Meta-heurísticas para resolução de alguns problemas de planejamento e controle da produção - Bissoli, Dayan de Castro (2018)
This study addresses the resolution of three different problems, widely encountered in the real context of production planning and control. Initially, a GRASP metaheuristic is proposed to solve an assembly-line balancing problem (SALBP-2). The proposed method presented competitive results in relation to the literature, also focusing on a simplicity of operation to be applied in real cases. Subsequently, the same method was used to solve the Job Shop Scheduling Problem (JSP). The GRASP developed for the JSP also presented good results, with low average relative deviation in relation to the best solutions known in the literature. Next, we approached an extension of the JSP, the Flexible Job Shop Scheduling Problem (FJSP). The JSP is limited to the sequencing of operations on fixed machines, whereas in the FJSP the assignment of an operation is not preset and can thus be processed on a set of alternative machines. Therefore, the FJSP is not restricted to sequencing, extending in the assignment of operations to the appropriate machines (routing). The FJSP is more complex than the JSP because it considers the determination of the assignment of the machine for each operation. In order to solve the FJSP, we proposed four meta-heuristics: GRASP, Simulated Annealing (SA), Iterated Local Search (ILS) and Clustering Search (CS). SA presented lower results, however, incorporating it into a hybrid version of ILS, which uses it as a local search, the results improved, especially in more complex instances. Considering the hybrid characteristic of CS, the SA was also used, in this case as a solution-generating metaheuristic. This approach also presented superior results to SA. Both ILS and CS generated results with values equal to or close to those of the best known solutions for an extensive set of instances for the FJSP, as well as providing some new best known values.