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Treating Free Variables in Generalized Geometric Global Optimization Programs

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Abstract

Generalized geometric programming (GGP) problems occur frequently in engineering design and management. Recently, some exponential-based decomposition methods [Maranas and Floudas, 1997,Computers and Chemical Engineering 21(4), 351–370; Floudas et al., 1999 , Handbook of Test Problems in Local and Global Optimization, Kluwer Academic Publishers, Boston, pp. 5–105; Floudas, 2000 Deterministic Global Optimizaion: Theory, Methods and Application, Kluwer Academic Publishers, Boston, pp. 257–306] have been developed for GGP problems. These methods can only handle problems with positive variables, and are incapable of solving more general GGP problems. This study proposes a technique for treating free (i.e., positive, zero or negative) variables in GGP problems. Computationally effective convexification rules are also provided for signomial terms with three variables.

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References

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Authors and Affiliations

  1. Institute of Information Management, National Chiao Tung University, No. 1001, Ta Hsueh Road, Hsinchu, 300, Taiwan, R.O.C

    Han-lin Li

  2. Department of Business Management, National Taipei University of Technology, No. 1, Sec. 3, Chung Hsiao E. Road, Taipei, 10608, Taiwan, R.O.C

    Jung-fa Tsai

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  1. Han-lin Li
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  2. Jung-fa Tsai
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Correspondence to Jung-fa Tsai.

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Li, Hl., Tsai, Jf. Treating Free Variables in Generalized Geometric Global Optimization Programs. J Glob Optim 33, 1–13 (2005). https://doi.org/10.1007/s10898-005-2098-3

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  • DOI: https://doi.org/10.1007/s10898-005-2098-3

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