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The issue with constraint tolerance when implementing MPCC formulation in GEKKO is that the solver may not be able to find a feasible solution within the specified tolerance range. This can happen when the constraints are very tight or when the model has multiple constraints and highly nonlinear equations. In some cases, the solver may require a higher tolerance to find a feasible solution, but this can increase the computational time and memory usage. Therefore, selecting an appropriate constraint tolerance is important to balance the accuracy and efficiency of the optimization process.