基于改进人工蜂群算法的云制造服务组合优化方法

doi:10.11959/j.issn.1000-436x.2023024

Abstract

Abstract:

To improve the optimization quality, efficiency and stability of cloud manufacturing service composition, a optimization method for cloud manufacturing service composition based on improved artificial bee colony algorithm was proposed.Firstly, three methods of service collaboration quality calculation under cloud manufacturing service composition scenario were put forward.Then, the optimization model with service collaboration quality was constructed.Finally, an artificial bee colony algorithm with multi-search strategy island model was designed to solve the optimal cloud manufacturing service composition.The experimental results show that the proposed algorithm is superior to the current popular improved artificial bee colony algorithms and other swarm intelligence algorithms in terms of optimization quality, efficiency and stability.

Key words: cloud manufacturing, service composition, process optimization, artificial bee colony

CLC Number:

TN92

Qiang HU, Yuqing TIAN, Haoquan QI, Peng WU, Qingxue LIU. Optimization method for cloud manufacturing service composition based on the improved artificial bee colony algorithm[J]. Journal on Communications, 2023, 44(1): 200-210.

Figures/Tables 18

名称	顺序结构	并行结构	选择结构	循环结构
MT	$\sum_{i = 1}^{n} MT (s_{i})$	max(MT(s_i))	max(MT(s_i))	$\sum_{i = 1}^{n} MT (s_{i})$
SC	$\sum_{i = 1}^{n} SC (s_{i})$	$\sum_{i = 1}^{n} SC (s_{i})$	max(SC(s_i))	$\sum_{i = 1}^{n} SC (s_{i})$
SP	$\frac{1}{n} \sum_{i = 1}^{n} SP (s_{i})$	$\frac{1}{n} \sum_{i = 1}^{n} SP (s_{i})$	min(SP(s_i))	$\frac{1}{n} \sum_{i = 1}^{n} SP (s_{i})$
SR	$\prod_{i = 1}^{n} SR (s_{i})$	min(SR(s_i))	min(SR(s_i))	$\prod_{i = 1}^{n} SR (s_{i})$

References 23

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算法	最差值	最优值	平均值	标准差
MGABC	2.71	3.07	2.94	0.102
MABCM	2.83	3.1	2.905	0.079
SFABC	2.74	3.12	2.869	0.105
IABC	2.71	3.12	2.918	0.148
MSSIABC	2.83	3.12	2.985	0.075
IGSA	2.73	3	2.857	0.099
SCRIHHO	2.7	3	2.825	0.113
GA-HH	2.65	3	2.825	0.093
A-NSGA-III	2.69	3.03	2.896	0.114

算法	最差值	最优值	平均值	标准差
MGABC	2.87	3.07	2.952	0.074
MABCM	2.9	3.12	2.99	0.076
SFABC	2.73	3.02	2.898	0.088
IABC	2.73	3.04	2.91	0.12
MSSIABC	2.98	3.14	3.039	0.07
IGSA	2.7	3.03	2.862	0.111
SCRIHHO	2.72	3.05	2.855	0.098
GA-HH	2.68	3.03	2.845	0.113
A-NSGA-III	2.75	3.09	2.933	0.116

算法	最差值	最优值	平均值	标准差
MGABC	2.87	3.09	2.995	0.073
MABCM	2.92	3.12	3.011	0.803
SFABC	2.8	3.12	2.918	0.099
IABC	2.73	3.03	2.918	0.132
MSSIABC	3	3.14	3.09	0.067
IGSA	2.74	2.99	2.81	0.077
SCRIHHO	2.76	3.01	2.856	0.070
GA-HH	2.85	3.01	2.918	0.059
A-NSGA-III	2.84	3.08	2.927	0.079

算法	最差值	最优值	平均值	标准差
MGABC	2.71	3.14	2.859	0.14
MABCM	2.9	3.09	2.967	0.073
SFABC	2.83	3.02	2.896	0.069
IABC	2.8	3.12	2.97	0.130
MSSIABC	2.97	3.15	3.07	0.064
IGSA	2.75	3.04	2.85	0.096
SCRIHHO	2.66	3.01	2.838	0.094
GA-HH	2.81	3.01	2.922	0.660
A-NSGA-III	2.85	3.08	2.945	0.073

Optimization method for cloud manufacturing service composition based on the improved artificial bee colony algorithm

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