E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking d...E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.展开更多
This paper considers an on-line scheduling and routing problem concerning the automated storage and retrieval system from tobacco industry. In this problem, stacker cranes run on one common rail between two racks. Mul...This paper considers an on-line scheduling and routing problem concerning the automated storage and retrieval system from tobacco industry. In this problem, stacker cranes run on one common rail between two racks. Multiple input/output-points are located at the bottom of the racks. The stacker cranes transport bins between the input/output-points and cells on the racks to complete requests generated over time. Each request should be accomplished within its response time. The objective is to minimize the time by which all the generated requests are completed. Under a given physical layout, the authors study the complexity of the problem and design on-line algorithms for both one-stacker-crane model and two-stacker-crane model. The algorithms are validated by instances and numerical simulations.展开更多
针对自动化立体仓库出库作业过程中剩余货物退库问题,以堆垛机作业总能耗最小化为目标,以退库货位分配为决策变量,建立了自动化立体仓库退库货位优化模型,提出了基于深度强化学习的自动化立体仓库退库货位优化框架。在该框架内,以立体...针对自动化立体仓库出库作业过程中剩余货物退库问题,以堆垛机作业总能耗最小化为目标,以退库货位分配为决策变量,建立了自动化立体仓库退库货位优化模型,提出了基于深度强化学习的自动化立体仓库退库货位优化框架。在该框架内,以立体仓库实时存储信息和出库作业信息构建多维状态,以退库货位选择构建动作,建立自动化立体仓库退库货位优化的马尔科夫决策过程模型;将立体仓库多维状态特征输入双层决斗网络,采用决斗双重深度Q网络(dueling double deep Q-network,D3QN)算法训练网络模型并预测退库动作目标价值,以确定智能体的最优行为策略。实验结果表明D3QN算法在求解大规模退库货位优化问题上具有较好的稳定性。展开更多
Optimization of the operational route in the automated storage/retrieval system （AS/RS） is transformed into the traveling salesman problem, To make the moving distance of the storage/retrieval machine shortest, we c...Optimization of the operational route in the automated storage/retrieval system （AS/RS） is transformed into the traveling salesman problem, To make the moving distance of the storage/retrieval machine shortest, we carry out a group of tests where 20 goods locations are chosed. Using PSO for operational route of AS/RS, the operation time can be shortened by about 11%. The experiments indicate that under the same conditions, the more the goods locations are, the higher the operation efficiency of the storage/retrieval machine is.展开更多
The Shuttle-Based Storage and Retrieval System(SBS/RS)has been widely studied because it is currently the most efficient automated warehousing system.Most of the related existing studies are focused on the prediction ...The Shuttle-Based Storage and Retrieval System(SBS/RS)has been widely studied because it is currently the most efficient automated warehousing system.Most of the related existing studies are focused on the prediction and improvement of the efficiency of such a system at the design stage.Hence,the control of existing SBS/RSs has been rarely investigated.In existing SBS/RSs,some empirical rules,such as storing loads column by column,are used to control or schedule the storage process.The question is whether or not the control of the storage process in an existing system can be improved further by using a different approach.The storage process is controlled to minimize the makespan of storing a series of loads into racks.Empirical storage rules are easy to control,but they do not reach the minimum makespan.In this study,the performance of a control system that uses reinforcement learning to schedule the storage process of an SBS/RS with fixed configurations is evaluated.Specifically,a reinforcement learning algorithm called the actor-critic algorithm is used.This algorithm is made up of two neural networks and is effective in making decisions and updating itself.It can also reduce the makespan relative to the existing empirical rules used to improve system performance.Experiment results show that in an SBS/RS comprising six columns and six tiers and featuring a storage capacity of 72 loads,the actor-critic algorithm can reduce the makespan by 6.67%relative to the column-by-column storage rule.The proposed algorithm also reduces the makespan by more than 30%when the number of loads being stored is in the range of 7–45,which is equal to 9.7%–62.5%of the systems’storage capacity.展开更多
In this paper, we apply the split-platform automated storage/retrieval systems (SP-AS/RSs) (Hu et al., 2005) to store containers in the yard to improve the yard performance and to increase the utilization of the yard ...In this paper, we apply the split-platform automated storage/retrieval systems (SP-AS/RSs) (Hu et al., 2005) to store containers in the yard to improve the yard performance and to increase the utilization of the yard space. The layout of an SP-AS/RS based yard is described in detail. To achieve an efficient operation, we present a novel yard space allocation policy called the ‘second-carrier-based allocation policy’, which can help to alleviate the out-of-sequence problem of containers and the congestion of vehicles at the AS/RS racks. Different allocation policies are compared by an integrated container terminal simulation system. The simulation results show that the second-carrier-based policy is very efficient and has the potential to offer high terminal performance.展开更多
文摘E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.
