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An Efficient Algorithm for Placement Sequence and Feeder Assignment Problems With Multiple Placement-Nozzles and Independent Link Evaluation

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2 Author(s)
Gyorfi, J.S. ; Motorola Lab., Schaumburg ; Wu, C.-H.

We show that the genetic algorithm that Leu described to plan component placement sequences and feeder assignments for pick-and-place printed circuit board assembly tasks is a special case of a more general model that supports multiple placement-nozzles and independent feeder and board link (chromosome) evaluation methods. We also show that independent link evaluation can be used to offset a reduction in the parent link sample space and that these results are better than what can be achieved through link-pair evaluation. These generalizations extend the capabilities of the genetic algorithm to a broader range of manufacturing scenarios.

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Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on  (Volume:38 ,  Issue: 2 )