DocumentCode
2974003
Title
Worker allocation in U-shaped assembly lines with multiple objectives
Author
Sirovetnukul, R. ; Chutima, P.
Author_Institution
Dept. of Ind. Eng., Mahidol Univ., Nakhonpathom, Thailand
fYear
2009
fDate
8-11 Dec. 2009
Firstpage
105
Lastpage
109
Abstract
The multi-objective worker allocation problems of single and mixed-model assembly lines having manually operated machines in several fixed U-shaped layouts are developed. Three objective functions are simultaneously minimized, i.e. number of workers, deviation of operation times of workers, and walking time. NSGA-II, an evolutionary optimization algorithm, searches only good solutions from the population, but a selection method should also discard the below-average solutions in order to avoid producing bad solutions. The COINcidence algorithm makes use of both good and not-good solutions with reward and punishment schemes to update a better generator. After getting the first objective of minimum number of workers, the rest are compared between NSGA-II and COIN in four measures for all testing problems. Each of the computational results gives a worker good task assignment and walking path. COIN is preferable to NSGA-II in most cases.
Keywords
assembling; combinatorial mathematics; evolutionary computation; mechanical stability; personnel; production control; COINcidence algorithm; NSGA-II; U-shaped assembly lines balancing problem; evolutionary optimization algorithm; mixed-model assembly lines; multiobjective worker allocation problems; punishment schemes; reward schemes; task assignment; walking path; Assembly systems; Evolutionary computation; Industrial engineering; Legged locomotion; Mass customization; Mass production; Optimization methods; Polynomials; Testing; Workstations; COIN; NSGA-II; U-shaped assembly lines; Worker allocation; multiple objectives;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-4869-2
Electronic_ISBN
978-1-4244-4870-8
Type
conf
DOI
10.1109/IEEM.2009.5373414
Filename
5373414
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