首页> 外文会议>International Conference on Modeling, Optimization, and Computing >Multi-objective and Perishable Fuzzy InventoryModels Having Weibull Life-time With TimeDependent Demand, Demand DependentProduction and Time Varying Holding Cost: APossibility/Necessity Approach
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Multi-objective and Perishable Fuzzy InventoryModels Having Weibull Life-time With TimeDependent Demand, Demand DependentProduction and Time Varying Holding Cost: APossibility/Necessity Approach

机译:多目标和易腐模糊库存模型,具有时间依赖性需求的威布尔寿命,需求依赖性生产和时间各种持有成本:绝对性/必要性方法

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A multi-objective inventory model of deteriorating item has been developed with Weibull rate of decay, time dependent demand, demand dependent production, time varying holding cost allowing shortages in fuzzy environments for non- integrated and integrated businesses. Here objective is to maximize the profit from different deteriorating items with space constraint. The impreciseness of inventory parameters and goals for non-integrated business has been expressed by linear membership functions. The compromised solutions are obtained by different fuzzy optimization methods. To incorporate the relative importance of the objectives, the different cardinal weights crisp/fuzzy have been assigned. The models are illustrated with numerical examples and results of models with crisp/fuzzy weights are compared. The result for the model assuming them to be integrated business is obtained by using Generalized Reduced Gradient Method (GRG). The fuzzy integrated model with imprecise inventory cost is formulated to optimize the possibility necessity measure of fuzzy goal of the objective function by using credibility measure of fuzzy event by taking fuzzy expectation. The results of crisp/fuzzy integrated model are illustrated with numerical examples and results are compared.
机译:衰减物品的多目标库存模型已经采用Weibull衰减,时间依赖性需求,需求依赖性生产,时间随着非整合和综合业务的模糊环境中的短缺而变化。目的是利用空间约束来最大化不同恶化项目的利润。线性成员函数表示,库存参数和非综合业务目标的不精确性。受损解决方案是通过不同的模糊优化方法获得的。为了纳入目标的相对重要性,已经分配了不同的主要重量清脆/模糊。该模型用数字示例进行说明,并比较了具有清晰/模糊重量的模型的结果。假设它们是通过使用广义的减少的梯度方法(GRG)获得集成业务的模型的结果。具有不精确库存成本的模糊综合模型被制定为优化目标函数的可能性必要性测量目标函数的模糊目标通过采取模糊期望来衡量模糊事件的可信度。清晰/模糊集成模型的结果用数值例子说明并进行了比较结果。

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