An Introduction to Genetic Algorithms for Numerical Optimization
The paper is organized as follows. Section 1 establishes the distinction between local and global optimization and the meaning of performance measures in the context of global optimization. Section 2 introduces the general idea of a genetic algorithm, as inspired from the biological process of evolution by means of natural selection. Section 3 provides a detailed comparison of the performance of three genetic algorithm-based optimization schemes against iterated hill climbing using the simplex method. Section 4 describes in full detail the use of a genetic algorithm to solve a real data modeling problem, namely the determination of orbital elements of a binary star system from observed radial velocities. The paper closes in section 5 with reflections on matters of a somewhat more philosophical nature, and includes a list of suggested further readings.
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http://n2t.net/ark:/85065/d74j0dj1
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2016-01-01T00:00:00Z
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2002-01-01T00:00:00Z
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