Metaheurísticas para la programación de producción de la planta de la imprenta de billetes del banco de la república (2021)
Abstract This work proposes the investigation and implementation of three metaheuristics that allow solving the job scheduling and sequencing problem of Imprenta de Billetes del Banco de la República, which works under the Hybrid Flowshop with Missinging Operations system with the objective of minimizing the total time to complete all the jobs or Makespan, known for being an NP-Hard type problem. For this purpose, we compare the performance of the Simulated Annealing (SA), Greedy Randomized Adaptive Search Procedure (GRASP) and Biased Random-Keys Genetic Algorithm metaheuristics using the same scheduling procedure based on the NEH algorithm. Likewise, computational results are shown with respect to the solutions of an exact model to evaluate its efficiency on 30 randomly generated instances.