A new linearization method for generalized linear multiplicative programming

  • Authors:
  • Chun-Feng Wang;San-Yang Liu

  • Affiliations:
  • Department of Mathematical Sciences, Xidian University, Xi'an 710071, PR China;Department of Mathematical Sciences, Xidian University, Xi'an 710071, PR China

  • Venue:
  • Computers and Operations Research
  • Year:
  • 2011

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Abstract

This paper presents a deterministic global optimization algorithm for solving generalized linear multiplicative programming (GLMP). In this algorithm, a new linearization method is proposed, which applies more information of the function of (GLMP) than some other methods. By using this new linearization technique, the initial nonconvex problem is reduced to a sequence of linear programming problems. A deleting rule is presented to improve the convergence speed of this algorithm. The convergence of this algorithm is established, and some experiments are reported to show the feasibility and efficiency of this algorithm.