Abstract
The most common approach for solving constrained optimization problems is based on penalty functions, where the constrained problem is transformed into a sequence of unconstrained problem by penalizing the objective function when constraints are violated. In this paper, we analyze the implementation of an adaptive penalty method, within the DIRECT algorithm, in which the constraints that are more difficult to be satisfied will have relatively higher penalty values. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered.
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