应急物流中的覆盖问题 最大覆盖问题算法) 线性规划:Church RL和Meadows ME 拉格朗日松弛算法(Lagrangean Relaxation):Roberto,Orhan 启发式算法:Charles,Haldun,Benedict,Hogan,Daskin 超立方体排队模型 Fernando etc.
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...模拟退火(simulated annealing)–遗传算法(ic algorithms)–人工神经网络(works)–拉格朗日松弛算法(Lagrange slack arithmetic)组合最优化问题概论 binatorial optimization)–是通过对数学方法的研究去寻找离散事件的最优编排、分组、次序或筛选等–组合最优...
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算法实例表明，改进后的拉格朗日松弛算法迭代步数显著减少，证明算法是有效的。
Computational examples show that the modified subgradient optimization algorithm for Lagrangean relaxation can reduce the iterative steps obviously, and is proved to be efficient.
通过对该算法及其改进算法以及拉格朗日松弛算法的应用效果分析，验证所提算法的有效性。
By the analyses of applications of the new algorithms and Lagrangian relaxation algorithm, the validity of the algorithms presented in this paper is verified.
以医疗急救资源的配置问题为建模核心，运用次梯度最优算法对传统的拉格朗日松弛算法进行了改进。
This paper focuses on the modeling of the resources location of medical rescue. At first, the traditional Lagrangean relaxation algorithm is improved by using subgradient optimization algorithm.
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