Continuous GRASP with a local active-set method for bound-constrained global optimization

被引:3
|
作者
Birgin, Ernesto G. [2 ]
Gozzi, Erico M. [2 ]
Resende, Mauricio G. C. [1 ]
Silva, Ricardo M. A. [3 ]
机构
[1] AT&T Labs Res, Algorithms & Optimizat Res Dept, Florham Pk, NJ USA
[2] Univ Sao Paulo, Inst Matemat & Estatist, Sao Paulo, Brazil
[3] Univ Fed Lavras, Dept Comp Sci, Lavras, Brazil
关键词
Global optimization; Stochastic methods; Active-set methods; Heuristic; CGRASP; GENCAN; AUGMENTED LAGRANGIAN-METHODS; ALGORITHM; SOFTWARE;
D O I
10.1007/s10898-009-9494-z
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Global optimization seeks a minimum or maximum of a multimodal function over a discrete or continuous domain. In this paper, we propose a hybrid heuristic-based on the CGRASP and GENCAN methods-for finding approximate solutions for continuous global optimization problems subject to box constraints. Experimental results illustrate the relative effectiveness of CGRASP-GENCAN on a set of benchmark multimodal test functions.
引用
收藏
页码:289 / 310
页数:22
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