基金supported by the National Natural Science Foundation of China under Grant No.11371137Research Fund for the Doctoral Program of China under Grant No.20120074110021
文摘This paper considers an on-line scheduling and routing problem concerning the automated storage and retrieval system from tobacco industry. In this problem, stacker cranes run on one common rail between two racks. Multiple input/output-points are located at the bottom of the racks. The stacker cranes transport bins between the input/output-points and cells on the racks to complete requests generated over time. Each request should be accomplished within its response time. The objective is to minimize the time by which all the generated requests are completed. Under a given physical layout, the authors study the complexity of the problem and design on-line algorithms for both one-stacker-crane model and two-stacker-crane model. The algorithms are validated by instances and numerical simulations.
文摘针对自动化立体仓库出库作业过程中剩余货物退库问题,以堆垛机作业总能耗最小化为目标,以退库货位分配为决策变量,建立了自动化立体仓库退库货位优化模型,提出了基于深度强化学习的自动化立体仓库退库货位优化框架。在该框架内,以立体仓库实时存储信息和出库作业信息构建多维状态,以退库货位选择构建动作,建立自动化立体仓库退库货位优化的马尔科夫决策过程模型;将立体仓库多维状态特征输入双层决斗网络,采用决斗双重深度Q网络(dueling double deep Q-network,D3QN)算法训练网络模型并预测退库动作目标价值,以确定智能体的最优行为策略。实验结果表明D3QN算法在求解大规模退库货位优化问题上具有较好的稳定性。
文摘Optimization of the operational route in the automated storage/retrieval system （AS/RS） is transformed into the traveling salesman problem, To make the moving distance of the storage/retrieval machine shortest, we carry out a group of tests where 20 goods locations are chosed. Using PSO for operational route of AS/RS, the operation time can be shortened by about 11%. The experiments indicate that under the same conditions, the more the goods locations are, the higher the operation efficiency of the storage/retrieval machine is.
基金supported by the National Natural Science Foundation of China(No.52075036)and the Natural Science Foundation of Beijing Municipality(No.L191011).
文摘The Shuttle-Based Storage and Retrieval System(SBS/RS)has been widely studied because it is currently the most efficient automated warehousing system.Most of the related existing studies are focused on the prediction and improvement of the efficiency of such a system at the design stage.Hence,the control of existing SBS/RSs has been rarely investigated.In existing SBS/RSs,some empirical rules,such as storing loads column by column,are used to control or schedule the storage process.The question is whether or not the control of the storage process in an existing system can be improved further by using a different approach.The storage process is controlled to minimize the makespan of storing a series of loads into racks.Empirical storage rules are easy to control,but they do not reach the minimum makespan.In this study,the performance of a control system that uses reinforcement learning to schedule the storage process of an SBS/RS with fixed configurations is evaluated.Specifically,a reinforcement learning algorithm called the actor-critic algorithm is used.This algorithm is made up of two neural networks and is effective in making decisions and updating itself.It can also reduce the makespan relative to the existing empirical rules used to improve system performance.Experiment results show that in an SBS/RS comprising six columns and six tiers and featuring a storage capacity of 72 loads,the actor-critic algorithm can reduce the makespan by 6.67%relative to the column-by-column storage rule.The proposed algorithm also reduces the makespan by more than 30%when the number of loads being stored is in the range of 7–45,which is equal to 9.7%–62.5%of the systems’storage capacity.
基金the Agency for Science, Technology and Research, the Maritime and Port Authority,and Nanyang Technological University, Singapore
文摘In this paper, we apply the split-platform automated storage/retrieval systems (SP-AS/RSs) (Hu et al., 2005) to store containers in the yard to improve the yard performance and to increase the utilization of the yard space. The layout of an SP-AS/RS based yard is described in detail. To achieve an efficient operation, we present a novel yard space allocation policy called the ‘second-carrier-based allocation policy’, which can help to alleviate the out-of-sequence problem of containers and the congestion of vehicles at the AS/RS racks. Different allocation policies are compared by an integrated container terminal simulation system. The simulation results show that the second-carrier-based policy is very efficient and has the potential to offer high terminal performance.
