The field of evolutionary knowledge transfer (EKT) has recently begun to systematically develop algorithms that exploit a number of related problem instances to accelerate problem solving on difficult optimization tas...
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evolutionary algorithms are among the metaheuristic search methods that have been applied to the structural test data generation problem. Fitness evaluation methods play an important role in the performance of evoluti...
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ISBN:
(纸本)1595931864
evolutionary algorithms are among the metaheuristic search methods that have been applied to the structural test data generation problem. Fitness evaluation methods play an important role in the performance of evolutionary algorithms and various methods have been devised for this problem. In this paper, we propose a new fitness evaluation method based on pairwise sequence comparison also used in bioinformatics. Our preliminary study shows that this method is easy to implement and produces promising results.
evolutionary algorithms have shown during the last decades that they can solve a wide range of real-world problems in different fields, such as science or engineering. In this paper, we explore the application of Hybr...
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The decision space of large-scale multi-objective evolutionary optimization problems is broader, which makes the solving process more difficult. In this paper, we propose an adaptive large-scale multi-objective optimi...
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This paper presents two parallelizations of a standard evolutionary algorithm on an NVIDIA GPGPU card, thanks to a parallel replacement operator. These algorithms tackle new problems where previously presented approac...
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The indicator-based multi-objective optimization evolutionary algorithm has gained significant attention for its strong performance across various optimization problems. We draw on the advantages and try to make impro...
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With the rapid growth of solar energy demand, the optimization of the photovoltaic model becomes significant. The conversion efficiency of the photovoltaic model is mainly determined by its structural parameters, and ...
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Many-objective Optimization problems (MaOPs), with four or more objectives are difficult to solve, is a kind of common optimization problems in actual industrial production. In recent years, a large number of many-obj...
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Mammographic risk analysis is an important and challenging issue in modern medical science;research and development in this area has recently attracted much attention. Many efforts have been devoted to achieving a hig...
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evolutionary algorithms are applied to problems that are not well understood as well as to problems in combinatorial optimization. The analysis of these search heuristics has been started for some well-known polynomia...
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ISBN:
(纸本)3540230920
evolutionary algorithms are applied to problems that are not well understood as well as to problems in combinatorial optimization. The analysis of these search heuristics has been started for some well-known polynomial solvable problems. Such analyses are starting points for the analysis of evolutionary algorithms of difficult problems. We consider the NP-hard multi-objective minimum spanning tree problem and give upper bounds on the expected time until a simple evolutionary algorithm has produced a population including for each extremal point of the Pareto Front a corresponding spanning tree.
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