Publication:
Multi-objective particle swarm optimization with negative knowledge for U-shaped assembly line worker allocation problems

dc.contributor.authorR. Sirovetnukulen_US
dc.contributor.authorP. Chutimaen_US
dc.contributor.otherMahidol Universityen_US
dc.contributor.otherChulalongkorn Universityen_US
dc.date.accessioned2018-09-24T08:59:10Z
dc.date.available2018-09-24T08:59:10Z
dc.date.issued2010-12-01en_US
dc.description.abstractA 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.en_US
dc.identifier.citationIEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management. (2010), 2033-2038en_US
dc.identifier.doi10.1109/IEEM.2010.5674252en_US
dc.identifier.other2-s2.0-78751683918en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/29062
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78751683918&origin=inwarden_US
dc.subjectEngineeringen_US
dc.titleMulti-objective particle swarm optimization with negative knowledge for U-shaped assembly line worker allocation problemsen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78751683918&origin=inwarden_US

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