Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Adaptive global optimization with local search
Adaptive global optimization with local search
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
| Hi-index | 0.00 |
The present paper attempts to employ hybrid genetic algorithms (GAs) to solve the flexible-ligand docking problem i.e. predicting the binding conformation of a flexible ligand molecule into a rigid protein. Our hybrid GA scheme uses the concept of Lamarckian genetics to perform a local search about an individual, followed by replacing it with a better solution found in its neighborhood. Two local search schemes have been investigated and their performance relative to the standard GA have been compared. Preliminary results obtained on a set of three protein-ligand complexes are encouraging.