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Modeling and optimization for the joint replenishment and delivery problem with heterogeneous items

机译：异质物料联合补货和交货问题的建模和优化

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摘要

In the real world, some heterogeneous items are prohibited from being transported together or penalty cost occurs when transporting them together. This paper firstly proposes the joint replenishment and delivery URD) model where a warehouse procures multi heterogeneous items from suppliers and deliveries them to retailers. The problem is to determine the grouping decision and when and how many to order and delivery to the warehouse and retailers such that the total costs are minimized. However, due to the JRD's difficult mathematical properties, simple and effective solutions for this problem have eluded researchers. To find an optimal solution, an adaptive hybrid differential evolution (AHDE) algorithm is designed. Results of contrastive numerical examples show that AHDE outperforms genetic algorithm. The effectiveness of AHDE is further verified by randomly generated problems. The findings show that AHDE is more stable and robust in handling this complex problem.
机译：在现实世界中，某些异类物品被禁止一起运输，否则一起运输时会产生罚款。本文首先提出了一种联合补货和交货模型，在该模型中，仓库从供应商那里采购多种异质物品，然后将其交付给零售商。问题在于确定分组决策以及何时以及多少订购和交付给仓库和零售商，以使总成本最小化。但是，由于JRD的困难的数学性质，研究人员还没有针对此问题的简单有效的解决方案。为了找到最佳解决方案，设计了一种自适应混合差分进化（AHDE）算法。对比数值例子的结果表明，AHDE优于遗传算法。随机产生的问题进一步验证了AHDE的有效性。研究结果表明，AHDE在处理此复杂问题方面更加稳定和强大。

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