A new global optimization approach for convex multiplicative programming

作者：Gao, Yuelin; Wu, Guorong; Ma, Weimin^*

来源：Applied Mathematics and Computation, 2010, 216(4): 1206-1218.

DOI：10.1016/j.amc.2010.02.012

• Global optimization
• Convex multiplicative programming
• Outer approximation
• Branch-and-bound
• Outcome space

In this paper, by solving the relaxed quasiconcave programming problem in outcome space, a new global optimization algorithm for convex multiplicative programming is presented. Two kinds of techniques are employed to establish the algorithm. The first one is outer approximation technique which is applied to shrink relaxation area of quasiconcave programming problem and to compute appropriate feasible points and to raise the capacity of bounding. And the other one is branch and bound technique which is used to guarantee global optimization. Some numerical results are presented to demonstrate the effectiveness and feasibility of the proposed algorithm.

• 出版日期2010-4-15
• 单位西北工业大学; 北方民族大学; 同济大学