.png){kind=icon}
返回
An approximate dynamic programming approach for the empty container allocation problem
.png){kind=icon}
PRE
AI
DOI：10.1016/j.trc.2007.04.005.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The objective of this study is to demonstrate the successful application of an approximate dynamic programming approach in deriving effective operational strategies for the relocation of empty containers in the containerized sea-cargo industry. A dynamic stochastic model for a simple two-ports two-voyages (TPTV) system is proposed first to demonstrate the effectiveness of the approximate optimal solution obtained through a simulation based approach known as the temporal difference (TD) learning for average cost minimization. An exact optimal solution can be obtained for this simple TPTV model. Approximate optimal results from the TPTV model utilizing a linear approximation architecture under the TD framework can then be compared to this exact solution. The results were found comparable and showed promising improvements over an existing commonly used heuristics. The modeling and solution approach can be extended to a realistic multiple-ports multiple-voyages (MPMV) system. Some results for the MPMV case are shown. (C) 2007 Elsevier Ltd. All rights reserved.
Keyword:
dynamic container allocation
temporal difference learning
average cost minimization
sea cargo
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.9
论文数:
4.7K
被引数:
3.2W
机构
暂无机构信息
引用论文
Comparing neuro-dynamic programming algorithms for the vehicle routing problem with stochastic demands具有随机需求的车辆路径问题的神经动态规划算法比较
.png){kind=icon}
PREAI
分享收藏
分享收藏Call admission control and routing in integrated services networks using neuro-dynamic programming
OAAI
OAAI分享收藏分享收藏
查看更多内容