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Numerous techniques exist in science for tackling large-scale optimisation problems. In many instances, scientists must identify the best solution from within a pool containing millions of possible solutions. Evolutionary algorithms are particularly adept at handling this sort of optimisation and their advantages often become more marked as the size of the search space grows. This chapter introduces...
This contribution focuses upon the application of evolutionary algorithms to the nondeterministic polynomial hard problem of global cluster geometry optimization. The first years of method development in this area are sketched briefly; followed by a characterization of the current state of the art by an overview of recent application work. Strengths and weaknesses of this approach are highlighted...
Evolutionary algorithms are finding increasing use in the study of a wide range of different types of diffraction data. In this chapter, we review recent applications of evolutionary algorithms to study a variety of structural problems. Examples range from the study of disordered materials by analysis of diffuse scattering data to molecular replacement techniques in biological crystallography. However,...
Methods, evolutionary and systematic search approaches, and applications of crystal structure prediction of closest-packed and framework materials are reviewed. Strategies include developing better cost functions, used to assess the quality of the candidate structures that are generated, and ways to reduce the set of candidate structures to be assessed. The crystallographic coordinates for new materials,...
Evolutionary algorithms have been widely adopted for solving many of the complex tasks involved in drug design. Here, applications to two different tasks are reviewed: combinatorial library design and deriving quantitative structure-activity relationship (QSAR) models. Combinatorial libraries are the result of combinatorial synthesis whereby robotics is used to synthesise large numbers of compounds...
Predicting the three-dimensional structure of proteins from their linear sequence is one of the major challenges in modern biology. It is widely recognized that one of the major obstacles in addressing this question is that the “standard” computational approaches are not powerful enough to search for the correct structure in the huge conformational space. Genetic algorithms, a cooperative computational...
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