Review on bio-inspired algorithms approach to solve assembly line balancing problem
Bio-inspired algorithms that have been developed by mimicking the biological phenomenon of nature have been widely applied to solve many real-world problems. For example, memetic algorithm, EGSJAABC3 to optimize economic environmental dispatch (EED), Hybrid Pareto Grey Wolf Optimization to minimize...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
Universiti Malaysia Pahang
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/27129/13/Review%20on%20bio-inspired%20algorithms%20approach.pdf |
| Summary: | Bio-inspired algorithms that have been developed by mimicking the biological phenomenon of nature have been widely applied to solve many real-world problems. For example, memetic algorithm, EGSJAABC3 to optimize economic environmental dispatch (EED), Hybrid Pareto Grey Wolf Optimization to minimize carbon and noise emission in U-shaped robotic assembly line and Polar Bear Optimization to optimize heat production. The results obtained form their research have clearly portrayed the robustness of bio-inspired algorithms to solve complex problems. This paper highlights the efficiencies of bio-inspired algoritms implemented in solving assembly line balancing problem. Assembly line balancing problem is very crucial to solve since it involves minimizing the time of the machines and operators that required optimal task distribution. The outcome of this paper shows the effectiveness of bio-inspired algorithms in solving assembly line balancing problem compared to traditional method. |
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