Application of genetic algorithms with decision rules in stochastic u-shaped line balancing
Abstract
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.
Downloads
This work is licensed under a Creative Commons Attribution 4.0 International License.
In order to promote the development and dissemination of research in education in Latin America, the Ibero-American Journal for Educational Research and Development (RIDE) adhered to the Budapest Open Access Initiative, which is why it is identified as a Open access publication. This means that any user can read the complete text of the articles, print them, download them, copy them, link them, distribute them and use the contents for other purposes. Creative Cummons licenses allow users to specify the rights to use an open access journal available on the Internet in such a way that users know the rules of publication. Authors who publish in this journal accept the following conditions: Authors they keep the author's rights and give the magazine the right of the first publication, with the work registered with the attribution license of Creative Commons, which allows third parties to use the published material whenever they mention the authorship of the work and the first publication in this The authors can make other independent and additional contractual agreements for the non-exclusive distribution of the version of the article published in this journal (eg, include it in an institutional repository or publish it in a book) as long as they clearly indicate that The work was published for the first time in this magazine. Authors are allowed and recommended to publish their work. low on the Internet (for example on institutional or personal pages) before and during the review and publication process, as it can lead to productive exchanges and to a greater and faster dissemination of the published work
