American Institute of Mathematical Sciences

April  2012, 8(2): 429-455. doi: 10.3934/jimo.2012.8.429

An efficient convexification method for solving generalized geometric problems

 1 Department of Information Management, Fu Jen Catholic University, No.510, Zhongzheng Rd., Xinzhuang Dist., New Taipei City 24205, Taiwan

Received  September 2010 Revised  November 2011 Published  April 2012

Convexification transformation is vital for solving Generalized Geometric Problems (GGP) in global optimization. Björk et al. [3] posited that transforming non-convex signomial terms in a GGP into 1-convex functions is currently the most efficient convexification technique. However, to the best of our knowledge, an efficient convexification method based on the concept of 1-convex functions has not been proposed. To address this research gap, we present a Beta method to maximally improve the efficiency of convexification based on the concept of 1-convex functions, and thereby enhance the accuracy of linearization without increasing the number of break points and binary variables in the piecewise linear function. The Beta method yields an excellent solution quality and computational efficiency. We compare its performance, with that of three existing approaches using four numerical examples. The computational results demonstrate that, in terms of solution quality and computation time, the proposed method outperforms the compared approaches.
Citation: Hao-Chun Lu. An efficient convexification method for solving generalized geometric problems. Journal of Industrial & Management Optimization, 2012, 8 (2) : 429-455. doi: 10.3934/jimo.2012.8.429
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References:
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