Una metodología multiobjetivo para optimizar un ambiente job shop

Abstract

The development of a methodology that contains a metaheuristic model based on the Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II) in a job shop production environment. This is to minimize three main process variables: total time of processing (makespan time), energy cost and labor accidents. With the application of this methodology, the variables under study were optimized in 42%, compared with traditional production programming techniques. Based on the application of the proposed methodology, it is suggested to explore other multi objective functions in which the consumption of other resources, such as water and fuel can be analyzed in undesirable situations such as transport strike, landslides and traffic congestion.