在一种新型的层控式双容量升降AVS/RS中检索请求测序

Jingjing Yang, Xiaolong Guo, Ran Chen, Zhaotong Wang
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引用次数: 0

摘要

我们研究了一种创新的自动车辆存储和检索系统,该系统配备了双容量升降机(AVS/RS-DL),其中升降机能够同时运输两个单元负载。因此,给定一组检索请求,检索排序问题包括决定哪些请求在同一行程中配对在一起,以及确定处理请求的顺序以最小化makespan。这个问题被证明是np困难的。我们提出了一种两步分解算法,该算法首先采用贪婪启发式算法来识别检索请求对。随后,利用动态规划方法,辅以推出启发式方法,确定这些对的序列。对比数值实验表明,与文献中提出的方法相比,该算法可以大大减少最大完工时间。此外,我们还研究了双容量升降机相对于单容量替代品的好处,以及可以并行操作但不能相互通过的单独升降台。现实世界的数据分析表明,我们提出的算法优于通常采用的先到先得策略。最后,我们证明了我们的算法可以很容易地扩展,以适应不同的缓冲区大小,多容量提升,并同时对检索和存储请求进行排序。
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Retrieval request sequencing in a novel tier-captive AVS/RS with a double-capacity lift
We study an innovative autonomous vehicle storage and retrieval system equipped with a double-capacity lift (AVS/RS-DL), where the lift is capable of transporting two unit loads simultaneously. Therefore, given a set of retrieval requests, the retrieval sequencing problem consists of deciding which requests are paired together in the same tour and determining the sequence in which the requests are processed to minimize the makespan. The problem is proved to be NP-hard. We propose a two-step decomposition algorithm that first employs a greedy heuristic to identify pairs of retrieval requests. Subsequently, a dynamic programming approach, complemented by a rollout heuristic, is utilized to determine the sequence of these pairs. Comparative numerical experiments demonstrate that the algorithm leads to substantial makespan reduction compared to the methods proposed in the literature. Furthermore, we examine the benefits of the double-capacity lift against single-capacity alternatives and separate lifting tables that can operate in parallel but not pass each other. Real-world data analysis showcases the superiority of our proposed algorithm over the commonly employed first-come-first-served policy. Finally, we demonstrate that our algorithm can easily be extended to accommodate varying buffer sizes, a multi-capacity lift, and to simultaneously sequence both retrieval and storage requests.
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来源期刊
CiteScore
16.20
自引率
16.00%
发文量
285
审稿时长
62 days
期刊介绍: Transportation Research Part E: Logistics and Transportation Review is a reputable journal that publishes high-quality articles covering a wide range of topics in the field of logistics and transportation research. The journal welcomes submissions on various subjects, including transport economics, transport infrastructure and investment appraisal, evaluation of public policies related to transportation, empirical and analytical studies of logistics management practices and performance, logistics and operations models, and logistics and supply chain management. Part E aims to provide informative and well-researched articles that contribute to the understanding and advancement of the field. The content of the journal is complementary to other prestigious journals in transportation research, such as Transportation Research Part A: Policy and Practice, Part B: Methodological, Part C: Emerging Technologies, Part D: Transport and Environment, and Part F: Traffic Psychology and Behaviour. Together, these journals form a comprehensive and cohesive reference for current research in transportation science.
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