Direct-space techniques genetic algorithms

Direct Methods Direct-Space Techniques Patterson Methods Monte Carlo Simulated Annealing Genetic Algorithm Degree of Freedom Cost Function... 

The main focus of this article is the application of genetic algorithm (GA) techniques to solve crystal structures of molecular materials directly from powder diffraction data (Sect. 2). In this application, the aim is to find the set of atomic positions (x,y, z) [knowing the unit cell a, b, c, a, y and space group S] that give the optimal representation of an experimental powder diffraction pattern. In such applications, the population in the evolutionary algorithm com-... 

As an alternative to RSM, simulation responses can be used directly to explore the sample space of control variables. To do so, a lot of combinatorial optimization approaches were adapted for simulation optimization. In general, there are four main classes of methods that have shown a particular applicability in (multi-objective) simulation optimization Meta-heuristics, gradient-based procedures, random search, and sample path optimization. Of particular interest are meta-heuristics as they have shown a good performance for a wide range of combinatorial optimization approaches. Therefore, commercial simulation software primarily uses these techniques to incorporate simulation optimization routines. Among meta-heuristics, tabu search, scatter search, and genetic algorithms are most widely used. Table 4.13 provides an overview on aU aforementioned techniques. 

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