对于一类比式和问题(P)给出一全局优化算法.首先利用线性约束的特征推导出问题(P)的等价问题(P1),然后利用新的线性松弛方法建立了问题(P1)的松弛线性规划(RLP),通过对目标函数可行域线性松弛的连续细分以及求解一系列线性规划,提出的分枝定界算法收敛到问题(P)的全局最优解.最终数值实验结果表明了该算法的可行性和高效性.
A global optimization algorithm is proposed for solving a class of sum of ratios problems (P). Firstly,an equivalent problem (P1) of the (P) is derived by exploiting the characteristics of linear constraints. Then, by utilizing a new linear relaxation method the relaxation linear program- ming (RLP) of the (P1) can be constructed and the proposed algorithm is convergent to the global minimum of the (P) through the successive refinement of the linear relaxation of feasible region of the objective function and solutions of a series of (RLP). And finally the numerical experiments are given to illustrate the feasibility and efficiency of the proposed algorithm.