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An optimization algorithm for integrated remanufacturing production planning and scheduling system

机译:一种用于集成再制造生产规划和调度系统的优化算法

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It is known that production planning and scheduling are mutual influence and restriction. In this paper, we aim to obtain the minimum remanufacturing time of recycling parts by use of birandom variables and further optimize an integrated remanufacturing production planning and scheduling system under uncertain conditions. An integrated production planning and scheduling optimization model with birandom variable restraints is firstly established. Then we develop a hybrid intelligent algorithm including random simulation technique, neural network, and genetic algorithms to optimize an integrated remanufacturing production planning and scheduling system. Furthermore, we generate a random variable samples matrix through random simulation technique and a trained neural network is embedded into genetic algorithm. Finally, this hybrid intelligent algorithm is applied to optimize an integrated remanufacturing production planning and scheduling system through a case study. (C) 2017 Elsevier Ltd. All rights reserved.
机译:众所周知,生产规划和调度是相互影响和限制。在本文中,我们的目标是通过使用Birandom变量获得回收零件的最小再制造时间,并在不确定条件下进一步优化集成的再制造生产规划和调度系统。首先建立了具有Birandom可变束缚的集成生产规划和调度优化模型。然后我们开发一种混合智能算法,包括随机仿真技术,神经网络和遗传算法,以优化集成的再制造生产规划和调度系统。此外,我们通过随机仿真技术生成随机变量样本矩阵,培训的神经网络嵌入到遗传算法中。最后,应用这种混合智能算法通过案例研究来优化集成的再制造生产规划和调度系统。 (c)2017 Elsevier Ltd.保留所有权利。

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