k-median问题的近似算法研究一直是计算机科学工作者关注的焦点.基于均衡限制条件,利用反向贪心策略,给出求解该问题的随机近似算法.证明该算法以较大的概率满足其近似性能比的期望值为(3 +O(ln(ln(k)/a)).该算法的时间复杂度为O([k/aln(k)]2(n+m)),其中n和m分别代表设施集合以及客户点集的大小.最后,通过计算机实验验证了k-median问题的反向贪心算法的实际计算效果.%Research on the approximated algorithms for k-median problem has been a focus of computer scientists. Based on the balanced parameter, this paper presented a randomized algorithm for k-median problem by means of the reverse greedy. The new algorithm's expected approximate ratio was proved to be(3+O(ln(ln(k)/a)) with high probability. The running time of the new algorithm is [k/aln(k)]2 (n+m) .where n and m represent the number of clients and facilities for the given instance. Finally,computer verification was used to study the real computational effect of the algorithm.
展开▼
