Using the conic function model local approximation , w . cdavidon ( 1980 ) proposed a class of iterative algorithms with modified matrix combining function value , furthermore under the theory d . c . sorensen has used local quadratic approximation method , then applying collinear scaling idea improving on the above algorithm and generalizing it , getting a class of collinear scaling algorithm , unifying former quasi - newton . in the paper , using local quadratic approximation method , the first , constructing the new collinear scaling gene , getting a class of the new collinear scaling algorithm with briefness and numerical stability , . , we discusses some properties of the algorithm and its local linear convergence , q - superlinear convergence and the whole convergence ; secondly we have made numerical experimentation and numerical analysis ; the last , we have done much discussion for collinear scaling idea and given the several new collinear scaling algorithm 本文的工作就是基于局部二次逼近原理,首先通过构造新的共线调比因子,得到了一类新的更简洁,数值稳定性更好的共线调比算法,进而我们给出了本共线调比算法的局部收敛性,全局收敛性以及算法q -超线性速度的理论证明;其次,用经典的无约束优化五大考核函数就本共线调比算法进行了数值试验和数值分析;最后,就局部二次逼近思想,进行共线调比算法思想进行更广泛的讨论,给出了几个新共线调比算法。
The main research objects are transferred structure control stochastic system . according to the condition of the system , a decision maker ( a man or a computer ) should select a way to control or affect the transfer of the system , so that each way decides the aimed function value of the stochastic process and the corresponding ones 其主要研究对象是转移结构受控的随机系统,根据系统的状态,决策者(如人类或计算机)选取一个策略来控制或影响系统的转移,从而每个策略可定义一个随机过程和相应于该过程的目标函数值, mdp的目的是选取一个好的控制策略。
One method which can obtain best scheduling rule set in specific manufacture environment is proposed , genetic algorithm and process simulation is integrated in this method , process simulation is used to get adaptive function value and genetic algorithm is used to search optimum solution . and , for lessening calculation time , serial genetic algorithm is replaced by parallel genetic algorithm 提出了一种将遗传算法和过程仿真相结合的调度规则选择方式,它以过程仿真求取适应度函数值,应用遗传算法进行优化,从而完成特定生产环境下的调度规则选择问题;并以主从式并行遗传算法代替传统遗传算法,从而保证了最终解在时间上和质量上的可行性。