Elizabeth F. Wanner

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This paper proposes a local search optimizer that, employed as an additional operator in multiobjective evolutionary techniques, can help to find more precise estimates of the Pareto-optimal surface with a smaller cost of function evaluation. The new operator employs quadratic approximations of the objective functions and constraints, which are built using(More)
This paper presents a new operator for genetic algorithms that enhances their convergence in the case of nonlinear problems with nonlinear equality constraints. The proposed operator, named CQA (Constraint Quadratic Approximation), can be interpreted as both a local search engine (that employs quadratic approximations of both objective and constraint(More)
Recent works raised the hypothesis that the assignment of a geometry to the decision variable space of a combinatorial problem could be useful both for providing meaningful descriptions of the fitness landscape and for supporting the systematic construction of evolutionary operators (the geometric operators) that make a consistent usage of the space(More)
This paper presents a new operator for genetic algorithms that enhances convergence in the case of multiple nonlinear equality constraints. The proposed operator, named CQA-MEC (Constraint Quadratic Approximation for Multiple Equality Constraints), performs the steps: (i) the approximation of the non-linear constraints via quadratic functions; (ii) the(More)
The optimal solution provided by metaheuristics can be viewed as a random variable, whose behavior depends on the value of the algorithm's strategic parameters and on the type of penalty function used to enforce the problem's soft constraints. This paper reports the use of parametric and non-parametric statistics to compare three different penalty functions(More)