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Solving the minimum M-dominating set problem by a continuous optimization approach based on DC programming and DCA

机译:通过基于DC编程和DCA的连续优化方法来解决最小M控制集问题

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摘要

We propose a new optimization approach based on DC (Difference of Convex functions) programming and DCA (DC Algorithm) to the so-called Minimum M-Dominating Set problem in graphs. This problem is beforehand re-casted as a polyhedral DC program with the help of exact penalty in DC programming. The related DCA is original and computer efficient because it consists of solving a few linear programs and converges after a finite number of iterations to an integer solution while working in a continuous domain. Numerical simulations show the efficiency and robustness of DCA and its superiority with respect to standard methods.
机译:我们提出了一种基于DC(凸函数的差异)编程和DCA(DC算法)的新优化方法,以解决图中的最小M支配集问题。借助DC编程中的精确代价,可以将该问题预先转换为多面体DC程序。相关的DCA是原始的并且计算机高效的,因为它由一些线性程序组成,并且在连续域中工作时,经过有限次迭代后收敛到整数解。数值模拟显示了DCA的效率和鲁棒性及其相对于标准方法的优越性。

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