Range reduction techniques for improving computational efficiency in global optimization of signomial geometric programming problems

► We integrate range reduction techniques for SGP problems to decrease CPU time. ► Proposed algorithm reaches an approximate global solution. ► Numerical experiments are presented to demonstrate the advantages. Many global optimization approaches for solving signomial geometric programming problems...

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Veröffentlicht in:	European journal of operational research Jg. 216; H. 1; S. 17 - 25
Hauptverfasser:	Lin, Ming-Hua, Tsai, Jung-Fa
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 2012 Elsevier Elsevier Sequoia S.A
Schlagworte:	Algorithms Applied sciences Approximation Computational efficiency Efficiency Exact sciences and technology Geometry Global optimization Integer programming Inverse problems Linearization Mathematical models Mathematical programming Operational research and scientific management Operational research. Management science Optimization Optimization algorithms Piecewise linear function Programming Range reduction Reduction Signomial geometric programming Studies Transformations Range reduction Global optimization Piecewise linear function Signomial geometric programming Non convex programming Inverse transformation Global optimum Mixed integer programming Non linear programming Convex programming Optimization Geometric programming Computation time Point process Linearization techniques Problem solving Signomial function Piecewise linearization Piecewise-linear techniques
ISSN:	0377-2217, 1872-6860
Online-Zugang:	Volltext
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