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Abstract

The general nonlinear programming problem NLP is to find x so as to optimize

$$optimizef(x),x = ({{x}_{1}}, \ldots ,{{x}_{q}}) \in {{R}^{q}},$$

subject to p ≥0 inequalities:

$${{g}_{i}}(x) = 0,j = 0, \ldots ,p,$$

and m−p ≥0 equations:

$${{h}_{j}}(x)0,j = p + 1, \ldots ,m.$$

A traveler in quest of the divine asked the Master how to distinguish a true teacher from a false one when he got back to his own land.

Said the Master, ‘A good teacher offers practice; a bad one offers theories.’

‘But how shall I know good practice from bad?’

‘In the same way that the farmer knows good cultivation from bad?’

Anthony de Mello, One Minute Wisdom

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© 1996 Springer-Verlag Berlin Heidelberg

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Michalewicz, Z. (1996). Handling Constraints. In: Genetic Algorithms + Data Structures = Evolution Programs. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-03315-9_8

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  • DOI: https://doi.org/10.1007/978-3-662-03315-9_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-08233-7

  • Online ISBN: 978-3-662-03315-9

  • eBook Packages: Springer Book Archive

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