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An optimal order quantity model for multi-products with uncertain arrival time

机译:到达时间不确定的多产品最优订货量模型

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Based on the analysis and summary of the features of supply chain components as well as the sales company itself, the problem of allocating order quantity of multi-products in several periods with an uncertain arrival time is investigated for a sales company. A concept of random fuzzy arrival rate is proposed to describe the uncertainty of the arrival time effectively, and the customer satisfaction is guaranteed by a transfer strategy. Considering all the factors including order costs, inventory costs, and transfer costs, a random fuzzy optimal order quantity model of multi-products with uncertain arrival time is established to minimize the total costs with constraints of purchase quantity, inventory capacity and current capitals based on the random fuzzy theory in uncertain theory. The multi-products optimal order quantity model with a random fuzzy variable is transferred into a random fuzzy expected value model to calculate the solutions. Genetic Algorithm is employed to solve the problem according to the characteristics and complexity of the solution. Simulation experiments were conducted using practical data of a sales company, and the results verified the effectiveness and efficiency of the proposed model and the solving algorithm.
机译:在对供应链组件特征以及销售公司自身进行分析和总结的基础上,研究了销售公司不确定到达多个时间段内的多产品订单数量分配问题。提出了一种随机模糊到达率的概念来有效描述到达时间的不确定性,并通过转移策略来保证顾客满意度。考虑到订单成本,库存成本和转移成本等所有因素,建立了具有不确定到达时间的多产品随机模糊最优订货数量模型,以基于采购数量,库存能力和流动资金约束的总成本最小化不确定理论中的随机模糊理论。将具有随机模糊变量的多产品最优订单量模型转换为随机模糊期望值模型以计算解。根据解决方案的特点和复杂性,采用遗传算法解决问题。利用销售公司的实际数据进行了仿真实验,结果验证了所提模型和求解算法的有效性和有效性。

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