出了第一个约束规划公式,以及一组用于证明不可行性、域缩减技术、对称破坏约束和有效不等式的检查。我们对随机和伪蛋白质实例的计算结果表明,我们的公式优于最先进的整数规划公式。
更新日期:2021-07-01
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