首先回顾了采用最钝角行、列主元规则求解线性规画问题的原始、对偶可行解的主要过程，阐述了其与众不同的特性。
First, the main procedures and the distinctive features of the most-obtuse-angle (MOA) row or column pivot rules are introduced for achieving primal or dual feasibility in linear programming.
采用椭球剖分策略剖分可行域为小的椭球，用投影次梯度算法解松弛二次规划问题的拉格朗日对偶问题，从而获得原问题的一个下界。
A projection subgradient algorithm for the Lagrangian dual problem of the relaxed quadratic problem is employed to general lower bounds of the optimal value for the original problem.
然后依据对偶问题的解，以启发式方法构作原问题的可行解。
A heuristic method is then proposed to construct a feasible solution of the original problem.
然后依据对偶问题的解，以启发式方法构作原问题的可行解。
A heuristic method is then proposed to construct a feasible solution of the original problem.
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