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Abstract
The goal of the printed circuit board job-batching problem is to minimize the total manufacturing time required to process a set of printed circuit board jobs on an insertion machine. We have developed four families of heuristics to solve this problem: the clustering family, the bin-packing family, a family of sequencing genetic algorithms, and a grouping genetic algorithm. Within each family of heuristics, we developed several variations. Some of the variations use techniques from the literature and some of the techniques we developed specifically for this problem. We test the variations and select a good performer from each family.
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