作　　者： (高引民）; (陈建斌）;

机构地区： 北京联合大学商务学院,北京100025

出　　处： 《中北大学学报（自然科学版）》 2017年第4期409-413,共5页

摘　　要： 为完善线性规划约束条件方面的基本理论,研究了一种高效的求解线性规划问题的算法.以区分最优松约束条件和最优紧约束条件为主线,利用线性规划,线性代数等数学理论,进行分析,并通过大量的数据实验进行验证.从理论上获得了最优紧约束条件一些性质及识别最优松约束条件的定理,提供了一种新的单纯形算法.数据试验和理论上表明,在求解大规模解线性规划问题时,利用新的求解算法,使得模型逐步降阶,能达到求解的高效率. Aiming to improve the theory of linear programming with respect to the constraint conditions, a new simple method in solving the large-scale problem ineffective variables was presented. Methods to study the property of optimal slack constraint conditions and optimal tight constraint conditions emplo- ying some mathematical tools in linear programming and linear algebra and so forth were used to do numerical tests. The characteristics of the optimal tight constraint conditions, the theorems of identifying optimal slack constraint conditions and a new simple method have been obtained from results. Numerical tests and theory illustrated that identifying and eliminating optimal slack constraint conditions can simplify its constraint conditions and improve the efficiency of solving the problem of linear programming in solving the large-scale problem.

关 键 词： 线性规划 单纯形算法 约束条件 最优紧约束条件