A new linearization technique for minimax linear fractional programming

作者：Jiao, Hongwei; Liu, Sanyang^*

来源：International Journal of Computer Mathematics, 2014, 91(8): 1730-1743.

DOI：10.1080/00207160.2013.860449

• global optimization
• minimax linear fractional programming
• linearization technique
• branch-and-bound
• linear relaxation programming

This paper presents a deterministic global optimization algorithm for solving minimax linear fractional programming (MLFP). In this algorithm, a new linearization technique is proposed, which uses more information of the objective function of the (MLFP) than other techniques. By utilizing this new linearization technique, the initial nonconvex programming problem (MLFP) is reduced to a sequence of linear relaxation programming (LRP) problems, which can provide reliable lower bound of the optimal value. The proposed algorithm is convergent to the global minimum of the (MLFP) through the successive refinement of the feasible region and solutions of a series of the (LRP). Compared with the known algorithms, numerical results show that the proposed algorithm is robust and effective.

• 出版日期2014
• 单位西安电子科技大学