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首页> 外文期刊>International Journal of Computer Integrated Manufacturing >Multi-objective multi-product multi-site aggregate production planning in a supply chain under uncertainty: fuzzy multi-objective optimisation
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Multi-objective multi-product multi-site aggregate production planning in a supply chain under uncertainty: fuzzy multi-objective optimisation

机译：不确定条件下供应链中的多目标多产品多站点总体生产计划：模糊多目标优化

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摘要

The existing technology is advancing into specialisation and globalisation. To survive in global competition, manufacturers should be responsible to consumer demands in different situations that are possible through efficient production planning. Due to the interaction of manufacturing components with each other, supply chain (SC) planning is an efficient approach. The sensitivity of such planning will be increased when a manufacturer is faced with fluctuations in demands. This article presents a mathematical model for production planning in a SC under demand uncertainty and solves it by a fuzzy multi-objective optimisation method. This model is formulated as multi-objective mixed-integer non-linear programming with conflicting objective functions. To release the sensitivity or different reactions of the system in terms of diverse uncertainty values, fuzziness is also considered in the inequalities of a constraint that includes an uncertain demand. The proposed method converts the non-linear model to the linear one and then transforms the fuzzy model to the parametric deterministic model. To show the effectiveness and validity of the presented model, a case study is carried out and the results obtained from GAMS software are shown. Finally, the conclusion is provided.
机译：现有技术正在向专业化和全球化发展。为了在全球竞争中生存，制造商应负责通过有效的生产计划在不同情况下满足消费者的需求。由于制造组件之间的相互影响，供应链（SC）计划是一种有效的方法。当制造商面临需求波动时，这种计划的敏感性将会提高。本文提出了需求不确定情况下供应链工厂生产计划的数学模型，并通过模糊多目标优化方法对其进行求解。该模型被公式化为具有冲突目标函数的多目标混合整数非线性规划。为了释放系统在各种不确定性值方面的敏感性或不同反应，在包括不确定性需求的约束的不等式中也考虑了模糊性。该方法将非线性模型转换为线性模型，然后将模糊模型转换为参数确定性模型。为了显示所提出模型的有效性和有效性，进行了案例研究，并显示了从GAMS软件获得的结果。最后，提供了结论。

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