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• W2774422817 abstract "Abstract Industry 4.0 is widely accepted in manufacturing industry since it guides a novel and promising production paradigm. A new characteristic in Industry 4.0-based manufacturing systems is that the applications of advanced intelligent machines which have communication, self-optimization and self-training behaviors. Based on this new change, this study investigates a flow-shop scheduling problem under the consideration of multiple objectives, time-dependent processing time and uncertainty. A mixed integer programming model is formulated for this problem, and a fireworks algorithm is developed where some special strategies are designed, e.g., explosion sparks procedure and selection solution procedure. Simulation experiments on a set of test problems are carried out, and the experimental results demonstrate that the model and proposed algorithm can achieve a satisfactory performance by comparing with three state-of-the-art multi-objective optimization algorithms." @default.
• W2774422817 created "2017-12-22" @default.
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• W2774422817 date "2018-07-01" @default.
• W2774422817 modified "2023-10-01" @default.
• W2774422817 title "Two-objective stochastic flow-shop scheduling with deteriorating and learning effect in Industry 4.0-based manufacturing system" @default.
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• W2774422817 doi "https://doi.org/10.1016/j.asoc.2017.12.009" @default.
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