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I have a non-convex Quadratic Programming over unite simplex set. I have a valid lower bound on the objective function (goal is minimization problem). If I add a constraint like $$f(x)\geq lower~bound,$$ the solver time is increased, since I add a non-convex constraint! is there any efficient way to use a lower bound in the input when we use Gurobi as a solver (in yalmip)?

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There's a cutoff parameter that may help. Another approach, though may or may not work is to try with $Z(x)$ $=$ lower_bound$+f(x)$

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