Tabu search algorithms for an industrial multi-product and multi-objective assembly line balancing problem, with reduction of the task dispersion

This paper presents a real-world industrial application of the multi-product and multi-objective assembly line balancing problem, for a company involved in the production of four models of a white goods product. The problem solved is a GALBP-2, with 10 workstations and multiple objectives (to maximize the production rate in order to deal with an increase of the demand forecasted, to reach an equal cycle time of all the models and an equal workload of the different workstations, and finally, to minimize the dispersion of worker tasks on each one of the different models—the common tasks of the different models at the same workstation). The paper presents an integrated approach based on four heuristics cited in the literature and: (1) an improvement procedure based on tabu search, with the objective of minimizing the cycle time; and, subsequently, (2) a second tabu search in order to increase the uniformity of the tasks performed at each workstation (the common tasks at the same workstation).