Research on Production Balance Technology of Robotic Assembly Line Based on Fruit Fly Optimization Algorithm
To address the balancing problem of the robot bilateral assembly line, a mathematical model is constructed with cycle time and energy consumption as optimization objectives, subject to multiple constraints. This model is solved using an Improved Self-adaptive Fruit Fly Optimization Algorithm (ISFOA)...
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| Veröffentlicht in: | International Conference on Industrial Mechatronics and Automation (Online) S. 789 - 794 |
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| Sprache: | Englisch |
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IEEE
03.08.2025
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| ISSN: | 2152-744X |
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| Abstract | To address the balancing problem of the robot bilateral assembly line, a mathematical model is constructed with cycle time and energy consumption as optimization objectives, subject to multiple constraints. This model is solved using an Improved Self-adaptive Fruit Fly Optimization Algorithm (ISFOA). In the algorithm design, tent chaotic mapping is introduced during population initialization to ensure uniform distribution of the population. Additionally, an individual information utilization mechanism is incorporated, where there is an 80% probability of generating the next generation based on the global optimum and a 20% probability of generating it through random uniform perturbation of individuals, thereby fully utilizing population information. Simulated annealing-based multiple mutation rules and local perturbation are also integrated into the algorithm. Considering the characteristics of the model, a four-layer coding scheme is designed, and a decoding method is employed to achieve a better balance between local and global optima. Finally, the effectiveness of the proposed ISFOA algorithm for solving the Robotic Two-sided Assembly Line Balancing Problem of Type-2 (RTALBP-2) is verified by solving various cases of different scales and comparing its performance with other algorithms. |
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| AbstractList | To address the balancing problem of the robot bilateral assembly line, a mathematical model is constructed with cycle time and energy consumption as optimization objectives, subject to multiple constraints. This model is solved using an Improved Self-adaptive Fruit Fly Optimization Algorithm (ISFOA). In the algorithm design, tent chaotic mapping is introduced during population initialization to ensure uniform distribution of the population. Additionally, an individual information utilization mechanism is incorporated, where there is an 80% probability of generating the next generation based on the global optimum and a 20% probability of generating it through random uniform perturbation of individuals, thereby fully utilizing population information. Simulated annealing-based multiple mutation rules and local perturbation are also integrated into the algorithm. Considering the characteristics of the model, a four-layer coding scheme is designed, and a decoding method is employed to achieve a better balance between local and global optima. Finally, the effectiveness of the proposed ISFOA algorithm for solving the Robotic Two-sided Assembly Line Balancing Problem of Type-2 (RTALBP-2) is verified by solving various cases of different scales and comparing its performance with other algorithms. |
| Author | Liu, Kun Liu, Guanquan Jiao, Ying Wu, Yibo |
| Author_xml | – sequence: 1 givenname: Guanquan surname: Liu fullname: Liu, Guanquan email: lgq1971@163.com organization: College of Management Engineering, Qingdao University of Technology,Qingdao,Shandong,China – sequence: 2 givenname: Ying surname: Jiao fullname: Jiao, Ying email: jiojio1202@126.com organization: College of Management Engineering, Qingdao University of Technology,Qingdao,Shandong,China – sequence: 3 givenname: Kun surname: Liu fullname: Liu, Kun email: liukun2001@vip.qq.com organization: College of Management Engineering, Qingdao University of Technology,Qingdao,Shandong,China – sequence: 4 givenname: Yibo surname: Wu fullname: Wu, Yibo email: 1614491522@qq.com organization: College of Management Engineering, Qingdao University of Technology,Qingdao,Shandong,China |
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| Snippet | To address the balancing problem of the robot bilateral assembly line, a mathematical model is constructed with cycle time and energy consumption as... |
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| SubjectTerms | Assembly Assembly line balancing Convergence Encoding Energy consumption Fruit fly optimization algorithm Mathematical models Mixed-integer programming model Optimization Perturbation methods Production Programming Robot kinematics Robotic two-sided assembly line Sequence-dependent |
| Title | Research on Production Balance Technology of Robotic Assembly Line Based on Fruit Fly Optimization Algorithm |
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