Bibliographical Note on Geometric Programming

Rijckaert, M. J.; Martens, X. M.

doi:10.1007/978-1-4615-8285-4_23

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Program I Minimize1

Introduction1

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1986

2008

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Article2

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Cited by 2 publications

(2 citation statements)

References 95 publications

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“…Y -Ail -s q , i = 1, 2 , ..., k ; and l pO -pl ST then the optimal solution -given by Eqs. (7) and ( 8 ) is the optimal solution of Program 2 and hence that of Program 1 . Otherwise, go to STEP 6.…”

Section: Program I Minimizementioning

confidence: 96%

Multiobjective optimization of a queueing system

Verma

1986

Optimization

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Section: Program I Minimizementioning

confidence: 96%

Multiobjective optimization of a queueing system

Verma

1986

Optimization

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“…Many local optimization approaches have been developed for the solution of GGP problems. Some examples from the literature are [5][6][7]. A computational study of local GGP codes is reported in [8].…”

Section: Introductionmentioning

confidence: 98%

Global solution of optimization problems with signomial parts

Pörn¹,

Björk

Westerlund

2008

Discrete Optimization

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In this paper a new approach for the global solution of nonconvex MINLP (Mixed Integer NonLinear Programming) problems that contain signomial (generalized geometric) expressions is proposed and illustrated. By applying different variable transformation techniques and a discretization scheme a lower bounding convex MINLP problem can be derived. The convexified MINLP problem can be solved with standard methods. The key element in this approach is that all transformations are applied termwise. In this way all convex parts of the problem are left unaffected by the transformations. The method is illustrated by four example problems.

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Bibliographical Note on Geometric Programming

Cited by 2 publications

References 95 publications

Multiobjective optimization of a queueing system

Multiobjective optimization of a queueing system

Global solution of optimization problems with signomial parts

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