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Using fuzzy bases to resolve nonlinear programming problems
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DOI：10.1016/S0165-0114(98)00273-5.png)
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Abstract
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In this paper we introduce the concept of fuzzy bases and its usefulness in solving optimization problems with a nonlinear objective function and linear constraints. We investigate the properties of fuzzy bases and operationalize them in fuzzy interpolation. The NLP can be relaxed into a bilinear program with a simple structure using fuzzy interpolation, irrespective of whether the objective function is convex or not. If the objective function is convex, we prove that the optimization problem can be transformed into an ordinary LP using fuzzy (linear) bases. (C) 2001 Elsevier Science B.V. All rights reserved.
Keywords:
fuzzy bases
fuzzy interpolation
transformation of NLPs
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