Solving global optimization problems using reformulations and signomial transformations

•A framework for convexifying MINLP problems containing signomial functions and twice-differentiable functions is presented.•Lifting transformation schemes based on power, exponential and αBB-type reformulations is used.•The transformations used in the framework are obtained by solving an optimizati...

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Veröffentlicht in:	Computers & chemical engineering Jg. 116; S. 122 - 134
Hauptverfasser:	Lundell, A., Westerlund, T.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 04.08.2018
Schlagworte:	Difference of convex functions Exponential transformations Global optimization Nonconvex MINLP Power transformations Reformulation techniques Signomial functions Twice-differentiable nonconvex functions α reformulation αBB convex underestimator Global optimization Twice-differentiable nonconvex functions Reformulation techniques Signomial functions α reformulation Power transformations Difference of convex functions Exponential transformations αBB convex underestimator Nonconvex MINLP
ISSN:	0098-1354, 1873-4375
Online-Zugang:	Volltext
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