Optimization of Storage Location Assignment for Fixed Rack Systems

2010 ◽  
pp. 29-35 ◽  
Author(s):  
Qinghong Wu ◽  
Ying Zhang ◽  
Zongmin Ma
Keyword(s):  
Storage Location ◽  
Location Assignment

scholarly journals Particle Swarm Optimization Using Neighborhood-Based Mutation Operator and Intermediate Disturbance Strategy for Outbound Container Storage Location Assignment Problem

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Yuyan He ◽  
Aihu Wang ◽  
Hailiang Su ◽  
Mengyao Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Assignment Problem ◽  
Particle Swarm ◽  
Local Solution ◽  
Mutation Operator ◽  
Swarm Optimization ◽  
Intermediate Disturbance ◽  
Storage Location ◽  
Location Assignment ◽  
Container Storage Location Assignment

Outbound container storage location assignment problem (OCSLAP) could be defined as how a series of outbound containers should be stacked in the yard according to certain assignment rules so that the outbound process could be facilitated. Considering the NP-hard nature of OCSLAP, a novel particle swarm optimization (PSO) method is proposed. The contributions of this paper could be outlined as follows: First, a neighborhood-based mutation operator is introduced to enrich the diversity of the population to strengthen the exploitation ability of the proposed algorithm. Second, a mechanism to transform the infeasible solutions into feasible ones through the lowest stack principle is proposed. Then, in the case of trapping into the local solution in the search process, an intermediate disturbance strategy is implemented to quickly jump out of the local solution, thereby enhancing the global search capability. Finally, numerical experiments have been done and the results indicate that the proposed algorithm achieves a better performance in solving OCSLAP.

Constrained clustering method for class-based storage location assignment in warehouse

2016 ◽  
Vol 116 (4) ◽  
pp. 667-689 ◽  
Author(s):  
Chao-Lung Yang ◽  
Thi Phuong Quyen Nguyen
Keyword(s):  
Principal Component ◽  
Constrained Clustering ◽  
Clustering Method ◽  
Content Type ◽  
Assignment Model ◽  
Retrieval Efficiency ◽  
Storage Location ◽  
Component Loadings ◽  
Location Assignment

Purpose – Class-based storage has been studied extensively and proved to be an efficient storage policy. However, few literature addressed how to cluster stuck items for class-based storage. The purpose of this paper is to develop a constrained clustering method integrated with principal component analysis (PCA) to meet the need of clustering stored items with the consideration of practical storage constraints. Design/methodology/approach – In order to consider item characteristic and the associated storage restrictions, the must-link and cannot-link constraints were constructed to meet the storage requirement. The cube-per-order index (COI) which has been used for location assignment in class-based warehouse was analyzed by PCA. The proposed constrained clustering method utilizes the principal component loadings as item sub-group features to identify COI distribution of item sub-groups. The clustering results are then used for allocating storage by using the heuristic assignment model based on COI. Findings – The clustering result showed that the proposed method was able to provide better compactness among item clusters. The simulated result also shows the new location assignment by the proposed method was able to improve the retrieval efficiency by 33 percent. Practical implications – While number of items in warehouse is tremendously large, the human intervention on revealing storage constraints is going to be impossible. The developed method can be easily fit in to solve the problem no matter what the size of the data is. Originality/value – The case study demonstrated an example of practical location assignment problem with constraints. This paper also sheds a light on developing a data clustering method which can be directly applied on solving the practical data analysis issues.

A Genetic Algorithm for Minimizing Relocations at Container Yard in Container Terminal

2014 ◽  
Vol 931-932 ◽  
pp. 1683-1688
Author(s):  
Phatchara Sriphrabu ◽  
Kanchana Sethanan ◽  
Somnuk Theerakulpisut
Keyword(s):  
Genetic Algorithm ◽  
Current Practice ◽  
Container Terminal ◽  
Experimental Result ◽  
Container Ship ◽  
Storage Assignment ◽  
Storage Location ◽  
Location Assignment

This paper focuses on storage location assignment and exported container relocation in container yard of container terminal with the objective of minimizing the number of container lifting. On the lifting steps, the truck with yard crane should be chosen in order to deliver a container from container yard to container ship, and this action can reduce container ship's docking time and increase effectiveness in container terminal service. In this paper, a genetic algorithm (GA) in container storage assignment and a heuristic for the container relocation determination are adopted. Also, the current practice including first-in-first-stored (FIFS) and simple relocation (SR) is used to compare the effectiveness of the GA and the proposed heuristic (RH). The experimental result presented that the proposed method is able to construct the effective solutions of storage location assignment of exported containers, and it reduces the number of relocations of exported container effectively.

scholarly journals Research on Dynamic Storage Location Assignment of Picker-to-Parts Picking Systems under Traversing Routing Method

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xiangbin Xu ◽  
Chenhao Ren
Keyword(s):  
Average Order ◽  
Online Retail ◽  
Whole Process ◽  
Operation Process ◽  
Storage Location ◽  
Final Adjustment ◽  
Location Assignment ◽  
Dynamic Storage ◽  
Varying Demand ◽  
Demand Correlation

Considering time-varying demand of online retail industry, the traditional static storage location assignment is converted into a multistage storage location assignment process based on the idea of gradual and small-step-forward optimization, which can respond to rapid changes in demand by adjusting the storage location of SKUs in the warehouse in real time and dynamically. First, the study formulates the framework dynamic storage location assignment. Then, the adjustment gain model of dynamic storage location assignment is built, and a genetic algorithm is designed to find the final adjustment solution. Finally, the computer program is developed to simulate the whole process. Simulation and data analysis results show that dynamic storage location assignment can effectively improve picking efficiency when the average order size is small and large demand correlation strength. Dynamic storage location assignment simplifies the warehouse operation process by combining the picking operation and storage location assignment into one without changing the picker’s current walking route, which can offer some theoretical guidance for online retail enterprises implementing dynamic storage location assignment.

scholarly journals The storage location assignment problem: A literature review

2019 ◽  
pp. 199-224 ◽  
Author(s):  
Juan José Rojas Reyes ◽  
Elyn Lizeth Solano-Charris ◽  
Jairo Rafael Montoya-Torres
Keyword(s):  
Literature Review ◽  
Assignment Problem ◽  
Storage Location ◽  
Location Assignment
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