Storage space allocation models for inbound containers in an automatic container terminal

2013 ◽  
Vol 226 (1) ◽  
pp. 32-45 ◽  
Author(s):  
Mingzhu Yu ◽  
Xiangtong Qi
Keyword(s):  
Container Terminal ◽  
Storage Space ◽  
Space Allocation ◽  
Storage Space Allocation

Optimizing Solution for Storage Space Allocation Problem in Container Terminal Using Genetic Algorithm

2016 ◽  
pp. 159-184
Author(s):  
Gamal Abd El-Nasser A. Said ◽  
El-Sayed M. El-Horbaty
Keyword(s):  
Genetic Algorithm ◽  
Service Time ◽  
Container Terminal ◽  
Study Data ◽  
Allocation Problem ◽  
Container Terminals ◽  
Storage Space ◽  
Space Allocation ◽  
Storage Space Allocation ◽  
Np Hard Problem

Seaport container terminals are essential nodes in sea cargo transportation networks. In container terminal, one of the most important performance measures in container terminals is the service time. Storage space allocation operations contribute to minimizing the vessel service time. Storage space allocation problem at container terminals is a combinatorial optimization NP-hard problem. This chapter proposes a methodology based on Genetic Algorithm (GA) to optimize the solution for storage space allocation problem. A new mathematical model that reflects reality and takes into account the workload balance among different types of storage blocks to avoid bottlenecks in container yard operations is proposed. Also the travelling distance between vessels berthing positions and storage blocks at container yard is considered in this research. The proposed methodology is applied on a real case study data of container terminal in Egypt. The computational results show the effectiveness of the proposed methodology.

scholarly journals Storage Space Allocation of Inbound Container in Railway Container Terminal

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Li Wang ◽  
Xiaoning Zhu ◽  
Zhengyu Xie
Keyword(s):  
Container Terminal ◽  
Solution Algorithm ◽  
Allocation Problem ◽  
Container Terminals ◽  
Optimization Models ◽  
Rolling Horizon ◽  
Storage Space ◽  
Space Allocation ◽  
Storage Space Allocation ◽  
Efficient Storage

Efficient storage strategy of railway container terminals is important in balancing resource utilization, reducing waiting time, and improving handling efficiency. In this paper, we consider the formulation and solution algorithm for storage space allocation problem of inbound containers in railway container terminal. The problem is formulated as two-stage optimization models, whose objectives are balancing the workload of inbound containers and reducing the overlapping amounts. An algorithm implement process based on rolling horizon approach is designed to solve the proposed models. Computational experiments on an actual railway container terminal show that the proposed approach is effective to solve space allocation problem of inbound container and is significant for the operation and organization of railway container terminals.

scholarly journals Storage Space Allocation Strategy for Digital Data with Message Importance

Entropy ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 591
Author(s):  
Shanyun Liu ◽  
Rui She ◽  
Zheqi Zhu ◽  
Pingyi Fan
Keyword(s):  
Data Compression ◽  
Optimal Allocation ◽  
Reconstruction Error ◽  
Digital Data ◽  
Storage Space ◽  
Allocation Strategy ◽  
Storage Size ◽  
Space Allocation ◽  
Storage Space Allocation ◽  
Data Value

This paper mainly focuses on the problem of lossy compression storage based on the data value that represents the subjective assessment of users when the storage size is still not enough after the conventional lossless data compression. To this end, we transform this problem to an optimization, which pursues the least importance-weighted reconstruction error in data reconstruction within limited total storage size, where the importance is adopted to characterize the data value from the viewpoint of users. Based on it, this paper puts forward an optimal allocation strategy in the storage of digital data by the exponential distortion measurement, which can make rational use of all the storage space. In fact, the theoretical results show that it is a kind of restrictive water-filling. It also characterizes the trade-off between the relative weighted reconstruction error and the available storage size. Consequently, if a relatively small part of total data value is allowed to lose, this strategy will improve the performance of data compression. Furthermore, this paper also presents that both the users’ preferences and the special characteristics of data distribution can trigger the small-probability event scenarios where only a fraction of data can cover the vast majority of users’ interests. Whether it is for one of the reasons above, the data with highly clustered message importance is beneficial to compression storage. In contrast, from the perspective of optimal storage space allocation based on data value, the data with a uniform information distribution is incompressible, which is consistent with that in the information theory.

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