Scheduling flow shops with multiple processors: a flexible ANN-fuzzy simulation approach

Authors:
Ali Azadeh;Mohsen Moghaddam;Pegah Geranmayeh;Arash Naghavi
Affiliations:
University of Tehran, Tehran, Iran;University of Tehran, Tehran, Iran;University of Tehran, Tehran, Iran;University of Tehran, Tehran, Iran
Venue:
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
Year:
2010

Citing 5
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Abstract

In this study, a flexible artificial neural network (ANN)-fuzzy simulation algorithm is proposed for solving the multi-attribute combinatorial dispatching (MACD) decision problem. Multi-layered ANN as a commonly used meta-heuristic is employed for solving this complex optimization problem. Fuzzy simulation is used to solve complex optimization problems to deal with imprecision and uncertainty. The proposed flexible algorithm is capable of modeling a non-linear and stochastic problem which uses ANN simulation for crisp input data and fuzzy simulation for fuzzy input data. The solution quality is illustrated by a case study from a multi-layer ceramic capacitor (MLCC) manufacturing plant. The manufacturing lead times (MLT) produced by the flexible ANN-fuzzy simulation model turned out to be superior to conventional simulation model.