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• W2783127396 startingPage "1850009" @default.
• W2783127396 abstract "In this study, a novel multi-objective hybrid algorithm (MHGH, multi-objective HPSO-GA hybrid algorithm) is developed by crossing the heuristic particle swarm optimization (HPSO) algorithm with a genetic algorithm (GA) based on the concept of Pareto optimality. To demonstrate the effectiveness of the MHGH, the optimizations of four unconstrained mathematical functions and four constrained truss structural problems are tested and compared to the results using several other classic algorithms. The results show that the MHGH improves the convergence rate and precision of the particle swarm optimization (PSO) and increases its robustness." @default.
• W2783127396 created "2018-01-26" @default.
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• W2783127396 date "2018-01-01" @default.
• W2783127396 modified "2023-09-27" @default.
• W2783127396 title "A Multi-Objective Hybrid Algorithm for Optimization of Grid Structures" @default.
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• W2783127396 doi "https://doi.org/10.1142/s1758825118500096" @default.
• W2783127396 hasPublicationYear "2018" @default.
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