An intelligent optimization approach for storage space allocation at seaports: A case study

2015 ◽  
Author(s):  
Gamal Abd El-Nasser A. Said ◽  
El-Sayed M. El-Horbaty
Keyword(s):  
Optimization Approach ◽  
Storage Space ◽  
Intelligent Optimization ◽  
Space Allocation ◽  
Storage Space Allocation

Multiple Equipment Integrated Scheduling and Storage Space Allocation in Rail–Water Intermodal Container Terminals Considering Energy Efficiency

2019 ◽  
Vol 2673 (3) ◽  
pp. 199-209 ◽  
Author(s):  
Yijia Yang ◽  
Xiaoning Zhu ◽  
Ali Haghani
Keyword(s):  
Energy Consumption ◽  
Large Scale ◽  
Operation Time ◽  
Container Terminals ◽  
Optimization Approach ◽  
Storage Space ◽  
Integrated Scheduling ◽  
Space Allocation ◽  
Storage Space Allocation ◽  
And Storage

The rail–water coordinated operation area in a container terminal is the key place to operate the transshipment of intermodal containers between the rail and the sea—the handling efficiency in which can affect the overall transport turnover efficiency. A complicated operational process for various handling equipment exists in this coordinated operation area and can lead to a large amount of energy consumption and environmental pollution. This study proposes an integrated optimization approach to manage the multiple equipment integrated scheduling and storage space allocation problem in an energy-efficient way. A bi-objective optimization model is proposed to minimize the overall operation time and energy consumption, in which the handling operations of imported and exported intermodal containers are considered simultaneously. A genetic algorithm based heuristic algorithm is developed to solve the problem. Results from computational experiments indicate the feasibility and effectiveness of the proposed model and algorithm, verifying that a near-optimum solution can be obtained for large-scale problems efficiently, which contributes to the improvement of operation services in rail–water intermodal container terminals.

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 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.

scholarly journals A Novel Two-Stage Heuristic for Solving Storage Space Allocation Problems in Rail–Water Intermodal Container Terminals

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1229 ◽  
Author(s):  
Chang ◽  
Zhu
Keyword(s):  
Simulated Annealing Algorithm ◽  
Allocation Problem ◽  
Container Terminals ◽  
Storage Space ◽  
Two Stage ◽  
Space Allocation ◽  
Storage Space Allocation ◽  
Annealing Algorithm ◽  
Stage 1 ◽  
Railway Operation

In the past, most researchers have paid attention to the storage space allocation problem in maritime container terminals, while few have studied this problem in rail–water intermodal container terminals. Therefore, this paper proposes a storage space allocation problem to look for a symmetry point between the efficiency and effectivity of rail–water intermodal container terminals and the unbalanced allocations and reallocation operations of inbound containers in the railway operation area, which are two interactive aspects. In this paper, a two-stage model on the storage space allocation problem is formulated, whose objective is to balance inbound container distribution and minimize overlapping amounts, considering both stacking principles, such as container departure time, weight and stacking height, and containers left in railway container yards from earlier planning periods. In Stage 1, a novel simulated annealing algorithm based on heuristics is introduced and a new heuristic algorithm based on a rolling horizon approach is developed in Stage 2. Computational experiments are implemented to verify that the model and algorithm we introduce can enhance the storage effect feasibly and effectively. Additionally, two comparison experiments are carried out: the results show that the approach in the paper performs better than the regular allocation approach and weight constraint is the most important influence on container storage.

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.

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