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- W2074461331 abstract "T his paper presents a n ovel adaptive multi-objective particle swarm optimization algorithm and with adaptive multi-objective particle swarm algorithm for solving constrained function optimization problems, in which Pareto non-dominated ranking, tournament selection, crowding distance method were introduced, simultaneously the rate of crowding distance changing were integrated into the algorithm. Finally, ten standard functions are used to test the performance of the algorithm, experimental results show that the proposed approach is an effecient, and achieve a high-quality performance." @default.
- W2074461331 created "2016-06-24" @default.
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- W2074461331 date "2010-08-12" @default.
- W2074461331 modified "2023-09-26" @default.
- W2074461331 title "An Effective Adaptive Multi-objective Particle Swarm for Multimodal Constrained Function Optimization" @default.
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- W2074461331 doi "https://doi.org/10.4304/jcp.5.8.1144-1151" @default.
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