Um estudo comparativo entre soluções aplicadas a um problema de flow line misto

Abstract

This paper presents the Mixed-Model Flow Line problem for Production Scheduling. Production problems have been vastly studied given their usability in all kind of assembly lines and its production in the industry worldwide. The problem processes jobs grouped by families in stations of machines seeking for the best sequencing the families can provide to be produced in the processing time (Makespan). In this work, a bibliographic review was performed to support the study, looking different methods and problems that encompass the Mixed-Model Flow Line in the literature showing its importance towards the industrial and scientific environment. The Mixed-Model Flow Line problem was solved through optimization techniques: An integer lienar programming inGUROBI, Lagrangian Relaxation and Genetic Algorithm. The processing times and demands are randomly generated for each instance. Finally, the results obtained in the techniques used for the problem were compared to each other.