An accelerated extended cutting plane approach with piecewise linear approximations for signomial geometric programming

This paper presents a global optimization approach for solving signomial geometric programming (SGP) problems. We employ an accelerated extended cutting plane (ECP) approach integrated with piecewise linear (PWL) approximations to solve the global optimization of SGP problems. In this approach, we s...

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Vydáno v:Journal of global optimization Ročník 70; číslo 3; s. 579 - 599
Hlavní autoři: Zhan, Yiduo, Zheng, Qipeng P., Tseng, Chung-Li, Pasiliao, Eduardo L.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.03.2018
Springer
Springer Nature B.V
Témata:
Algorithms
Approximation
Computer Science
Cutting
Economic models
Global optimization
Mathematical programming
Mathematics
Mathematics and Statistics
Methods
Mixed integer
Nonlinear programming
Operations Research/Decision Theory
Optimization
Real Functions
Piecewise linear approximation
Signomial geometric programming
Accelerated extended cutting plane
Mixed-integer linear programming
ISSN:0925-5001, 1573-2916
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Shrnutí:This paper presents a global optimization approach for solving signomial geometric programming (SGP) problems. We employ an accelerated extended cutting plane (ECP) approach integrated with piecewise linear (PWL) approximations to solve the global optimization of SGP problems. In this approach, we separate the feasible regions determined by the constraints into convex and nonconvex ones in the logarithmic domain. In the nonconvex feasible regions, the corresponding constraint functions are converted into mixed integer linear constraints using PWL approximations, while the other constraints with convex feasible regions are handled by the ECP method. We also use pre-processed initial cuts and batched cuts to accelerate the proposed algorithm. Numerical results show that the proposed approach can solve the global optimization of SGP problems efficiently and effectively.
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ISSN:0925-5001
1573-2916
DOI:10.1007/s10898-017-0563-4