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A two-warehouse EOQ model with interval-valued inventory cost and advance payment for deteriorating item under particle swarm optimization

机译:一个双仓库EOQ模型,间隔值库存成本和粒子群优化下的劣化项目的预付款

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摘要

Generally, most of the inventory costs are not always fixed due to uncertainty of competitive market. In the existing literature, it is found that several researchers have worked on uncertainty considering inventory parameters as fuzzy valued. In this work, we have represented the inventory parameters as interval. Using this concept, we have developed a two-warehouse inventory model with advanced payment, partial backlogged shortages. Due to uncertainty, this problem cannot be solved by existing direct/indirect optimization technique. For this purpose, different variants of particle swarm optimization techniques (viz. PSO-CO, WQPSO and GQPSO) have been developed to solve the problem of the proposed inventory model by using interval arithmetic and interval order relations. Finally, to illustrate and also to validate the proposed model, a numerical example has been solved and the best found solutions (which is either optimal solution or near optimal solution) obtained from different variants of PSO have been compared. Then, a sensitivity analysis has been performed to study the effect of changes of different parameters of the model on the optimal policy.
机译:通常,由于竞争市场的不确定,大多数库存成本并不总是固定的。在现有文献中,发现有几位研究人员在考虑库存参数作为模糊值的情况下致力于不确定性。在这项工作中,我们将清单参数表示为间隔。使用这一概念,我们开发了一个双仓库库存模型,具有先进的付款,部分积压短缺。由于不确定性,此问题无法通过现有的直接/间接优化技术来解决。为此目的,已经开发出不同的粒子群优化技术(viz。PSO-Co,WQPSO和GQPSO)以通过使用间隔算术和间隔关系来解决所提出的库存模型的问题。最后,为了说明和验证所提出的模型,已经解决了数值示例,并比较了从PSO的不同变体获得的最佳发现的解决方案(即最佳溶液或接近最佳溶液)。然后,已经进行了敏感性分析,以研究模型不同参数变化对最佳政策的影响。

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