We study an optimization problem for weighted Lin–Lu–Yau curvature. Given a graph and a prescribed lower curvature bound , we ask for the smallest multiplicative distortion of the edge weights needed to make every edge have curvature at least . This leads to the family which extends the nonnegative-curvature invariant introduced in our preceding paper \cite{Xia2026InvariantI}. The edge weights change the transition probabilities, while the combinatorial graph distance remains fixed. Positive prescribed curvature leads to a fundamental distinction from the case . If is a connected locally finite infinite graph and , then Thus no finite multiplicative distortion of the edge weights can impose a uniform positive curvature lower bound on such a graph. For a finite tree with edges, such weights exist exactly when . We prove that the minimum distortion is attained by a weight unique up to scaling, and that the normalized minimizer and its distortion depend continuously and nondecreasingly on . We then extend the finite-tree theory to general connected graphs. As an application, we characterize the graphs of girth at least six for which finite -distortion is possible.

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