Abstract:

An optimization strategy is presented that provides a framework in which optimization algorithms and heuristic procedures can be coupled to solve nonlinearly constrained design optimization problems.  These problems cannot be efficiently solved by either approach independently.  The approach is based on an optimization algorithm dealing with local monotonicity and sequential quadratic programming techniques with heuristic procedures which are statistically derived form observations obtained by applying the optimization algorithm to different classes of test problems
 

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