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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/sowvaovjz5h3hpgfua7tikprd4" style="color: black;">International Journal of Production Research</a>
We study the problem of sequencing mixed-model assembly lines operating with a heterogeneous workforce. The practical motivation for this study comes from the context of managing assembly lines in sheltered work centers for the disabled. We propose a general framework in which task execution times are both worker and model dependent. Within this framework, the problem is defined and mathematical mixed-integer models and heuristic procedures are proposed. These include a set of fast constructive<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1080/00207543.2014.987881">doi:10.1080/00207543.2014.987881</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bvgxpb5bjvaatcrf4qokcjfc2a">fatcat:bvgxpb5bjvaatcrf4qokcjfc2a</a> </span>
more »... heuristics, two local search procedures based on approximate measures using either a solution upper bound or the solution of a linear program and a GRASP metaheuristic. Computational tests with instances adapted from commonly used literature databases are used to validate the proposed approaches. These tests give insight on the quality of the di↵erent techniques, which prove to be very e cient both in terms of computational e↵ort and solution quality when compared to other strategies such as a random sampling or the solution of the MIP models using a commercial solver.
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