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A polynomial case of the cardinality-constrained quadratic optimization problem

机译:基数约束二次优化问题的多项式情况

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摘要

We propose in this paper a fixed parameter polynomial algorithm for the cardinality-constrained quadratic optimization problem, which is NP-hard in general. More specifically, we prove that, given a problem of size n (the number of decision variables) and s (the cardinality), if the n - k largest eigenvalues of the coefficient matrix of the problem are identical for some 0 < k ≤ n, we can construct a solution algorithm with computational complexity of O (n~(2k)). Note that this computational complexity is independent of the cardinality s and is achieved by decomposing the primary problem into several convex subproblems, where the total number of the subproblems is determined by the cell enumeration algorithm for hyperplane arrangement in R~k space.
机译:我们针对基数约束的二次优化问题提出了一种固定参数多项式算法,该算法通常为NP-hard。更具体地说,我们证明,给定大小为n(决策变量的数量)和s(基数)的问题,如果问题的系数矩阵的n-k个最大特征值在0

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