COMBINATION OF ACO AND PSO TO MINIMIZE MAKESPAN IN ORDERED FLOWSHOP SCHEDULING PROBLEMS

The problem of scheduling flowshop production is one of the most versatile problems and is often encountered in many industries. Effective scheduling is important because it has a significant impact on reducing costs and increasing productivity. However, solving the ordered flowshop scheduling problem with the aim of minimizing makespan requires a difficult computation known as NP-hard. This research will contribute to the application of combination ACO and PSO to minimize makespan in the ordered flowshop scheduling problem. The performance of the proposed scheduling algorithm is evaluated by testing the data set of 600 ordered flowshop scheduling problems with various combinations of job and machine size combinations. The test results show that the ACO-PSO algorithm is able to provide a better scheduling solution for the scheduling group with small dimensions, namely 76 instances from a total of 600 inctances and is not good at obtaining makespan in the scheduling group with large dimensions. The ACO-PSO algorithm uses execution time which increases as the dimension size (multiple jobs and many machines) increases in a scheduled instanc

MRP and Scheduling integration: A case study for the food industry

En este proyecto, se estudió una empresa encargada de elaborar productos alimenticios, con un proceso de producción complejo. Esta empresa no dispone de herramientas o metodologías para analizar el comportamiento de las variables, que en la literatura son consideradas importantes para planificar adecuadamente un determinado período de tiempo. Por esta razón, el foco del proyecto está en la planificación y ejecución del proceso productivo de la empresa. Para solucionar este problema, se propone una secuencia que vincula la metodología de planeamiento con la metodología de ejecución, donde ambas tienen objetivos diferentes, pero sus resultados son utilizados para retroalimentar el proceso en general, logrando un mejor desempeño en la utilización de materias primas y la reducción de posibles faltantes, que al final influyen en la reducción de los costos de producción, generando mayores ganancias para la empresa. La secuencia parte del desarrollo por separado de herramientas, que en primer lugar dan solución a la planificación del abastecimiento de materias primas para atender la demanda prevista, y en segundo lugar, la creación de herramientas que establecen un plan de producción, indicando el orden de los trabajos a realizar y proporcionando una idea de la capacidad productiva actual de la empresa. Para comprobar la eficacia de las metodologías, se utilizaron los datos de la empresa relacionados con los tiempos de procesamiento de los puestos, las máquinas, las cantidades producidas para cada día y las demandas históricas de la empresa. Se analizaron todos esos datos y se construyó un modelo de simulación para ajustar la metodología final. De hecho, una parte importante del proceso fue el trabajo en colaboración con la empresa, ya que se recibió feedback a través de la comunicación de los resultados.In this project, a company in charge of producing food products, with a complex production process, was studied. This company does not have tools or methodologies to analyze the behavior of variables, which in the literature are considered important to adequately plan a specific period of time. For this reason, the focus of the project is on the planning and execution of the company's production process. To solve this problem, a sequence is proposed that links the planning methodology with the execution methodology, where both have different objectives, but their results are used to feed back the process in general, achieving a better performance in the use of raw materials and the reduction of possible shortages, which in the end influence the reduction of production costs, generating more profits for the company. The sequence starts from the separate development of tools, which firstly provide a solution to the planning of the supply of raw materials to meet the forecasted demand, and secondly, the creation of tools that establish a production plan, indicating the order of the work to be done and providing an idea of the current production capacity of the company. To test the effectiveness of the methodologies, company’s data related to processing times of the stations, machines, quantities produced for each day and the historical demands of the company was used. All those data were analyzed, and a simulation model was built to adjust the final methodology. Indeed, an important part of the process was the collaborative work with the company, since feedback was received through the communication of the results.Ingeniero (a) IndustrialPregrad