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Dual command cycle dynamic sequencing method to consider GHG efficiency in unit-load multiple-rack automated storage and retrieval systems

机译:在单位负载多机架自动存储和检索系统中考虑温室气体效率的双指令周期动态排序方法

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In some AS/RS, the S/R machine executes a storage request and then a retrieval request to form a dual command (DC) cycle. This paper deals with a DC cycle “dynamic sequencing” method in unit-load multiple-rack AS/RS system. To create a kind of greenhouse gas (GHG) efficiency in the model, tax cost, penalty cost and discount of produced GHG emissions, limitations on available time of all facilities and total permitted GHG emissions produced by all equipment are considered in the model. In addition, an ant colony optimization (ACO) is employed to find a near-optimum solution of proposed mathematical model with the objective of minimizing the total cost of the GHG efficiency in AS/RS. Since no benchmark is available in the literature, a genetic algorithm (GA) is developed as well to validate the result obtained. For further validation, warehouse throughput rate in terms of time and cost is calculated for the model. At the end, twenty numerical examples are presented to demonstrate the application of the proposed methodology. Our results verified that GA was able to find better and nearer optimal solutions.
机译:在某些AS / RS中,S / R机器先执行存储请求,然后执行检索请求,以形成双命令(DC)周期。本文研究了单位负载多机架AS / RS系统中的直流循环“动态排序”方法。为了在模型中创建一种温室气体(GHG)效率,模型中考虑了税收成本,罚款成本和产生的温室气体排放折扣,所有设施可用时间的限制以及所有设备产生的允许的温室气体排放总量。此外,采用蚁群优化(ACO)来找到拟议数学模型的近似最优解,目的是使AS / RS中的温室气体效率总成本最小化。由于文献中没有基准可用,因此也开发了遗传算法(GA)来验证获得的结果。为了进一步验证,针对该模型计算了时间和成本方面的仓库吞吐率。最后,给出了二十个数值例子来说明所提出方法的应用。我们的结果证明了GA能够找到更好,更接近最优的解决方案。

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