Then a suboptimal solution of the graph maximum equal - cut problem is presented employing the randomized algorithm and the improved coordinate ascent ( descent ) algorithm on the optimal solution of semidefmite relaxation 在利用lagrange乘子理论得出原始问题的等价形式之后，将近似算法与改进的坐标上升(下降)算法结合，求得原问题的次优解。
After that , the crisp equivalences are also discussed for different models when fuzzy variables are characterized by triangular fuzzy numbers , and the procedure is given to solve the deterministic models based on the genetic algorithm 当模糊变量是三角模糊数时，讨论了模糊规划模型的清晰等价形式，并采用遗传算法给出了求解模型的具体步骤。
In chapter 3 , we give an equivalent form of semi - infinite programming , and a locally convergent ssle method is proposed for sip . we only need solve a linear system equations and a subproblem with a parameter per step , also a modified algorithm which saves cost of computations is given , at the end of the paper , we give a proof of the convergence for the algorithms 第三章通过适当的变形，得到半无限规划问题的一个等价形式，并给出一个局部收敛的序列线性方程组算法，这个算法在每一步，只需求解一个线性方程组和一个带参数的非线性子问题，证明了算法的收敛性，同时，给出了一个修正算法，与前面算法相比较，修正算法节约一定的计算量，同样具有较好的收敛性。
Common pd in signal language learning mainly showed in the following : ca n ' t understand the objects the mathematics signals represent ; scare of extensive cognition to the mathematics objects which mathematics signals represent . do n ' t understand the meaning expressed by signal language . the same signal forms can express different meanings , and different signal forms can express the same meaning , if student separate signal language from its maths meaning contained in it , the ml they mastered is a kind of signal game without any meaning ; not mastering various forms of signal language ( signal language has many equal forms ) or only mastering one kind or several kinds forms , the cognition to signals are not enough 符号语言学习的常见心理偏差主要表现存不能理解数学符号代表的对象，缺乏对数学符号所表示的数学对象的广泛性的认识；不明白符号语言表达的含义，如果将符号语言与所表达的数学含义相脱离，学生所掌握的数学语言就是毫无意义的符号游戏；掌握不了符号语言的各种变化形式，符号语言有许多的等价形式，如果只是掌握其中的一种或几种形式，对它的认识将不够充分。
