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An inventory model for deteriorating items with inflation induced variable demand under two level partial trade credit: A hybrid ABC-GA approach

机译:具有两级部分贸易信贷的具有通胀导致可变需求的变质物品库存模型:混合ABC-GA方法

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In this research work an inventory model of a deteriorating item is considered under two level partial trade credit policy incorporating inflation and time value of money in a finite planning horizon. Here it is assumed that a wholesaler offers a partial trade credit to a retailer i.e., trade credit period is offered on an portion of the total purchase amount. In turn the retailer also offers a partial trade credit to its customers. Demand of the item linearly decreases with time and influenced by unit selling price of the item. As selling price is influenced by the inflation and time value of money, so the base demand depends on inflation and bank interest rate also. The retailer also introduces some promotional cost to boost the demand of the item. Under this circumstances, marketing decisions are made to maximize the present value of the total profit. On the other hand combining the features of artificial bee colony (ABC) and genetic algorithm (GA), a hybrid algorithm, artificial bee genetic algorithm (ABGA) has been developed to find the most appropriate business strategies for the proposed model. Efficiency of this algorithm is tested and compared with some ABC variants using a set of benchmark test functions. The model has been illustrated with several numerical examples and some managerial insights are outlined.
机译:在这项研究工作中,在有限计划范围内考虑了通货膨胀和货币时间价值的两级部分贸易信贷政策下,考虑了恶化项目的库存模型。这里假设批发商向零售商提供了部分贸易信贷,即,贸易信贷期是以总购买金额的一部分提供的。反过来,零售商也向其客户提供部分贸易信贷。物品的需求随时间线性下降,并受物品的单价影响。由于售价受通货膨胀和货币时间价值的影响,因此基本需求也取决于通货膨胀和银行利率。零售商还引入了一些促销费用以提高商品的需求。在这种情况下,将做出营销决策以使总利润的现值最大化。另一方面,结合人工蜂群(ABC)和遗传算法(GA)的特点,开发了一种混合算法,人工蜂遗传算法(ABGA),以为该模型找到最合适的商业策略。测试了该算法的效率,并使用一组基准测试功能将其与某些ABC变体进行了比较。通过几个数值示例对模型进行了说明,并概述了一些管理方面的见解。

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