This course is oriented around computation and computation-related issues in developing and solving large-scale optimization models.
本课程定位是开发和解决大规模最佳化模型中的计算以及计算相关问题。
With the rapid development of computer science and urgent needs for practical problem in recent years, the large-scale optimization problem has drawn more and more attention.
近年来，随着计算机的飞速发展以及实际问题的需要，大规模优化问题越来越受到重视，很多实际问题都可以归结为最优化问题来解。
Genetic algorithms are efficient search procedures for large scale optimization.
遗传算法是求解大型优化问题非常有效的算法。
Conjugate gradient method, which can be easily computed and requires no matrix storage, is one of the most popular and useful method for solving large scale optimization problems.
共轭梯度法是最优化中最常用的方法之一，它具有算法简便、不需要矩阵存储等优点，十分适合于大规模优化问题。
Conjugate gradient method, which can be easily computed and requires no matrix storage, is one of the most popular and useful method for solving large scale optimization problems.
共轭梯度法是最优化中最常用的方法之一，它具有算法简便、不需要矩阵存储等优点，十分适合于大规模优化问题。
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