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Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining

机译:组合优化和数据挖掘动态规划的扩展

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In contrast with conventional dynamic programming algorithms that return one solution, extensions of dynamic programming allows us to work with the whole set of solutions or its essential part, to perform multi-stage optimization relative to different criteria, to count the number of solutions, and to find the set of Pareto optimal points for bi-criteria optimization problems. The presentation is based on the results considered in three books published or accepted by Springer.
机译:与返回一个解决方案的传统动态编程算法相比,动态编程的扩展允许我们使用整组解决方案或其基本部分,以执行相对于不同标准的多级优化,以计算解决方案的数量,以及 找到帕累托的帕累托最优点,用于双标准优化问题。 该演示文稿基于Springer发布或接受的三本书中考虑的结果。

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