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Global Optimization of Membrane Processes

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For a number of years, researchers and engineers in many fields have reported the problem of obtaining multiple solutions while solving problems of nonlinear programming (NLP). Multiplicity of solutions is caused by the nonconvex nature being present typically in many engineering problems. Global optimization (GO), sometimes called nonconvex optimization, encompasses several techniques which can be used to handle the problem of finding the best of these solutions, the global optimum.

General form of GO problem is same as for NLP problem and it may be stated as

$$ \begin{array}{l}\underset{x}{ \min }f\left(\boldsymbol{x}\right)\\ {}\mathrm{s}.\mathrm{t}. \boldsymbol{h}\left(\boldsymbol{x}\right)=0\\ {} \boldsymbol{g}\left(\boldsymbol{x}\right)\le 0\end{array} $$

where x represents vector of optimization (decision) variables, f(x) is optimization criterion, h(x) and g(x) stand for vectors of equality and inequality constraints, respectively.

To find the global optimum, many methods have...

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Correspondence to Radoslav Paulen .

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Paulen, R. (2014). Global Optimization of Membrane Processes. In: Drioli, E., Giorno, L. (eds) Encyclopedia of Membranes. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40872-4_701-5

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  • DOI: https://doi.org/10.1007/978-3-642-40872-4_701-5

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  • Online ISBN: 978-3-642-40872-4

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