A nondominated sorting ant colony optimization algorithm for complex assembly line balancing problem incorporating incompatible task sets
Two-sided assembly lines are heavily used in automotive industry for producing large-sized products such as buses, trucks and automobiles. Mixed-model lines help manufacturers satisfy customized demands at a reasonable cost with desired quality. This paper addresses to mixed-model two-sided lines in...
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| Format: | Article |
| Language: | English |
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Pamukkale University
2018-02-01
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| Series: | Pamukkale University Journal of Engineering Sciences |
| Subjects: | |
| Online Access: | https://dergipark.org.tr/tr/pub/pajes/issue/35876/400852 |
| Summary: | Two-sided
assembly lines are heavily used in automotive industry for producing
large-sized products such as buses, trucks and automobiles. Mixed-model lines
help manufacturers satisfy customized demands at a reasonable cost with desired
quality. This paper addresses to mixed-model two-sided lines incorporating
incompatible task groups and proposes a new method for minimizing two
conflicting objectives, namely cycle time and the number of workstations, to
maximize line efficiency. While such an approach yields to a so-called type-E
problem in the line balancing domain, the proposed nondominated sorting ant
colony optimization (NSACO) approach provides a set of solutions dominating
others in terms of both objectives (pareto front solutions). The solution which
has the highest line efficiency among pareto front solutions is then determined
as the best solution. An additional performance criterion is also applied when
two different solutions have the same values for both objectives. The solution
which has the smoother workload distribution is favoured when both criteria are
the same. NSACO is described and a numerical example is provided to exhibit its
running mechanism. The performance of the algorithm is tested through test
problems in two conditions, i.e. incompatible task sets are considered and not
considered, and computational results are presented for the first time. The
results indicate that NSACO has a promising solution capacity. |
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| ISSN: | 1300-7009 2147-5881 |