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- W2345328535 abstract "This paper presents a new bi-objective mixed integer programming model for the two-stage assembly flow shop scheduling problem with preventive maintenance (PM) activities, in which the reliability/availability approach is employed to model the maintenance concepts of a problem. PM activities carry out the operations on machines and tools before the breakdown takes place. Therefore, it helps to prevent failures before they happen. After developing a new bi-objective model, an Epsilon-constraint method is proposed to solve the problem. This problem has been known as Np-hard. Therefore, three multi-objective optimization methods, namely fast non-dominated sorting genetic algorithm, Multi-objective imperialist competitive algorithm, and non-dominated ranking genetic algorithm (NRGA) are employed to find the pareto-optimal front for large sized problems. The parameters of the proposed algorithms are calibrated using artificial neural network (ANN) and the performances of the proposed algorithms on the problems..." @default.
- W2345328535 created "2016-06-24" @default.
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- W2345328535 date "2016-05-02" @default.
- W2345328535 modified "2023-09-25" @default.
- W2345328535 title "Bi-objective optimization for integrating production and preventive maintenance scheduling in two-stage assembly flow shop problem" @default.
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- W2345328535 doi "https://doi.org/10.1080/21681015.2016.1173599" @default.
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