  By combining a parameterized Hermitian matrix, the realignment matrix of the
bipartite density matrix $\rho$ and the vectorization of its reduced density
matrices, we present a family of separability criteria, which are stronger than
the computable cross norm or realignment (CCNR) criterion. With linear
contraction methods, the proposed criteria can be used to detect the
multipartite entangled states that are biseparable under any bipartite
partitions. Moreover, we show by examples that the presented multipartite
separability criteria can be more efficient than the corresponding multipartite
realignment criterion based on CCNR, multipartite correlation tensor criterion
and multipartite covariance matrix criterion.
