对带自由变量的广义几何规划问题(FGGP)给出一全局优化算法.该算法先利用等价转换把(FGGP)中的自由变量转化为正变量,再通过凸化方案建立了(FGGP)的松弛凸规划(RCP).通过对(RCP)可行域的细分以及一系列(RCP)的求解过程,提出的算法收敛到(FGGP)的全局最优解,且数值例子表明了算法的可行性.
A global optimization algorithm is proposed for locating global minimum ot generalized geometric programming (FGGP) with free variables. By utilizing equivalent transformation, free variables in (FGGP) are first transformed into positive variables, by con- vexication strategies the relaxation convex programming (RCP) about (FGGP) is then estab- lished. The proposed branch and bound algorithm is 'convergent to the global minimum of (FGGP) through the successive renement of the feasible region of (RCP) and the solutions of a series of (RCP). And finally the numerical examples are given to illustrate the feasibility of the present algorithm.