采用本文的混合算法对初始调度方案的多目标调度模型进行求解，并与常规PS

采用本文的混合算法对初始调度方案的多目标调度模型进行求解，并与常规PSO算法进行对比，其迭代收敛曲线如图6所示。从曲线上看，随着迭代次数的增加，各目标函数的最优值均在逐渐优化，经过大约50次迭代后混合算法趋于稳定，总体上优化结果比常规PSO方法的最优值更小，表明混合算法具有良好的收敛性。

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结果 (英语) 1: [复制]

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The hybrid algorithm in this paper is used to solve the multi-objective scheduling model of the initial scheduling scheme, and compared with the conventional PSO algorithm, the iterative convergence curve is shown in Figure 6. From the curve point of view, as the number of iterations increases, the optimal value of each objective function is gradually optimized. After about 50 iterations, the hybrid algorithm stabilizes, and the overall optimization result is smaller than the optimal value of the conventional PSO method. , Which shows that the hybrid algorithm has good convergence.

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结果 (英语) 2:[复制]

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The hybrid algorithm in this paper is used to solve the multi-objective scheduling model of the initial scheduling scheme, and compared with the conventional PSO algorithm. The iterative convergence curve is shown in Fig. 6. From the curve, with the increase of the number of iterations, the optimal value of each objective function is gradually optimized. After about 50 iterations, the hybrid algorithm tends to be stable. On the whole, the optimization result is smaller than the optimal value of the conventional PSO method, indicating that the hybrid algorithm has good convergence.<br>

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结果 (英语) 3:[复制]

复制成功！

This paper uses the hybrid algorithm to solve the multi-objective scheduling model of the initial scheduling scheme, and compares it with the conventional PSO algorithm. The iterative convergence curve is shown in Figure 6. From the curve point of view, with the increase of iteration times, the optimal value of each objective function is gradually optimized. After about 50 iterations, the hybrid algorithm tends to be stable, and the overall optimization result is smaller than the optimal value of the conventional PSO method, which indicates that the hybrid algorithm has good convergence.

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