Linear programming is a tool for solving optimization problems.
线性编程是一个用来解决优化问题的工具。
This and the other optimization problems you'll look at might have more than one solution.
这种最优化问题和其他最优化问题的解可能不止一个。
Once computers are equipped with semantics, they will be capable of solving complex semantical optimization problems.
一旦电脑具备了语义功能，它们就有能力解决复杂的语义最优化问题。
But dynamic programming is usually applied to optimization problems like the rest of this article's examples, rather than to problems like the Fibonacci problem.
但是动态编程通常被用于最优化问题(比如本文后面的示例)，而不是像斐波纳契数这样的问题。
Since the development of the simplex algorithm, linear programming has been used to solve optimization problems in industries as diverse as banking, education, forestry, petroleum, and trucking.
由于simplex算法的出现，线性编程已经在工业界、银行界、教育界、林业、石油行业以及运输业界中广泛地用来解决优化问题。
The assignment problem is a kind of combinatorial optimization problems.
分配问题是一个组合优化问题。
The VRP and the network flow problem are all famous network optimization problems.
车辆路径问题和网络流问题都是非常著名的网络优化问题。
The maximum flow problem is one of the classical combinatorial optimization problems.
最大流问题是一个经典的组合优化问题。
The trust region method is one of the most valid ways to study optimization problems.
信赖域方法是研究最优化问题的有效方法之一。
In this paper, we consider the nonlinear inequality constrained optimization problems.
在本文中，我们考虑非线性不等式约束优化问题。
This characteristic can be successfully used to solve combination optimization problems.
这一特性可成功地应用于解决组合优化问题。
Many optimization problems involve determining efficient methods for reasoning about graphs.
许多优化问题都需要确定有关图推理的高效方法。
Conjugate gradient methods are important iterative methods for solving optimization problems.
共轭梯度法是求解最优化问题的一类有效算法。
Ant Colony algorithm is a novel heuristic algorithm to solve complicated optimization problems.
蚁群算法是一种新型求解复杂优化问题的启发式算法。
Many practical engineering problems can be abstracted to corresponding function optimization problems.
许多实际工程问题可以抽象为相应的函数优化问题。
Finally, we study feasibility and optimality conditions for optimization problems with equilibrium constraints.
第三部分，研究平衡约束优化问题的可行性和最优性条件。
It is an efficient method to solve engineering optimization problems with neural networks and genetic algorithms.
神经网络建模和遗传算法优化是求解工程优化问题的一种行之有效的方法。
Taking complex industry process control as background, this research focuses on optimization problems of fuzzy systems.
本研究是以复杂生产过程为背景，在模糊系统优化领域开展的专项研究。
On the basis of current GRASP, presents an advanced GRASP to solve assembly workshops scheduling optimization problems.
在已有GRASP的基础上，提出一种改进GRASP来解决装配车间调度优化问题。
SA is a stochastic optimization technique that has been used to solve continuous, order discrete and muti-modal optimization problems.
模拟退火算法是一种用于解决连续、有序离散和多模态优化问题的随机优化技术。
The method has universal meaning for a great number of structure optimization problems for which analytic solutions could not be found.
这种方法对实际应用中大量存在而又无法得到解析式的结构优化问题有着普遍的意义。
It has strong robustness and searching ability in whole region, so it can solve most of the optimization problems in practical projects.
由于其具有较强的鲁棒性和全局搜索能力，因此能够有效地解决实际工程中的许多复杂的优化问题。
It has been very important to find very robust and very efficient algorithms for solving optimization problems at structural optimum design.
寻找高度鲁棒的、高效率的优化问题求解算法始终是结构优化设计中一个重要的课题。
Ant colony system is a novel simulated evolutionary algorithm, which provides a new method for complicated combinatorial optimization problems.
蚁群算法是一种新型的模拟进化算法，为求解复杂的组合优化问题提供了一种新的思路。
The ant colony algorithm has good adaptability when solving combined optimization problems, it isn t very good for continuous optimization problems.
蚁群算法在解决组合优化问题上有着良好的适应性，但直接应用于求解连续优化问题难以获得理想的效果。
The ant colony algorithm has good adaptability when solving combined optimization problems, it isn t very good for continuous optimization problems.
蚁群算法在解决组合优化问题上有着良好的适应性，但直接应用于求解连续优化问题难以获得理想的效果。
应用推荐