Model and heuristics for the multi-manned assembly line worker integration and balancing problem
Adalberto Sato Michels, Alysson M. Costa
Abstract
This paper examines the balancing of assembly lines with multi-manned stations and a heterogeneous workforce.Both topics received considerable attention in the literature, but not in an integrated fashion.Combining these two characteristics gives rise to a highly combinatorial Multi-manned Assembly Line Worker Integration and Balancing Problem.When considering multimanned stations, the already coupled decisions on assigning tasks to heterogeneous workers and workers to stations must be further linked with task scheduling assessments.We propose a Mixed-Integer Linear Programming model and develop two heuristic solution procedures, which tackle the problem with a hierarchical decomposition approach.Computational tests on a large dataset indicate that the proposed method can obtain good primal bounds in short computational times.We demonstrate that these results can be applied to the monolithic model either as a warm start or in a proximity search procedure to obtain synergistic gains with statistically significant differences.From a managerial perspective, we show that multi-manned stations can reduce the assembly line's length even in the presence of a heterogeneous workforce, which is crucial for many industries manufacturing large-size products.