Hybrid approach for machine scheduling optimization in custom furniture industry

TítuloHybrid approach for machine scheduling optimization in custom furniture industry
AutoresJ.C. Vidal, M. Mucientes, A. Bugarín, M. Lama, Reza Sadigh Balay
TipoComunicación para congreso
Fonte 8th International Conference on Hybrid intelligent systems, Barcelona, Spain, 2008.
AbstractMachine scheduling is a critical problem in industries where products are custom-designed. The wide range of products, the lack of previous experiences in manufacturing, and the several conflicting criteria used to evaluate the quality of the schedules define a huge search space. Furthermore, production complexity and human influence in each manufacturing step make time estimations difficult to obtain thus reducing accuracy of schedules. The solution described in this paper combines evolutionary computing and neural networks to reduce the impact of (i) the huge search space that the multi-objective optimization must deal with and (ii) the inherent problem of computing the processing times in a domain like custom manufacturing. Our hybrid approach obtains near optimal schedules through the Non-dominated Sorting Genetic Algorithm II (NSGA-II) combined with time estimations based on multilayer perceptron networks.
Palabras chavescheduling, optimization, evolutionary computing, neural networks