Improved Regularity Model-Based EDA for Many-Objective Optimization
نویسندگان
چکیده
منابع مشابه
Improved Regularity Model-based EDA for Many-objective Optimization
The performance of multi-objective evolutionary algorithms deteriorates appreciably in solving many-objective optimization problems which encompass more than three objectives. One of the known rationales is the loss of selection pressure which leads to the selected parents not generating promising offspring towards Pareto-optimal front with diversity. Estimation of distribution algorithms sampl...
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Multiobjective optimization problems occur frequently in practice where multiple objectives have to be optimized simultaneously and the goal is to find or approximate the set of Pareto-optimal solutions. Multiobjective evolutionary algorithms (MOEAs) are one type of randomized search heuristics that are well-suited for multiobjective optimization problems due to their ability of computing a set...
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ژورنال
عنوان ژورنال: IEEE Transactions on Evolutionary Computation
سال: 2018
ISSN: 1089-778X,1089-778X,1941-0026
DOI: 10.1109/tevc.2018.2794319