Hybrid Colonial Competitive Algorithm for the Two-sided Assembly Line Balancing Problem with Multiple Constraints

doi:10.3901/JME.2015.02.183

Journal of Mechanical Engineering ›› 2015, Vol. 51 ›› Issue (2): 183-189.doi: 10.3901/JME.2015.02.183

Previous Articles Next Articles

Hybrid Colonial Competitive Algorithm for the Two-sided Assembly Line Balancing Problem with Multiple Constraints

LI Dashuang¹ZHANG Chaoyong¹SHAO Xinyu¹YUAN Biao²TANG Qiuhua³

State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074;Department of Industrial Engineering and Logistics Management, Shanghai Jiao Tong University, Shanghai 200240;College of Mechanical Automation, Wuhan University of Science and Technology, Wuhan 430081

Online:2015-01-20 Published:2015-01-20

Abstract

Abstract: In view of the special constraints such as operational direction constraint, precedence constraint, positional constraint, zoning constraint and synchronous constraint in the two-sided assembly line balancing problem, the characteristics of every constraint and the special requirements of task assignment are analyzed, and the corresponding mathematical model is built. A colonial competitive algorithm is proposed according to the model. To make every task sequence meet the precedence constraint, the binary tree adjustment algorithm is proposed. The efficiency of assigning the task only in the feasible solution space is improved. The LAHC algorithm is added in the algorithm as a local search algorithm, to improve the global search of the algorithm. Experiments are carried out to demonstrate the performance of the proposed method.

Key words: colonial competitive algorithm, late acceptance hill-climbing, multiple constraints, two-sided assembly line

CLC Number:

TP18

LI Dashuang, ZHANG Chaoyong, SHAO Xinyu, YUAN Biao, TANG Qiuhua. Hybrid Colonial Competitive Algorithm for the Two-sided Assembly Line Balancing Problem with Multiple Constraints[J]. Journal of Mechanical Engineering, 2015, 51(2): 183-189.

[1]	ZHU Haihua, WANG Jianjie, LI Fei, LIU Changchun, CAI Qixiang. Workshop Order Remaining Completion Time Prediction Based on the Feature Selection and SSA-LSTM [J]. Journal of Mechanical Engineering, 2024, 60(20): 388-402.
[2]	LI Zhipeng, MA Tianyu, LIU Jinping, XIANG Qingsong, TANG Junjie. Multi-source Domain Adaptation Intelligent Fault Diagnosis Method Based on Asymmetric Adversarial Training [J]. Journal of Mechanical Engineering, 2024, 60(18): 76-88.
[3]	WANG Jun, YANG Yiqing, LIU Jinzhao, SHEN Changqing, HUANG Weiguo, ZHU Zhongkui. Interpretable Intelligent Diagnosis Based on Wavelet Kernel Encoded Spiking Convolutional Neural Networks [J]. Journal of Mechanical Engineering, 2024, 60(12): 41-50.
[4]	LIN Chen, HE Zhicheng, HUANG Yifei, LIN Zhigui, FU Guang, HUANG Jin. Research on Detection Method for Driving Scenarios Based on Multi-stage Parameter Fusion Network [J]. Journal of Mechanical Engineering, 2024, 60(10): 64-75.
[5]	SU Jiantao, DONG Shaohua, ZHU Shimin. Research on Machine Fault Rescheduling Problem of Multi Objective Hybrid Flow Shop Based on Intelligent Manufacturing [J]. Journal of Mechanical Engineering, 2024, 60(4): 438-448.
[6]	JIANG Zhoumingju, XIONG Yi, WANG Baicun. Human-machine Collaborative Additive Manufacturing for Industry 5.0 [J]. Journal of Mechanical Engineering, 2024, 60(3): 238-253.
[7]	GU Wenbin, LI Yuxin, LIU Siqi, YUAN Minghai, PEI Fengque. Research on Data-driven Real-time Scheduling Method of Smart Workshop [J]. Journal of Mechanical Engineering, 2023, 59(12): 47-61.
[8]	LIU Qiong, LIU Jiahao, LIU Jialiang. Integrated Optimization of Preventive Maintenance and Flexible Job Shop Group Scheduling Based on an ABC-AN Algorithm [J]. Journal of Mechanical Engineering, 2023, 59(12): 89-96.
[9]	WU Qiangewei, WEN Long. Union-adversarial Training for Deep Learning based on Surface Defect Detection [J]. Journal of Mechanical Engineering, 2023, 59(12): 173-182.
[10]	SHEN Tianhao, DING Kang, LI Jie, HUANG Ruyi, LI Weihua. Graph Structure and Temporal Data Driven Remaining Useful Life Prediction Method for Machinery [J]. Journal of Mechanical Engineering, 2023, 59(12): 183-194.
[11]	HE Yunze, LI Xiang, WANG Hongjin, HOU Yuejun, ZHANG Fan, MU Xinying, LIU Hao, CHENG Hao, LI Shihua, LI Jie. A Review: Full-cycle Nondestructive Testing Based on Visible Light and Thermography of Wind Turbine Blade [J]. Journal of Mechanical Engineering, 2023, 59(6): 32-45.
[12]	YAO Xifan, MA Nanfeng, ZHANG Cunji, ZHOU Jiajun. Human-centric Smart Manufacturing: Evolution and Outlook [J]. Journal of Mechanical Engineering, 2022, 58(18): 2-15.
[13]	MA Nanfeng, YAO Xifan, CHEN Feixiang, YU Hongjun, WANG Kesai. Human-centric Smart Manufacturing for Industry 5.0 [J]. Journal of Mechanical Engineering, 2022, 58(18): 88-102.
[14]	HUANG Sihan, WANG Baicun, ZHANG Meidi, HUANG Jintang, ZHU Qizhang, YANG Geng. Operator 4.0 Towards Human-centric Smart Manufacturing: Framework, Enabling Technologies and Typical Scenarios [J]. Journal of Mechanical Engineering, 2022, 58(18): 251-264.
[15]	YANG Geng, ZHOU Huiying, WANG Baicun. Digital Twin-driven Smart Human-machine Collaboration: Theory, Enabling Technologies and Applications [J]. Journal of Mechanical Engineering, 2022, 58(18): 279-291.

Hybrid Colonial Competitive Algorithm for the Two-sided Assembly Line Balancing Problem with Multiple Constraints

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments