scholarly journals Storage allocation in a warehouse based on the forklifts fleet availability

2018 ◽  
Vol 12 (2) ◽  
pp. 127-135 ◽  
Author(s):  
Iman Ghalehkhondabi ◽  
Dale T Masel
Keyword(s):  
Operation Time ◽  
Working Hours ◽  
Storage Space ◽  
Storage Allocation ◽  
Efficient Utilization ◽  
Product Allocation ◽  
Allocation Model ◽  
Space Allocation ◽  
Storage Space Allocation ◽  
Proposed Model

Product allocation is one of the most important duties in warehousing operations. Based on the time and the number of products to put away and retrieve, storage allocation can directly affect the efficiency of a warehouse in terms of both response and operation time. Traditionally, the product storage allocation is done based on the less distance of shipment but focusing on distance may decrease the efficiency of a warehouse in terms of efficient utilization of resources such as warehouse inbound shipping fleet. This paper proposes a storage space allocation model that considers the availability of forklift fleet in a warehouse instead of product shipping distance. The numerical example shows that storing the products based on the proposed model can reduce the volume of forklift fleet idle hours on days with fewer volume of receiving and shipping outs. The proposed model also reduces the overtime working hours on days with higher volume of receiving and shipping out products.

scholarly journals The outbound container slot allocation based on the stowage plan in rail–water intermodal container terminals

2019 ◽  
Vol 52 (5-6) ◽  
pp. 509-525 ◽  
Author(s):  
Yimei Chang ◽  
Xiaoning Zhu ◽  
Ali Haghani
Keyword(s):  
Influence Factor ◽  
Planning Horizon ◽  
Allocation Problem ◽  
Container Terminals ◽  
Slot Allocation ◽  
Allocation Model ◽  
Space Allocation ◽  
Storage Space Allocation ◽  
Proposed Model ◽  
Stowage Plan

In the past, most researchers focused on the storage space allocation problem or container block allocation problem in maritime container terminals, while few studied the container slot allocation problem in rail–water intermodal container terminals. Container slot allocation problem is proposed to reduce relocation operations of containers in railway container yards and improve the efficiency of rail–water intermodal container terminals. In this paper, a novel outbound container slot allocation model is introduced to reduce the rehandling operations, considering stowage plan, containers left from earlier planning periods and container departure time. A novel heuristic algorithm based on the rolling planning horizon approach is developed to solve the proposed problem effectively. Computational experiments are carried out to validate that the proposed model and algorithm are feasible and effective to enhance the storage effect. Meanwhile, some other experiments are conducted to verify that our approach is better than the regular allocation approach, which is a common method in marine and railway container terminals, and container weight is the most important influence factor when storing containers.

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 allocation optimization model in a Colombian company

DYNA ◽  
2019 ◽  
Vol 86 (209) ◽  
pp. 255-260 ◽  
Author(s):  
Julian Andres Zapata-cortes ◽  
Martin Dario Arango-Serna ◽  
Frank Alexander Ballesteros Riveros ◽  
Wilson Adarme - Jaimes
Keyword(s):  
Optimization Model ◽  
Cost Efficiency ◽  
Time Horizon ◽  
Material Handling ◽  
Storage Allocation ◽  
Product Allocation ◽  
Allocation Model ◽  
Specific Position ◽  
Material Handling Costs ◽  
The Cost

The storage allocation in warehouse is about of deciding the corresponding areas in which the products must be allocated. It can be made using different techniques to stablish the specific position for the products. Some applications provide solutions and evaluate results independently, allowing the identification of its potential in warehouses. This paper presents the application of a storage allocation model in a food company considering several products in a defined time horizon. The algorithm identifies the operation area and the corresponding spaces that are required for the products allocation, aimed to reduce holding and material handling costs. As a result, the application of the algorithm produces a complete product allocation in each period and improves the cost efficiency in the warehouse.

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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