Optimization of Automated Warehouse Storage Location Assignment Problem Based on Improved Genetic Algorithm

Class-based stereo warehouse storage policy distributes products among a number of classes and for each class it reserves a region within the storage area. In this paper, a genetic algorithm method of using the intersectant operation of chromosome repair and mutation operation of two-way movement detection is developed to solve an integer programming model for storage assignment. Computational experience on randomly generated data sets and an industrial case shows that improved genetic algorithm gives superior results than the genetic algorithm without improving for storage location assignment with ordering restriction.

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EFFICIENT STORAGE LOCATION ASSIGNMENT USING GENETIC ALGORITHM IN WAREHOUSE MANAGEMENT SYSTEM.

International Journal of Advanced Research ◽

10.21474/ijar01/757 ◽

2016 ◽

Vol 4 (6) ◽

pp. 18-24

Author(s):

V.Uma Rani ◽

◽

J.LinEby Chandra ◽

D. Jayashree ◽

◽

...

Keyword(s):

Genetic Algorithm ◽

Management System ◽

Warehouse Management ◽

Efficient Storage ◽

Storage Location ◽

Location Assignment ◽

Warehouse Management System

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

Mathematical Problems in Engineering ◽

10.1155/2019/9132315 ◽

2019 ◽

Vol 2019 ◽

pp. 1-13 ◽

Cited By ~ 2

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.

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

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.931-932.1683 ◽

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.

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