Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/43984
Type of publication: Straipsnis konferencijos medžiagoje Clarivate Analytics Web of Science ar/ir Scopus / Article in Clarivate Analytics Web of Science or Scopus DB conference proceedings (P1a)
Field of Science: Informatika / Informatics (N009)
Author(s): Žilinskas, Antanas;Fraga, E.S;Mackutė, Aušra;Varoneckas, Audrius
Title: Adaptive search for optimum in a problem of oil stabilization process design
Is part of: Adaptive computing in design and manufacture VI. London : Springer, 2004
Extent: p. 87-99
Date: 2004
Note: Leidinio DOI 10.1007/978-0-85729-338-1
Keywords: Stabilization process design;Evolutionary optimization;Random search;Implicit constraints;Small feasible region
ISBN: 9781852338299
Abstract: The formulation of a model for an industrial problem in process design leads to an optimization problem with a small, implicitly defined, feasible region, a region which is difficult to identify a priori. The difficulties of obtaining a good solution with conventional optimization methods are discussed. A novel method is proposed, based on the paradigm of evolutionary computing and a two stage search: the first stage aims to find a set of points covering the feasible region and the second stage is a search for the optimum, modelling the evolution of the population, the set of points, found in the first stage. The results of profit optimization for an industrial case study are presented
Internet: https://hdl.handle.net/20.500.12259/43984
Affiliation(s): Vytauto Didžiojo universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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