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A supplementary feasibility sampling procedure is added to the framework of interval method for finding optimal solutions of global optimization problem over a bounded interval domain subject to multiple linear constraints.Its main feature is the ability to detect infeasibility or actually locate a feasible sample in any working subinterval.Thus it provides tighter upper bounds of the optimal objective function value than the standard methods.Numerical results will be provided to demonstrate its effectiveness.