Abstract

FERMAN ALVAREZ, Demetrio et al. Application of genetic algorithms with decision rules in stochastic u-shaped line balancing. RIDE. Rev. Iberoam. Investig. Desarro. Educ [online]. 2023, vol.14, n.27, e522.  Epub Oct 27, 2023. ISSN 2007-7467.  https://doi.org/10.23913/ride.v14i27.1577.

Currently, most of the research on the assembly line balancing problem considers that the task times are determined. However, in manufacturing processes there is always the possibility of obtaining variations in the processes, these variations lead to variations in the task times, which leads to address this type of problem from a stochastic approach. This paper presents a method that uses metaheuristic techniques, through a genetic algorithm which aims to solve the problem of balancing type 1 of U-shaped lines with stochastic task times using existing problems in the literature and then make a comparison between the existing solutions.

Seven categories of problems solved by another method were used for the validation process. The solution provided by the algorithm was subjected to an experimental analysis of the data to check if it is capable of providing one or more solutions that are better than the existing ones, seeking to balance the line with the least amount of human resources possible. The results show better solutions for the high variance problems, only for the WS Major result a difference of 4% is observed, but in the remaining results the percentages are better. It can be observed that 6 better solutions were found than the existing ones.

Keywords : metaheuristic techniques; solution to the balancing problem; U-shaped lines; stochastics; validation.