Multi-objective particle swarm optimization with negative knowledge for U-shaped assembly line worker allocation problems
A Single U-shaped Assembly Line (SUAL) is a type of Just-In-Time (JIT) production system where a variety of product models with similar product characteristics are assembled. Worker allocation to the SUAL is crucial to achieve the main benefits of JIT with the minimum of number of workers, equity of...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Published: |
2018
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| Online Access: | https://repository.li.mahidol.ac.th/handle/123456789/29062 |
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| Institution: | Mahidol University |
| Summary: | A Single U-shaped Assembly Line (SUAL) is a type of Just-In-Time (JIT) production system where a variety of product models with similar product characteristics are assembled. Worker allocation to the SUAL is crucial to achieve the main benefits of JIT with the minimum of number of workers, equity of workload and the shortest walking time. A novel algorithm, named Particle Swarm Optimization with Negative Knowledge (PSONK), is proposed to find the Pareto-optimal solutions for SUAL worker allocation problems with from seven to two hundred and ninety-seven tasks. The performance of PSONK are compared with Non-dominated Sorting Genetic Algorithm-II (NSGA-II) against the measures of convergence, spread, ratio of Pareto-optimal solutions, and CPU time. PSONK outperforms NSGA-II for most performance measures. ©2010 IEEE. |
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