In recent years, the flexible job shop scheduling problem (FJSP) has received a great deal of attention from researchers not only due to its complexity but also due to its wide range of applications in the industry. The FJSP extends the job shop scheduling problem (JSP) by allowing operations to be processed by a set of alternative machines. Many of the studies found in the literature consider the objective of minimizing the largest completion time of the jobs, that is, the makespan. However, in the real context of industries, considering more than one criterion is often relevant. Thus, the present work addresses two additional criteria besides the makespan: minimizing the maximum workload of the machines and minimizing the total workload of the machines. Aiming at real cases, where it is necessary to define priorities among the criteria, a clustering search (CS) algorithm was implemented using a lexicographic classification of the objectives for solving the multiobjective FJSP (MOFJSP). The results of this study show that compared to the state‐of‐the‐art approach, CS is an effective alternative to solve the MOFJSP.
O problema de layout em linha dupla (DRLP) consiste em determinar a localização de facilidades ao longo de ambos os lados de um corredor central, tendo como objetivo, a minimização da soma ponderada das distâncias entre todos os pares de facilidades. Como facilidades podem ser máquinas, centros de trabalho, células de manufatura, departamentos de um edifício e robôs em sistemas de manufatura. Esse trabalho propõe uma abordagem puramente heurística, baseada na meta-heurística Otimização do Enxame de Partículas (PSO). Para validar o algoritmo proposto, o mesmo foi submetido a testes computacionais com cinquenta e uma instâncias, incluindo instâncias consideradas de grande porte e os resultados encontrados mostram o PSO proposto como uma excelente abordagem para o DRLP, melhorado tendo os valores conhecidos para diversas instâncias disponíveis na literatura.
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