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Shelf space allocation problem with horizontal shelf division

机译：水平货架部门的货架空间分配问题

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The retailers are interested in different profit maximization approaches, which help them to perform daily shelf arrangement tasks, improve customers’ satisfaction and avoid out of stocks on the shelves. Most of the retail literature proposes basic models which don’t reflect complicated merchandising rules. The aim of the paper is to develop a shelf space allocation model which investigates vertical shelf levels, horizontal shelf division into segments, and product item allocation rules such as cappings and nestings. A genetic algorithm has been developed to implement the model. The efficiency was estimated with the help of CPLEX solver. The computational experiments show that the proposed approach allows getting the results of sufficient quality for different problem sizes in a short running time without requiring large computing resources. GA and CPLEX found statistically the same profitable solution within the same computational time. However, GA found a better solution in situations where the commercial solver can’t perform calculations during the increased computational time and stopped after a couple of minutes. This proves the reason for GA implementation for shelf space allocation problems.
机译：零售商对不同的利润最大化方法感兴趣，这有助于他们执行日常货架安排任务，提高客户的满意度，避免货架上的股票。大多数零售文献提出了不反映复杂的销售规则的基本模式。本文的目的是开发一个货架空间分配模型，调查垂直货架级别，水平货架划分到段，以及诸如Cappings和嵌套的产品项目分配规则。已经开发了一种遗传算法来实现模型。在CPLEL求解器的帮助下估计了效率。计算实验表明，所提出的方法允许在短时间内，在短时间内，在短时间内，在不需要大型计算资源的情况下使不同的问题大小的质量的结果。 GA和CPLEX在相同的计算时间内发现了统计上相同的盈利解决方案。然而，GA在商业求解器在增加计算时间内无法执行计算并在几分钟后停止的情况下找到更好的解决方案。这证明了GA实施货架空间分配问题的原因。

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