Website 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.

@article{ title = {Robust assembly line balancing with heterogeneous workers}, type = {article}, year = {2015}, identifiers = {[object Object]}, pages = {254-263}, volume = {88}, websites = {http://www.sciencedirect.com/science/article/pii/S0360835215003058}, id = {39ee30c9-864f-3359-a4d7-e28e77b88de7}, created = {2016-11-23T13:41:05.000Z}, accessed = {2016-11-23}, file_attached = {false}, profile_id = {134948fe-4bf0-3f08-9d61-f6cc9d0cdcb8}, last_modified = {2017-03-15T01:49:32.045Z}, read = {false}, starred = {false}, authored = {true}, confirmed = {true}, hidden = {false}, citation_key = {MoreiraEtAl_2015_caie}, private_publication = {false}, 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}, journal = {Computers & Industrial Engineering} }

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