Abstract
Distance geometry problems (DGP) arise from the need to position entities in the Euclidean K-space given some of their respective distances. Entities may be atoms (molecular distance geometry), wireless sensors (sensor network localization), or abstract vertices of a graph (graph drawing). In the context of molecular distance geometry, the distances are usually known because of chemical properties and nuclear magnetic resonance experiments; sensor networks can estimate their relative distance by recording the power loss during a two-way exchange; finally, when drawing graphs in two or three dimensions, the graph to be drawn is given, and therefore distances between vertices can be computed. DGPs involve a search in a continuous Euclidean space, but sometimes the problem structure helps reduce the search to a discrete set of points. In this paper we survey some continuous and discrete methods for solving some problems of molecular distance geometry. © 2010 The Authors. International Transactions in Operational Research. © 2010 International Federation of Operational Research Societies.
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Liberti, L., Lavor, C., Mucherino, A., & Maculan, N. (2011). Molecular distance geometry methods: From continuous to discrete. International Transactions in Operational Research, 18(1), 33–51. https://doi.org/10.1111/j.1475-3995.2009.00757.x
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