Slotting Optimization Algorithm of the Stereo Warehouse

Article Preview

Abstract:

In order to solve the problem of slotting optimization management with automated storage and retrieval system (AS / RS), the genetic algorithms of the slotting optimization process with stereo warehouse were discussed. The process of the slotting optimization was designed by the real-number coding. The mathematical models of the slotting optimization and cargo shipping time were built, and the simulation calculation of the models was done. The stability of the shelf and the efficiency of the accessing goods were significantly improved by the optimization simulation of the distribution of cargo space, after optimizing the storage order. The algorithms of the slotting optimization with stereo warehouse could effectively enhance the frequency of the stock in & out, increasing the revenue.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 756-759)

Pages:

1371-1376

Citation:

Online since:

September 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] L.Y. Zheng, S.Y. Wang. Slotting Optimization Management of Automated Warehouse. Market Modernization, vol. 10, p.96, (2007).

Google Scholar

[2] Y.L. Jia, L.X. Miu. Study on Optimization Problem of Cargo Space Real-time Allocation in the Automated Warehouse. Journal of Beijing Jiaotao University, vol. 4, p.18–24, (2007).

Google Scholar

[3] M. J. Li. Study on Optimization Methods of Automated Warehousing System. Dalian University of Technology, (2008).

Google Scholar

[4] Lee H F, Schaefer S K. Retrieval Sequencing for Unit Load Automated Storage and Retrieval Systems With Multiple Openings. International Journal of Production Research, Vol. 34, p.2943 –2962, (1996).

DOI: 10.1080/00207549608905067

Google Scholar

[5] C.J. Chen. Study on Intelligent Scheduling of Automated Warehouse. Mechanical Institute of Science and Technology, (2006).

Google Scholar

[6] E Zitzler,L Thiele. Multi-objective Evolutionary Algorithm a Comparative Case Study and the Strength Pareto Approach. IEEE Trans on Evolutionary Computation, Vol. 3, p.257–271, (1999).

DOI: 10.1109/4235.797969

Google Scholar

[7] Fonseca C M, Fleming P J. An Overview of Evolutionary Algorithms in Multi-objective Optimization. Evolutionary Computation, Vol. 3, p.165–180, (1995).

Google Scholar

[8] Y. Pan. Research on Automated Stereoscopic Warehouse Based on Modern Logistics. Suzhou University, (2008).

Google Scholar

[9] J.G. Lu, Q. Li. Genetic Algorithm and Engineering Applications. Press of China Mining University, p.23–35, (1997).

Google Scholar

[10] H. Zheng. Study on Routing Optimization Problem of Automated Warehouse. Jilin University, (2006).

Google Scholar

[11] Lina Sha. Management Methods of Slotting Optimization for Automated Warehouse. Dongbei University, (2005).

Google Scholar