Minimization of Makespan Using FCFS Method and Genetic Algorithm Method Comparison in Aluminum Industry

Abstract

Companies that produce Aluminum are experiencing rapid development. The company uses a flow shop system and the demand type is make to order. In the scheduling system the company currently uses First Come First Served (FCFS). The company still finds an improper quantity schedules, which results in a large amount of makespan and causes inaccurate product delivery schedules for consumers. The study was conducted to find the optimal sequence of scheduling with makespan minimization criteria by the genetic algorithm method and FCFS method comparison. The FCFS method used by the company produces makespan of 55,970 hours when the Genetic Algorithm method produces makespan of 46,637 hours. The recommendation method has a better performance level compared to the company shown in efficiency index (EI). The EI value of the Genetic Algorithm method is 1,20 (EI> 1) which shows that the Genetic Algorithm has good performance compared to the FCFS method. The calculation of the value of Relative Error (RE) shows that the saving of makespan obtained by the Genetic Algorithm method with the FCFS method is 20,13%. The conclusion is that the Genetic Algorithm method produces the minimum makespan value with a reduction of makespan of 9,33 hours. The schedule obtained using the Genetic Algorithm method is Job 2 - Job 3 - Job 1-Job 5 and Job 4. Job on the floor based on products section that produces in this industry. Jobs mean profile of aluminum that produced.