Robust assembly line balancing with heterogeneous workers. Moreira, M., C., O., Cordeau, J., Costa, A., M., & Laporte, G. Computers & Industrial Engineering, 88:254-263, 2015. ![Robust assembly line balancing with heterogeneous workers [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website doi abstract bibtex Assembly lines are manufacturing systems in which a product is assembled progressively in workstations by different workers or machines, each executing a subset of the needed assembly operations (or tasks). We consider the case in which task execution times are worker-dependent and uncertain, being expressed as intervals of possible values. Our goal is to find an assignment of tasks and workers to a minimal number of stations such that the resulting productivity level respects a desired robust measure. We propose two mixed-integer programming formulations for this problem and explain how these formulations can be adapted to handle the special case in which one must integrate a particular set of workers in the assembly line. We also present a fast construction heuristic that yields high quality solutions in just a fraction of the time needed to solve the problem to optimality. Computational results show the benefits of solving the robust optimization problem instead of its deterministic counterpart.
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abstract = {Assembly lines are manufacturing systems in which a product is assembled progressively in workstations by different workers or machines, each executing a subset of the needed assembly operations (or tasks). We consider the case in which task execution times are worker-dependent and uncertain, being expressed as intervals of possible values. Our goal is to find an assignment of tasks and workers to a minimal number of stations such that the resulting productivity level respects a desired robust measure. We propose two mixed-integer programming formulations for this problem and explain how these formulations can be adapted to handle the special case in which one must integrate a particular set of workers in the assembly line. We also present a fast construction heuristic that yields high quality solutions in just a fraction of the time needed to solve the problem to optimality. Computational results show the benefits of solving the robust optimization problem instead of its deterministic counterpart.},
bibtype = {article},
author = {Moreira, Mayron César O. and Cordeau, Jean-François and Costa, Alysson M. and Laporte, Gilbert},
doi = {10.1016/j.cie.2015.07.004},
journal = {Computers & Industrial Engineering}
}
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