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Evolution strategies | a stochastic optimization method originally designed for single criterion problems | have been modiied in such a way that they can also tackle multiple criteria problems. Instead of computing only one eecient solution interactively, a decision maker can collect as many members of the Pareto set as needed before making up his mind.(More)
Optimization algorithms imitating certain principles of nature have proved their capability in various domains of applications. Dealing with parameter optimization problems one usually trades the original problem for a much simpler one, estimating the exogenous parameters of the algorithm chosen to yield a good solution as fast as possible. On the one hand,(More)
| Which are the fundamental principles of life? This is the main question to be addressed if one tries to create artiicial life on computers. Though it has been answered only partially, evolutionary algorithms are substantially contributing already to many kinds of human problem solving by means of virtual organisms. Besides looking back on that success(More)
Evolutionary algorithms are direct, global optimization algorithms gleaned from the model of organic evolution. The most important representatives, genetic algorithms and evolution strategies, are brieey introduced and compared in this paper, and their major diierences are clariied. Furthermore, the paper summarizes the application possibilities of(More)
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