自适应樽海鞘群算法求解考虑运输时间的柔性作业车间调度

牛昊一,吴维敏,章庭棋,沈微,张涛

Adaptive salp swarm algorithm for solving flexible job shop scheduling problem with transportation time

Hao-yi NIU,Wei-min WU,Ting-qi ZHANG,Wei SHEN,Tao ZHANG

表 2 不同优化算法的实验测试结果（ ${{\overline t } / {\overline p }} > {\text{0}}{\text{.25}}$）

Tab.2 Comparison results of different optimization algorithms ( ${{\overline t } / {\overline p }}{\text{ > 0}}{\text{.25}}$)

案例 AGA IDSSA AAADE MOGWO ASSA $t_{\rm{op }}/ {\rm{s}} $ ${C_{\max }} $ $\delta / {\text{%}} $ $t_{\rm{op }}/ {\rm{s}}$ ${C_{\max }} $ $\delta / {\text{%}} $ $t_{\rm{op }}/ {\rm{s}}$ ${C_{\max }} $ $\delta / {\text{%}} $ $t_{\rm{op }}/ {\rm{s}}$ ${C_{\max }} $ $\delta / {\text{%}} $ $t_{\rm{op }}/ {\rm{s}}$ ${C_{\max }} $ $\delta / {\text{%}} $ EX11 6.37 96 0 7.78 97 1.04 5.46 96 0 8.83 96 0 5.04 96 0 EX21 19.97 102 0 15.21 104 1.96 13.63 102 0 21.00 103 0.98 13.27 102 0 EX32 6.91 85 0 7.25 85 0 5.15 86 1.77 4.78 86 1.77 4.71 85 0 EX42 28.85 88 0 31.78 88 0 26.55 88 0 35.19 88 0 26.03 88 0 EX53 8.71 74 0 11.61 74 0 6.02 76 2.70 8.00 76 2.70 5.68 74 0 EX63 17.16 104 0.97 23.01 107 3.89 15.63 103 0 23.67 104 0.97 15.11 103 0 EX74 23.90 127 0 26.29 130 2.36 18.68 128 0.79 18.42 130 2.36 18.18 128 0.79 EX84 18.75 163 0 23.15 165 1.23 15.79 163 0 17.46 170 4.29 15.23 163 0 EX94 6.81 122 1.67 8.76 125 4.17 6.33 120 0 7.58 122 1.67 5.87 120 0 EX104 14.74 159 0 18.13 165 3.77 12.04 159 0 19.79 160 0.63 11.50 159 0 平均值 15.22 — 0.26 17.30 — 1.84 12.53 — 0.53 16.47 — 1.54 12.06 — 0.08