The ant colony optimization meta-heuristic
New ideas in optimization
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Journal of Global Optimization
Computers and Operations Research
On a discretizable subclass of instances of the molecular distance geometry problem
Proceedings of the 2009 ACM symposium on Applied Computing
MD-jeep: an implementation of a branch and prune algorithm for distance geometry problems
ICMS'10 Proceedings of the Third international congress conference on Mathematical software
On the computation of protein backbones by using artificial backbones of hydrogens
Journal of Global Optimization
Influence of pruning devices on the solution of molecular distance geometry problems
SEA'11 Proceedings of the 10th international conference on Experimental algorithms
A note on teaching-learning-based optimization algorithm
Information Sciences: an International Journal
The discretizable molecular distance geometry problem
Computational Optimization and Applications
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We consider the Discretizable Molecular Distance Geometry Problem (DMDGP), which consists in a subclass of instances of the distance geometry problem related to molecular conformations for which a combinatorial reformulation can be supplied. We investigate the performances of two different algorithms for solving the DMDGP. The first one is the Branch and Prune (BP) algorithm, an exact algorithm that is strongly based on the structure of the combinatorial problem. The second one is the Monkey Search (MS) algorithm, a meta-heuristic algorithm that is inspired by the behavior of a monkey climbing trees in search for food supplies, and that exploits ideas and strategies from other meta-heuristic searches, such Genetic Algorithms, Differential Evolution, and so on. The comparison between the two algorithms is performed on a set of instances related to protein conformations. The used instances simulate data obtained from the Nuclear Magnetic Resonance (NMR), because the typical distances provided by NMR are considered and a predetermined number of wrong distances are included.