This work examines a balancing problem wherein the objective is to minimize both the ergonomic risk dispersion between the set of workstations of a mixed-model assembly line and the risk level of the workstation with the greatest ergonomic factor. A greedy randomized adaptive search procedure (GRASP) procedure is proposed to achieve these two objectives simultaneously. This new procedure is compared against two mixed integer linear programs: the MILP-1 model that minimizes the maximum ergonomic risk of the assembly line and the MILP-2 model that minimizes the average deviation from ergonomic risks of the set of workstations on the line. The results from the case study based on the automotive sector indicate that the proposed GRASP procedure is a very competitive and promising tool for further research.
Progress in Artificial Intelligence – Springer Journals
Published: Jun 5, 2018
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