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Performance assessment of multiobjective optimizers: an analysis and review
2003
IEEE Transactions on Evolutionary Computation
An important issue in multiobjective optimization is the quantitative comparison of the performance of different algorithms. In the case of multiobjective evolutionary algorithms, the outcome is usually an approximation of the Pareto-optimal set, which is denoted as an approximation set, and therefore the question arises of how to evaluate the quality of approximation sets. Most popular are methods that assign each approximation set a vector of real numbers that reflect different aspects of the
doi:10.1109/tevc.2003.810758
fatcat:4nfee4wwlnbvxbydgdtl7uug3y