Solving Stereo Warehouse Storage Location Assignment Problem Based on Genetic Algorithm

Meng Jin; Xi Hui Mu; Liang Chun Li; Feng Po Du

doi:10.4028/www.scientific.net/AMM.307.459

Paper Titles

Robust Scheduling, a Production Scheduling Model of Failures
p.443

A Service-Oriented After-Sales Services System in Mechanical Engineering Industry
p.447

Effective Design and Implementation of Distributed Business Information Systems
p.451

Research on the Development of the Coal-Electricity Integration Manufacturing Industry
p.455

Solving Stereo Warehouse Storage Location Assignment Problem Based on Genetic Algorithm
p.459

Preliminary Study on Voxel-Based Virtual Geographic Environment Representation
p.464

Predictive - Reactive Strategy for Real Time Scheduling of Manufacturing Systems
p.470

PDF417 Barcode and its Application in Aviation Spare Parts Management
p.474

On the Effective Internet Communication Filtering
p.478

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 307Solving Stereo Warehouse Storage Location...

Solving Stereo Warehouse Storage Location Assignment Problem Based on Genetic Algorithm

Abstract:

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.

You might also be interested in these eBooks

Mechatronics and Computational Mechanics

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 307)

Pages:

459-463

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.307.459

Citation:

Cite this paper

Online since:

February 2013

Authors:

Meng Jin, Xi Hui Mu, Liang Chun Li, Feng Po Du

Keywords:

Chromosome Repairment, Genetic Algorithm (GA), Stereo Warehouse Storage Location Assignment, Two-Way Movement Detection

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Li S, Ragu-Nathan B, Ragu-Nathan TS, Subba Rao S. The impact of supply chain management practices on competitive advantage and organizational performance. Omega 2006; 34(2): 107–24.

DOI: 10.1016/j.omega.2004.08.002

Google Scholar

[2] Wen U-P, Chang D-T. Picking rules for a carousel conveyor in an automated warehouse. Omega 1988; 16(2): 145–51.

DOI: 10.1016/0305-0483(88)90045-x

Google Scholar

[3] Frazelle E. World-class warehousing and material handling. New York, NY: McGraw-Hill; (2002).

Google Scholar

[4] Hausman WH, Schwarz LB, Graves SC. Optimal storage assignment in automatic warehousing systems. Management Science 1976; 22(6): 629–38.

DOI: 10.1287/mnsc.22.6.629

Google Scholar

[5] Petersen CG, Aase GR, Heiser DR. Improving order-picking performance through the implementation of class-based storage. International Journal of Physical Distribution and Logistics Management 2004; 34(7): 534–44.

DOI: 10.1108/09600030410552230

Google Scholar

[6] V.R. Muppani (Muppant), G.K. Adil Efﬁcient formation of storage classes forwarehouse storage location assignment: Asimulated annealing approach. Omega 36 (2008) 609 – 618.

DOI: 10.1016/j.omega.2007.01.006

Google Scholar